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Medical Patent Abstract
A system and method for providing computerized, knowledge-based
medical diagnostic and treatment advice. The medical advice is provided
to the general public over a telephone network. Two new authoring
languages, interactive voice response and speech recognition are
used to enable expert and general practitioner knowledge to be encoded
for access by the public. "Meta" functions for time-density
analysis of a number of factors regarding the number of medical
complaints per unit of time are an integral part of the system.
A semantic discrepancy evaluator routine along with a mental status
examination are used to detect the consciousness level of a user
of the system. A re-enter feature monitors the user's changing condition
over time. A symptom severity analysis helps to respond to the changing
conditions. System sensitivity factors may be changed at a global
level or other levels to adjust the system advice as necessary.
Medical Patent Claims
What is claimed is:
1. A computerized system for use in medical diagnosis, the system
comprising: a data structure configured to be accessed by a plurality
of attributes representative of a medical condition of a patient
and providing one or more selected medical diagnoses for the patient,
wherein a first attribute corresponds to a cause of disease and
a second attribute corresponds to an anatomic system of the patient
affected by the medical condition, wherein the provided data is
identified as being located within the data structure based on the
plurality of attributes, and wherein the data structure is stored
in a memory.
2. The system of claim 1, wherein each cause of disease is subdivided
into subcauses of disease.
3. The system of claim 1, wherein each anatomic system is subdivided
into anatomic subsystems.
4. The system of claim 2, wherein the subcauses of disease are
further divided into sublists of subcauses of disease.
5. The system of claim 3, wherein the anatomic subsystems are further
divided into sublists of anatomic subsystems.
6. The system of claim 1, wherein a third attribute is time.
7. The system of claim 6, wherein the time corresponds to a system
clock time of a consultation with the patient.
8. The system of claim 1, wherein the data structure is a two-dimensional
array.
9. The system of claim 1, wherein the data structure is a three-dimensional
cube.
10. The system of claim 1, wherein the anatomic systems include
cardiovascular, respiratory, nervous, digestive/gastrointestinal,
ear/nose/throat (ENT), ophthalmologic, gynecologic/obstetric, urologic,
blood/hematological, skin/dermatological, bones/orthopedic, and
endocrine.
11. The system of claim 1, wherein the causes of disease include
allergy, environment, infection, mental, poison, trauma, vascular,
genetic, nutritional/metabolic/endocrine, and tumor.
12. The system of claim 11, wherein infection is subdivided into
bacterial infection and viral infection.
13. The system of claim 12, wherein bacterial infection is further
divided into gram positive and gram negative.
14. The system of claim 1, wherein the memory is a disk drive.
15. The system of claim 1, wherein the memory is a floppy disk,
a CD-ROM, or a PC memory card.
16. A computerized method used in medical diagnosis, the method
comprising: ascertaining a plurality of attributes representative
of a medical condition of a patient, wherein a first attribute is
associated with a cause of disease and a second attribute is associated
with an anatomic system of the patient affected by the medical condition;
accessing a data structure based on the plurality of attributes;
and identifying a plurality of selected medical diagnoses in rank
order associated with a diagnosis of the patient based on the accessing.
17. The method of claim 16, additionally comprising storing the
data structure in a memory of a computer.
18. The method of claim 16, additionally comprising providing the
selected medical diagnoses for the patient from the data structure.
19. The method of claim 16, wherein each cause of disease is subdivided
into subcauses of disease.
20. The method of claim 16, wherein each anatomic system is subdivided
into anatomic subsystems.
21. The method of claim 16, wherein the data structure is a two-dimensional
array.
22. The method of claim 16, wherein the data structure is a three-dimensional
cube.
23. The method of claim 16, additionally comprising storing the
data structure in a disk drive.
24. The method of claim 16, additionally comprising storing the
data structure on a floppy disk, a CD-ROM, or a PC memory card.
25. A computer usable medium having computer readable program code
embodied therein for performing a computerized process used in medical
diagnosis, the computer readable code comprising instructions for:
ascertaining a plurality of attributes representative of a medical
condition of a patient, wherein a first attribute is associated
with a cause of disease and a second attribute is associated with
an anatomic system of the patient affected by the medical condition;
accessing a data structure based on the plurality of attributes;
and identifying a plurality of selected medical diagnoses in rank
order associated with a diagnosis of the patient based on the accessing.
26. The computer usable medium of claim 25, the computer readable
code additionally comprising instructions for providing the selected
medical diagnoses for the patient from the data structure.
27. The computer usable medium of claim 26, wherein the cause of
disease is subdivided into subcauses of disease.
28. The computer usable medium of claim 26, wherein the anatomic
system is subdivided into anatomic subsystems.
Medical Patent Description
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to medical knowledge systems and,
more particularly, to systems for giving medical advice to the general
public over a telephone network.
2. Description of the Related Technology
Health care costs currently represent 14% of the United States
Gross National Product and are rising faster than any other component
of the Consumer Price Index. Moreover, usually because of an inability
to pay for medical services, many people are deprived of access
to even the most basic medical care and information.
Many people delay in obtaining, or are prevented from seeking,
medical attention because of cost, time constraints, or inconvenience.
If the public had universal, unrestricted and easy access to medical
information, many diseases could be prevented. Likewise, the early
detection and treatment of numerous diseases could keep many patients
from reaching the advanced stages of illness, the treatment of which
is a significant part of the financial burden attributed to our
nation's health care system. It is obvious that the United States
is facing health-related issues of enormous proportions and that
present solutions are not robust.
One prior attempt at a solution to the health care problem is called
Ask-A-Nurse, wherein a group of nurses provide health information
by telephone around-the-clock. A person with a medical problem calls
an 800 number and describes the problem to the nurse. The nurse
uses a computer for general or diagnostic information on the ailment
or complaint mentioned by the caller. The nurse may then refer the
caller to a doctor from a computerized referral list for a contracting
hospital or group of hospitals. Client hospitals contract with Ask-A-Nurse
to provide patient referrals. A managed care option called Personal
Health Advisor is similar and adds the capability for the caller
to hear prerecorded messages on health topics 24 hours a day. Several
problems exist with these prior medical advice systems. First, these
systems have high costs associated with having a nurse answer each
telephone call. Second, the caller may have to belong to a participating
health plan to utilize the service. Third, if for some reason all
nurses on a particular shift happen to be busy and the caller has
an emergency condition (that is not known by the caller to be an
emergency), precious time in getting emergency services may be lost
during the delay.
Another prior health system was developed by InterPractice Systems
which provides a computerized service that answers health care questions
and advises people in their homes. A health maintenance organization
(HMO) may provide this service to its members in a particular geographic
area. To get advice at home, an HMO member connects a toaster-sized
box to a telephone and calls a toll-free 800 number. Using a keyboard
that is part of the box, the user answers questions displayed on
a screen of the box relating to the user's symptoms. Depending on
the answers, the user might be told to try a home remedy, be called
by a nurse or doctor, or be given an appointment to be examined.
A limitation of this system is the additional expense of the electronics
box, which could either be purchased by the user for approximately
$300 or purchased by the health organization with the expense to
be passed on to the users. Another limitation is that this service
is directed to members of a particular contracting health organization,
such as an HMO. What is desired is a system that does not require
additional hardware for the basic service, but that utilizes the
existing communication network. The desired system should be available
for use by any person, not just members of a certain organization.
A prior attempt at a health care solution for a limited set of
conditions is described in U.S. Pat. No. 4,712,562. A patient's
blood pressure and heart rate are measured and the measurements
are sent via telephone to a remote central computer for storage
and analysis. Reports are generated for submission to a physician
or the patient. U.S. Pat. No. 4,531,527 describes a similar system,
wherein the receiving office unit automatically communicates with
the physician under predetermined emergency circumstances.
U.S. Pat. No. 4,838,275 discloses a device for a patient to lay
on or sit in having electronics to measure multiple parameters related
to a patient's health. These parameters are electronically transmitted
to a central surveillance and control office where a highly trained
observer interacts with the patient. The observer conducts routine
diagnostic sessions except when an emergency is noted or from a
patient-initiated communication. The observer determines if a nonroutine
therapeutic response is required, and if so facilitates such a response.
As previously mentioned, highly trained people are needed by this
system along with the special measurement apparatus (embedded in
a bed or chair).
Other prior attempts at a health care solution are typified by
U.S. Pat. No. 5,012,411 which describes a portable self-contained
apparatus for measuring, storing and transmitting detected physiological
information to a remote location over a communication system. The
information is evaluated by a physician or other health professional.
As before, highly trained people are necessary to utilize such an
apparatus.
Several services to provide medical or pharmaceutical advice are
now available via "1-900" telephone numbers, e.g., "Doctors
by Phone." These services are available 24 hours a day and
7 days a week. A group of doctors, including some specialties, is
available to answer questions about health care or medical conditions
for people anywhere in the United States who call the "1-900"
telephone of one of the services. A group of registered pharmacists
answers questions about medications for the "1-900" pharmaceutical
service.
SUMMARY OF THE INVENTION
The present solution to the health care problem is a computerized
medical diagnostic and treatment advice (MDATA) system that is a
medical knowledge-based system designed to give medical advice to
the general public over the telephone network. The goal of the MDATA
system is to provide everyone with equal access to high quality,
100%-consistent medical advice at a reasonable cost. The MDATA system
provides callers with extremely fast and virtually unlimited access
to health care information, twenty-four hours a day, from any location
around the world. Health care advice is made available to an entire
spectrum of users, from elderly patients confined to their homes
to travelers in a foreign country with telephones in their cars.
The central ideas leading to the development of the MDATA system
are based on the following assumptions: Nearly 90% of all patient
complaints are confined to approximately 100 medical problems. Almost
all primary care decisions involved in these 100 problems can be
made based upon information learned solely by obtaining a detailed
medical history. The results of the physical examination, laboratory,
and imaging studies only tend to confirm a diagnosis. The minimal
amount of information that many doctors believe can only be obtained
from the physical examination can actually be directly acquired
from the patient when given appropriate instructions. In most cases,
a face-to-face interaction between the doctor and patient is not
necessary. A detailed and well-constructed history, along with physical
findings elicited from the patient, can be obtained over the telephone.
Medicine is basically diagnosis and treatment. Although treatment
recommendations change frequently, the fundamental principles of
making the diagnosis do not. There is a significant delay between
the time a new therapy is recognized as safe and effective and the
time physicians are able to provide it to their patients. These
central ideas are utilized in the implementation of the MDATA system.
A goal of the MDATA system is to give better medical advice than
a family practitioner who is unfamiliar with a patient, e.g., an
on-call physician. A person seeking medical advice frequently will
not be able to see or speak with his or her personal physician in
a timely manner. The MDATA system provides medical advice whenever
desired by the caller--seven days a week/24 hours a day.
All previous medical algorithms, including those used in the military,
are designed for face-to-face interactions. Self-help books generally
do not consider age and sex in their algorithms. Furthermore, a
book cannot take into account how many times a person has consulted
the same algorithm within a short period of time for the same problem.
The medical algorithms used by the MDATA system are designed for
use in a telecommunications setting and overcome the deficiencies
of self-help books.
Previous medical advice systems do not do a time-density analysis
for a number of factors with regard to the number of complaints
per unit of time. The MDATA system uses "meta" functions
to perform these analyses.
Previous medical advice algorithms do not have a way of detecting
the consciousness level of the person seeking consultation. The
MDATA system invokes a "mental status examination" whenever
a complaint or problem has the possibility of an altered level of
consciousness. In addition, the MDATA system uses "semantic
discrepancy evaluator loops" which allow the system to invoke
the mental status exam if there are differences in answers to the
parallel threads of thought that are woven or embedded into the
system.
Other medical advice systems do not have a "re-enter"
feature to monitor a patient's progress or worsening over time.
The MDATA system checks for and responds to changing conditions
over time.
Prior medical advice systems suffer from the inability to be nearly
instantly up-dated as new medical information is made available.
The MDATA system regularly and frequently updates the treatment
aspect of the system.
The computerized medical diagnostic and treatment advice (MDATA)
system is a medical knowledge-based system designed to give medical
advice to the general public over the telephone network. Using a
new authoring language, interactive voice response and speech recognition
technology, the MDATA system encodes a highly useful core of expert
and general practitioner diagnostic and treatment knowledge into
a computerized system for access by non-medically trained personnel.
The MDATA system does not provide advice for every medical problem,
nor does it make an exhaustive study of one vertical cross-section
of medicine. Instead, the MDATA system provides up-to-date medical
advice for approximately one hundred of the most commonly encountered
problems in general practice and emergency medicine. It also provides
valuable information to the public on any number of other medical
topics.
As another embodiment of the MDATA system, a person desiring medical
advice and having access to a personal computer (PC) loads a program
into the PC to produce a stand-alone medical diagnostic and treatment
advice (SA-MDATA) system. Rather than listening to questions and
responding via touch tone keypresses or via voice, the user responds
to questions and directions displayed on the computer screen via
a computer input device, such as a keyboard or mouse. The diagnosis
and/or treatment recommendations provided by the MDATA system are
the same as that provided by the SA-MDATA system. The user of the
SA-MDATA system can procure updates by contacting the MDATA system
sponsor/administrator to obtain the most current treatment table
information for a particular diagnosis.
In one aspect of the present invention there is a computerized
system for use in medical diagnosis, the system comprising a data
structure configured to be accessed by a plurality of attributes
representative of a medical condition of a patient and providing
one or more selected medical diagnoses for the patient, wherein
a first attribute corresponds to a cause of disease and a second
attribute corresponds to an anatomic system of the patient affected
by the medical condition, wherein the provided data is identified
as being located within the data structure based on the plurality
of attributes, and wherein the data structure is stored in a memory.
In another aspect of the present invention there is a computerized
method used in medical diagnosis, the method comprising ascertaining
a plurality of attributes representative of a medical condition
of a patient; accessing a data structure based on the plurality
of attributes; and identifying one or more selected medical diagnoses
associated with a diagnosis of the patient based on the accessing.
In yet another aspect of the present invention there is a computer
usable medium having computer readable program code embodied therein
for performing a computerized process used in medical diagnosis,
the computer readable code comprising instructions for ascertaining
a plurality of attributes representative of a medical condition
of a patient, accessing a data structure based on the plurality
of attributes, and identifying one or more selected medical diagnoses
associated with a diagnosis of the patient based on the accessing.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram illustrating the components of a presently
preferred embodiment of the computerized medical diagnostic and
treatment advice (MDATA) system of the present invention;
FIG. 2 is a diagram of the off-line process used in producing the
speech files shown in FIG. 1;
FIG. 3 is a diagram of the Node Translation process used in creating
files for use by the system of FIG. 1;
FIG. 4 is a diagram of some of the files and components of FIGS.
1 and 3 that are utilized at run time;
FIG. 5a is a diagram of the utilization of the files shown in FIG.
3 at run time;
FIGS. 5b 5g are an exemplary sequence of data structures of the
system shown in FIG. 1 at run time;
FIG. 6 is a block diagram illustrating a conceptual view of the
database files and processes of the system of FIG. 1;
FIGS. 7a, 7b, 7c and 7d are a top-level flow diagram of the MDATA
system of FIG. 1;
FIGS. 8a and 8b are a flow diagram of the patient login process
250 defined in FIG. 7a;
FIGS. 9a and 9b are a flow diagram of the patient registration
process 252 defined in FIG. 7a;
FIGS. 10a and 10b are a flow diagram of the evaluation process
254 defined in FIG. 7d;
FIGS. 11a and 11b are a flow diagram of the meta function 500 defined
in FIG. 10b;
FIGS. 12a and 12b are a flow diagram of the assistant login process
272 defined in FIG. 7b;
FIGS. 13a and 13b are a flow diagram of the assisted patient login
process 276 defined in FIG. 7b;
FIGS. 14a and 14b are a flow diagram of the assistant registration
process 274 defined in FIG. 7b;
FIGS. 15a and 15b are a flow diagram of the assisted patient registration
process 278 defined in FIG. 7b;
FIGS. 16a and 16b are a flow diagram of the mental status examination
function 508 defined in FIG. 10b;
FIG. 17 is a flow diagram of the semantic discrepancy evaluator
routine (SDER) 510 defined in FIG. 10b;
FIG. 18 is a flow diagram of the past medical history routine 512
defined in FIG. 10b;
FIG. 19 is a flow diagram of the physical self examination function
514 defined in FIG. 10b;
FIG. 20 is a flow diagram of the patient medical condition routine
516 defined in FIG. 10b;
FIG. 21 is a flow diagram of the symptom severity analysis function
518 defined in FIG. 10b;
FIG. 22 is a flow diagram of the treatment table process 256 defined
in FIG. 7d;
FIG. 23 is a flow diagram of the menu-driven treatment selection
process 864 defined in FIG. 22;
FIG. 24 is Table 3, a two dimensional array of causes of diseases
plotted against anatomical systems;
FIG. 25 is Table 4, an exemplary plot of symptom severity versus
time;
FIG. 26 is Table 5, another exemplary plot of symptom severity
versus time; and
FIG. 27 is Table 9, a plot of sensitivity and selectivity versus
time.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
The following detailed description of the preferred embodiments
presents a description of certain specific embodiments to assist
in understanding the claims. However, the present invention can
be embodied in a multitude of different ways as defined and covered
by the claims.
For convenience, the following description will be outlined into
the following 22 principal sections: Introduction, System Overview,
Operating Features of the MDATA System, Authoring Language, Run-Time
Operation, Software Structure, Top-Level Flow, Login Process, Registration
Process, Evaluation Process, The Meta Function, Mental Status Examination,
Semantic Discrepancy Evaluator Routine, Past Medical History Routine,
Physical Self Examination, Symptom Severity Analysis, Treatment
Table, The MDATA System Paradigm, Video Imaging, Benefits of the
MDATA System, Optional System Configuration, and Summary of Advantages
of the Present Invention.
I. Introduction
A consultation for a person seeking medical advice begins with
a telephone call to the medical diagnostic and treatment advice
(MDATA) system of the present invention. The MDATA system asks the
caller specific questions and then analyzes each response.
Voice recognition and interactive voice response technology allow
callers to respond to yes/no and multiple choice questions either
by speaking directly into the telephone or by using the touch tone
pad of their telephone.
Easy access to the information in the MDATA system is made possible
by a natural user interface. The computer-driven dialogue consists
of simple yes/no and multiple choice questions. The questions and
treatment recommendations are very simply worded yet skillfully
designed to reflect the accumulated experience of many physicians
in conducting patient interviews.
Although all the MDATA system's questions are designed to be easily
understood, unforeseen situations will inevitably arise. For this
reason, hierarchical staffing is implemented. As an example, for
every 10 telephone lines, one operator fully trained in triage and
the MDATA system will be available. For every 10 operators there
will be one registered nurse in attendance; and for every 10 registered
nurses, there will be one physician in attendance. Staffing requirements
are adjusted as the system is refined toward optimal efficiency.
The MDATA system does not require the operator or the registered
nurse to make any medical decisions.
II. System Overview
Referring to FIG. 1, the components of a presently preferred embodiment
of the computerized medical diagnostic and treatment advice (MDATA)
system 100 of the present invention are shown. A personal computer
(PC) 102 includes a plurality of components within an enclosure
104. A plurality of telephone lines 106 interface the public telephone
network 108 to the computer 102. As an example, one of telephone
lines 106 is shown to be switched via network 108 to connect with
a telephone 110 that is used by a person desiring medical advice
(user) 112. Throughout this document, the words user, caller and
patient are used interchangeably. However, it will be understood
that the caller may be acting as a proxy for the patient. If this
is the case, the caller will be registered as an assistant for the
patient.
The hardware and system software were assembled with two basic
concepts in mind: portability to other operating systems and the
use of industry standard components. In this way, the system can
be more flexible and will allow free market competition to continuously
improve the product, while, at the same time, decrease costs. While
specific hardware and software will be referenced, it will be understood
that a panoply of different components could be used in the present
system.
The system currently runs on the PC 102 with an Intel 80486 microprocessor.
"Telephony" functions use Dialogic Corporation's D/41D
voice processing board 122 based on a digital signal processor (DSP).
The voice processing (VP) board 122 performs several functions including
interfacing the telephone lines, decoding touch tone signals, speech
recording and speech playback. Touch tone signals are also known
as "dual tone multiple frequency" (DTMF) signals. A group
of one to four telephone lines 106 connect to the VP board 122.
The computer 102 may include a plurality of VP boards 122 based
on how many phone line connections are desired for the system 100.
Speech recognition is achieved using Voice Processing Corporation's
speech recognition VPRO-4 board 124 (also DSP based). The voice
recognition (VR) board 124 performs several functions including
recognizing utterances and returning an index number of a recognition
confidence level. The VR board 124 and the VP board 122 both connect
to an industry standard architecture (ISA) bus 126. The ISA bus
126 interconnects the microprocessor 120 with a plurality of peripherals
through controller circuits (chips or boards).
The VP board 122 also connects to a VPRO-Adapt board 128 via an
analog audio bus 130 that is called Analog Extension Bus. Four simultaneous
channels provide a 96 kbit/second data transfer rate. Each channel
corresponds to a telephone line connected to the VP board 122 and
is associated with a current patient consultation. The Adapt board
128 further connects to a digital audio bus 132. The VR board 124
also connects to the digital audio bus 132. The Adapt board 128
performs analog to digital signal conversion to a VPC-proprietary
digital pulse code modulation (PCM) format. The digital bus 132
can accommodate 32 channels and has a data transfer rate of 2.048
Mbits/second.
The computer ISA bus 126 has a plurality of peripherals connected
to it through adapters or controllers. A video adapter board 136,
preferably at VGA or better resolution, interconnects to a video
monitor 138. A serial communication circuit 140 interfaces a pointing
device, such as a mouse 142. A parallel communication circuit may
be used in place of circuit 140 in another embodiment. A keyboard
controller circuit 144 interfaces a keyboard 146. A small computer
systems interface (SCSI) adapter, such as model 1542C made by Adaptec,
provides a SCSI bus 150 to which a 500 Mb or greater hard disk drive
152 and dual Bernoulli 150 Mb disk drives are preferably attached.
The hard drive 152 stores database files such as the patient files,
speech files, and binary support files.
A main memory 156 connects to the microprocessor 120. In the presently
preferred embodiment, the MDATA system 100 operates under DOS version
5.0 operating system 158. The system software is written in Microsoft
C\C++ version 7.0 using structured programming techniques. An algorithm
processor 160 includes a parser and supporting functions that manipulate
a memory variable symbol table and a run time stack, which will
be described hereinbelow. Sequiter Software Inc. Codebase 5.0 allows
access to X-base compatible database records stored on the hard
drive 152. The MDATA system 100 also includes two new authoring
languages (one each is used in two embodiments of the system), which
will be discussed hereinbelow.
The system software includes the following code modules: A. main.c--a
collection of functions that mostly deal with telephony functions,
such as answering the phone line, speech file playback, and DTMF
tone collection. Global data structures are defined here. B. base.c--functions
that invoke the CodeBase revision 5.0 library to perform xbase file
manipulation. C. pars.c--the parse function, and supporting functions
that manipulate the memory variable symbol table and run time stack.
D. regi.c--an on-line patient registration module. E. resp.c--gets
the caller's responses, either DTMF or voice, and figures out what
to do next by obeying a command (e.g., "repeat" or "backup"),
or traversing through the algorithm node map. F. term.c--a useful
collection of text phrases for Dialogic and VPC board termination
events and error codes. G. user.c--"non-diagnostic" portions
of the caller session: initial screening questions, caller login,
and the next node playback initiator. H. util.c--a collection of
general purpose functions shared by a run time executable, a node
editor and ASCII translator tools. I. view.c--a module that controls
the graphics system display. J. x10.c--an X-10 computer interface
routine for fault recovery. K. xlat.c--a module linked with pars.c
and util.c object modules to build xlat.exe, a stand-alone translation
executable for offline ASCII text file translation. The application
is compiled with the Microsoft graphics, Dialogic board, VPC board
and CodeBase database libraries.
The Voice Processing Corporation (VPC) VPro-4 VR board has eight
voice recognition channels, which by default are associated one-to-one
with the Dialogic D/41D channels. VPC's pioneering work in the voice
processing field is in the area of continuous speech. This allows
a person to speak a multiple digit number in a natural manner, without
pausing after each digit. VPC supplies two continuous speech vocabularies:
one vocabulary contains the digits 1 through 9, plus "zero"
and "oh", and the other contains just the two words "yes"
and "no". The vendor-supplied digits continuous speech
vocabulary is used by the system 100. In the presently preferred
embodiment, if the score is 75% or better, the response is unconditionally
accepted. If the score is between 20% and 74%, the digits recognized
are read back, and the caller is asked to accept or reject the digits.
In another embodiment of the system 100, the above score thresholds
are implemented as tunable parameters. The scoring parameters are
stored in a configuration file that is manipulated off-line by a
utility program and is read by the run-time system at initialization.
VPC also provides a few discrete vocabularies. Discrete vocabularies
contain one or two word utterances. The vendor-supplied discrete
speech vocabulary of the months of the year is used in the on-line
patient registration process. A speaker-independent discrete speech
vocabulary consisting of the words "yes", "no",
"backup", "continue", "help", "operator",
"pause", "quit" and "repeat" has been
developed using a very powerful set of utilities supplied by VPC,
Scripter and Trainer. These utilities are for collecting samples
and training the vocabulary.
The VR board 124 has the minimum of two MB memory installed. The
default memory configuration has a partition for both continuous
vocabularies and a partition for one discrete vocabulary. Additional
discrete vocabularies may be downloaded if the on-board memory is
reconfigured.
The VR board 124 has four digital signal processors (DSP's) from
which VPC derived eight voice recognition channels. Each of these
eight recognition resources is referred to as a VPro Speech Processor
(VSP). Discrete vocabulary recognition requires one VSP; continuous
vocabulary recognition requires two adjacent VSP's. The MDATA system
100 has a VSP resource manager in the resp.c software module. This
resource manager allocates VSP's in a dynamic manner to VP board
122 channels on a demand basis. As soon as the system receives a
response, voice or DTMF, it releases the VSP's associated with the
caller's VP board 122 channel.
The MDATA system 100 uses VPC's application programming interface
(API) for the C programming language. This makes the application
vendor specific to VPC, but also allows the system 100 to utilize
all the powerful API features, e.g., on-line creation of discrete
speaker dependent vocabularies used for voice pattern matching or
voice printing.
The VPC API supports both continuous speech vocabulary (CSV) and
discrete speech vocabulary (DSV) recognition.
The voice processing (VP) board 122 supports speech recording and
playback, as well as touch tone (DTMF) signal detection and decoding.
A device driver, associated with the VP board 122, is loaded into
system memory during load operations. The device driver supports
communications between the VP board 122 and the application code
at run time (e.g., when a person is seeking medical advice). Through
a shared memory segment, the device driver sends event and status
data to the application code in real-time as events occur on the
associated telephone line. These events include the ring of an incoming
call, touch tone key pressed by the caller, and the hang-up signal.
The VP board 122 plays back speech messages that are stored on the
hard drive 152. The algorithm processor 160 sends a selected speech
file having an encoded speech message that is retrieved from the
hard drive 152 to the VP board 122 at the appropriate time for speech
message playback. A speech message can be of variable length with
a typical message about one to two minutes in length. Several speech
messages may be chained together to produce an extended spoken message,
e.g., giving instructions to the patient. During speech file playback,
the VP board 122 is monitoring touch tone response from the caller.
The VP board 122 may be configured to interrupt speech file playback
when a touch tone signal is detected.
System Operating Contexts
The system has an activity flag in the port status block for each
patient currently using the system to keep track of which state
the associated VP board channel is in: a. Idle Mode--an idle channel
waiting for a telephone call; b. Login Mode--a condition where a
patient is in the login process; c. Registration Mode--a condition
where a patient is in the registration process; d. Real Mode--a
condition where a patient is consulting for an actual medical problem;
e. Info (Information) Mode--a condition where a patient is consulting
for information or a hypothetical situation; f. Pause Mode--a patient-initiated
pause condition; g. Pending Mode--similar to Real mode except that
new medical information gathered for a patient is not automatically
added to the patient's medical record, but rather written to a "Pending"
file where it will be verified off-line by a staff person.
Voice Keywords and DTMF Command Keys
The system is responsive to the following voice keywords and DTMF
keys when it is in a prompting state, i.e., not in response to a
menu message:
TABLE-US-00001 Voice DTMF yes 1 Useful for answering yes/no ques-
tions. no 2 backup # Causes the system to back up to the "predecessor"
message (see below), then resume playback help * Plays helpful information:
either the node's help message list, or the DTMF command explanation
mes- sage. operator 0 Causes the system to transfer the caller to
a live person. pause 7 Transitions to pause mode. The sys- tem default
pause period is 30 seconds. quit 9 Quits the current algorithm,
and takes the caller to node 110, which asks the caller if (s)he
wishes to select another algorithm. repeat 3 Repeats the current
node's play mes- sage list. If this command is given in the middle
of a long play list, then playback restarts with the first mes-
sage in the list. Pause Mode Commands yes 1 Extends the pause period
by one de- fault pause interval (30 seconds). continue 2 Ends pause
mode. If this occurs at a Yes/No node, the system will repeat the
question. If this occurs at a Link node, the system will resume
play- back with the "current" message. The system resolves
the DTMF digit "2" ambiguity, "no" versus "continue",
by examining the pause mode flag.
FIG. 2 illustrates how speech files are created. A person programming
medical algorithms uses speech messages to communicate with the
person seeking medical advice. As previously mentioned, these speech
messages are of variable length. The programmer typically writes
a script for the speech message. Then using the handset of the telephone
110, a speakerphone feature, or other voice-input device, e.g.,
a microphone, the programmer reads the script into the voice-input
device which is connected to the VP board 122. The VP board converts
the speech into a digital format and records the digitized speech
to a file that is stored on the hard drive 152. In the presently
preferred embodiment, a subdirectory named vox contains the system
speech files, and subdirectories for each medical algorithm. System
speech files are of the form sysxxx, where xxx is some arbitrarily
assigned number. The system messages are used by the "fixed"
parts of the system, e.g., greeting, login process, registration
process. There are a few speech files of the form msgxxx. These
are the past medical history questionnaire messages, and response
acknowledgements. There are additional speech files of the form
msgxxxx in each of algorithm subdirectories, where xxxx generally
matches the node number, which will be explained hereinbelow. Node
messages include information, question, menu and help messages.
III. Operating Features of the MDATA System
One of the MDATA system's main objectives is to bring together
highly-qualified medical experts, encode their knowledge in a central
location, and make it available to everyone. A new and unique authoring
language is used by the MDATA system to help accomplish this objective.
Each day, specialists perform the same tasks over and over. They
enact the same diagnostic ritual of solving a familiar problem.
At the same time, however, primary care physicians attempt to find
the best path through the diagnostic maze of an unfamiliar problem.
This process is inefficient and fraught with error.
In medicine, there is generally one best way to do things. Instead
of physicians spending valuable time duplicating tasks, the MDATA
system utilizes medical experts from each medical specialty who
write detailed algorithms for the treatment of the 100 or so most
commonly encountered complaints in family practice and emergency
medicine. These algorithms are carefully and specifically designed
to elicit historical data and physical findings over the telephone,
rather than in face-to-face interactions.
Several experts could work together to thoroughly research one
particular complaint as well as to anticipate the full spectrum
of possible problems and patient responses. These experts could
also provide and maintain the MDATA system treatment table as well
as the imaging modality of choice and laboratory test of choice
tables. These concepts will be described hereinbelow.
Carefully crafted questions, used in the taking of a medical history,
are the main tools that the MDATA system uses to assess the problems
of patients. The key to getting a good history is to ask the right
questions. In a sense, in the diagnostic process questions are like
tests. It is important to note that the right questions are basically
always right; they don't change. Although they may be refined over
time, in general, once excellent and well-crafted questions are
developed they are good for a very long time. Of course, as new
diseases are discovered, e.g., toxic shock syndrome and AIDS, new
sets of diagnostic questions are developed that are disease specific.
The questions used by an earlier generation of physicians, who
did not have any of the latest imaging modalities (types or methods),
are far more sensitive and precise in diagnosing a patient's problem
than the questions used by doctors today. The MDATA system makes
use of fine nuances of language to diagnose patients as well as
to determine when certain tests or imaging studies are necessary.
The MDATA system's statistic generating capabilities enable the
system to analyze the effectiveness of the questions used in the
diagnostic process. As a result, physicians benefit from the immense
amount of statistical information that is gathered regarding the
wording of questions asked in taking medical histories. For example,
exactly what percentage of patients who answer "yes" to
the question, "Is this the worst headache of your life?"
actually have a subarachnoid hemorrhage? Although this is a classic
description of this problem, the exact probability of having this
kind of brain hemorrhage after answering "yes" to this
question is not presently known.
Currently, doctors can only estimate the probability of certain
conditions based on history. By applying the statistical information
that is generated, the MDATA system not only provides the patient
with advice that is continually improving, but it will also be able
to pass along these probabilities to the entire medical community.
To function optimally, the MDATA system tries to gain as much medical
information about its patients as possible. Although a first-time
caller is given excellent advice, more specific advice can be given
if the system has more information. Therefore, the MDATA system
asks patients for their complete medical history. The MDATA system
can either obtain the patient's medical record over the telephone
or it can mail or fax a detailed questionnaire to each patient.
The patient can then gather the necessary information at their convenience.
The MDATA system will always be available by telephone to clarify
any questions the patient may have.
The MDATA system uses the "International Classification of
Diseases" (ICD-9-CM) codes to help summarize the information
it has about a patient. This world standard is a comprehensive numerical
system used to classify the entire spectrum of medical diseases.
ICD-9-CM codes are also used to classify specific procedures performed
(e.g., appendectomy) as well as the morphology of neoplasm (i.e.,
tissue diagnosis of a cancer).
In addition, the MDATA system 100 uses ICD-9-CM "E-Codes"
to classify environmental events, circumstances, and conditions
as the cause of injury, poisoning, and other adverse effects. These
codes are particularly helpful for storing information about what
drugs the patient has taken or is currently taking, as well as the
context (e.g., therapeutic use, accident, poisoning, suicide attempt)
in which they were or are being taken. For example, E942.1 is the
code for the therapeutic use of digoxin. Medications are also cross-categorized
according to the classification done by the American Hospital Formulary
Service List (AHFS) Numbers. The MDATA system 100 also uses "V-Codes"
to classify other types of circumstances or events such as vaccinations,
potential health hazards related to personal and family history,
and exposure to toxic chemicals.
It is estimated that the alphanumeric component of a patient's
medical history will not exceed 1,000 atoms or pieces of information.
An atom is considered herein to be a separate identifiable data
item or point. With this assumption, the medical records of every
person on the planet could currently be stored on approximately
1,000 optical disks.
While a patient interacts with the MDATA system, the system is
constantly determining what questions to ask, based upon the information
it has about the patient. Just as a physician gathers relevant pieces
of information from his or her dialogue with a patient, the MDATA
system flags and later stores all pertinent pieces of information
that it learns from each interaction with its patient. Therefore,
certain questions, because their answers remain the same, need not
be repeated. For example, if the MDATA system learns that a patient's
mother has suffered from migraine headaches, it will never have
to ask for this information again.
Again, the more information the MDATA system has about a patient,
the more specific is its advice. It is not uncommon for the MDATA
system to give different advice to different patients calling for
the same complaint. In other words, the advice given is patient-specific.
Not only can the MDATA system's advice be different for different
patients, but there are times when the advice given to the same
patient (calling for the same complaint but at different times)
is different. For example, one of a group of functions called "meta"
keeps track of the number of times the MDATA system has been consulted
for the same problem. Once a threshold is reached, the MDATA system
advises the patient that the number of consultations alone, for
the same complaint, may signify a problem. The system then makes
an appropriate recommendation.
Before the MDATA system stores any information, the system verifies
its accuracy. To accomplish this task, "confirmation loops"
are used. Any piece of information that will become a part of the
patient's medical record is sent through a confirmation loop where
the system asks the patient to verify the accuracy of the information
that the system has collected. The confirmation loop enables the
system to verify new patient information and make corrections before
it enters this information into the patient's medical record.
IV. Authoring Language
The MDATA system uses a new authoring language that is specifically
designed to allow medical knowledge to be encoded into a usable
computer program. The presently preferred voice response or telephony
version of the MDATA system is written in object-oriented Microsoft
C\C++ version 7.0. This allows the MDATA system to easily interface
with industry-standard database programs, including those that are
SQL-based, as well as to be portable to other operating systems.
The operating system is transparent to the user.
Before the development of the MDATA system's authoring language,
there was no practical way for medical experts to encode their knowledge
into a meaningful, useful, and accessible structure. Although other
computer languages have been used to build medical expert systems,
they have almost always required a knowledge engineer and a programmer
to be involved. Quite often, the knowledge encoded in these systems
could only be accessed and fully understood by physicians. Typically,
the programmer would try to translate the doctor's diagnostic skills
and treatment rules into computer code. This separation of the physician's
knowledge from the encoded treatment recommendations often engendered
anxiety in the physician and has, at times, led to inaccurate treatment
recommendations.
The MDATA system's authoring language, however, is designed to
allow physicians to transfer their knowledge into a computer program
that can be directly accessed by non-medically trained personnel.
Recursive and iterative techniques are used to acquire the knowledge
from the expert and assemble it in a way that allows it to be immediately
transposed into the MDATA system's algorithms. Because of the simple
interface of the language, and because a formula for writing the
algorithms has already been developed, physicians who are not computer
literate can encode their knowledge as well as understand exactly
how that process takes place.
The MDATA system's authoring language allows flat information to
be restructured into a hierarchical or layered format in which the
arrangement of the knowledge conveys meaning. Thus, a textbook description
of a disease can be transposed into a form that allows useful treatment
recommendations to be made.
The new language also allows the formation of a structure in which
multiple overlays of screening questions, combined with the application
of recursive techniques, sequentially exclude some diagnoses while
at the same time reaching treatment recommendations. The MDATA system's
simplicity and elegance would not be possible without the new language.
The MDATA system's authoring language allows an algorithm programmer
to retrieve information from a patient's medical record, request
additional information from the patient, and guide the flow of algorithm
execution based on medical history and the patient's responses.
The language allows the programmer to implement an algorithm in
a natural scripted style.
The course of an algorithm is determined by caller responses to
questions that the MDATA system asks. For simple "yes/no"
questions, the flow of interaction can be described by a binary
tree. Multiple-choice questions (e.g., menus) provide multiple branches
in the tree. Each question can be considered a node, and the acceptable
responses to this question are branches leading to the next question
(node). Using this abstraction of an algorithm, one can draw a directed
graph (also known as a node map) of the nodes and branches of an
algorithm, beginning with the initial question, and ending with
all possible terminal points.
The node table is built in this manner: 1. An author develops an
algorithm. 2. The algorithm is broken up into separate nodes. 3.
A directed graph is drawn up, which is a flow chart of the algorithm's
operation. 4. Each node's definition is entered into the MDATA system,
either by: a. using an ednode utility to write each node's definition
into the system's machine readable node table, or b. using an xlat
utility to translate an ASCII file of human-readable node definitions
into the system's machine readable node table.
Referring to FIG. 3, a process for translating a medical algorithm
written in the authoring language will be described. FIG. 3 illustrates
an ASCII (American Standard Code for Information Interchange) format
text file 170 as an input to a translation utility 172. An ASCII
file can be created by use of a text editor or a word processing
program (may need to export to the ASCII format). The ASCII file
170 contains node definitions conforming to the syntax briefly described
hereinbelow.
The purpose of the ASCII node definition translator utility 172
(xlat.exe, along with functions in pars.c and util.c) is to convert
a human-readable document into a machine readable format that the
MDATA system reads at run time to process an algorithm. This utility
172 may be considered to be a preprocessor; the translation must
be accomplished prior to run time.
The output of the utility 172 is a set of binary (NOD_BLK) records
written to a node table 174 (filename of node.fos), and a set of
binary list files 176 (in a subdirectory \list\listxx \xxyy, where
xx is the first two digits of the node number, and yy are the last
two digits). Four list files 176a 176d are shown as an example.
Each "list" file, e.g., 176a, contains a "next"
table (i.e., the `next node after this one`), a message play list
for this node, and a "work" list (i.e., one or more "things
to do" at this node before beginning speech playback). The
binary record written to the node table 174 (node.fos) has fields
containing the node number (which is redundant; the record's position
in this file also indicates the node number), the node's "type"
attribute (Menu, Link, Prompt, Yes/No, Return, Hangup) and a parent
node number.
The node table 174 is a table of 10,000 NOD_BLK records. This table
174 is indexed by a node number, e.g., the fiftieth record corresponds
to node 50. The contents of the individual node records may be viewed
by selecting "Display Node" while running the ednode utility.
The node records are modified by either using the ednode utility,
or when translating node definitions from ASCII to the node file
with the xlat utility.
One of the following keywords is necessary as the first item on
each line, but only one keyword is accepted per line; any excess
information will be discarded.
TABLE-US-00002 Node The Node keyword denotes the beginning of a
new node and defines the node number. Parent The Parent keyword
defines the parent of the node being de- fined. Type The Type keyword
defines the class of the node being defined. Acceptable type names
are: Menu This node presents a multiple choice question. YesNo This
node presents a simple Yes/No type question. Link No caller response
is required at this node, algorithm processing will continue at
a predetermined node. Prompt This node requests some numeric information
from the caller. The information is placed in a DTMF buffer which
is then stored in the next node. Return Returns from a subroutine
call (e.g., after config- uring a past medical history object).
Hangup The system will release this caller after it finishes speech
file playback, or if the caller interrupts play- back with a DTMF
key press. Wait nn This node will play the message list, then pause
for the specified nonzero number of seconds before con- tinuing.
@ The @ keyword defines the action to be taken for a response to
either a Menu or YesNo type node. Digits The Digits keyword is used
in conjunction with Type Prompt to indicate the maximum number of
DTMF digits to collect from the caller. Play The Play keyword defines
a play list of one or more messages to be played at this node. Help
The Help keyword defines a play list of one or more messages containing
useful hints for interacting with the system. These messages provide
helpful instructions for a new or con- fused caller. Next The Next
keyword defines the next node to jump to after the node being defined.
It is used in conjunction with node types Link and Prompt. Work
The Work keyword indicates a sequence of one or more opera- tions
to perform when arriving at the node being defined. This processing
occurs before speech playback begins.
A select set of math functions, relational operators, and nested
if-then-else statements are supported. A pound sign (`#`) or a hyphen
(`-`) in the first position on a new line will cause the translator
to skip over the rest of the line. This is useful for inserting
comments, or delimiting between individual node definitions. The
translator also disregards blank lines.
In order for a node to be properly defined, a minimum number of
keywords must be present for each node, and other keywords must
be included depending on the node type. The minimum keyword set
for a properly defined node is:
Node, Parent, Type, and Play. Dependency Rules: (1) The Menu type
requires at least an @1 line and an @2 line. (2) The YesNo type
requires an @1 and an @2 line (@3, etc. are ignored). (3) The Link
type requires a Next line. (4) The Prompt type requires a Digits
line and a Next line.
The first keyword in a node definition must be Node. The other
keywords may be given in any order. The next occurrence of the Node
keyword will invoke a completeness test. If the completeness test
is successful, then the node definition is saved in machine readable
(binary) format, and translation continues with the new Node line.
A set of reserved language keywords is listed in Table 1.
TABLE-US-00003 TABLE 1 Reserved language keywords (case insensitive):
@ link return and menu test digbuf meta then digits next type else
node wait essf parent write flush play work hangup pop xor help
prompt yesno if push keep reenter
V. Run-Time Operation
Referring to FIG. 4, the run time interaction among the hardware
and software components of the MDATA system 100 will be described.
As previously mentioned, algorithm processor 160 includes the parser
and supporting functions that manipulate the memory variable symbol
table and the run time stack. For a selected medical algorithm,
a node record is read from the node table 174 and a list file is
read from the plurality of list files 176. The algorithm processor
also interacts with the Vpro voice recognition (VR) board 124 for
speech recognition and with the Dialogic voice processing (VP) board
122 for speech playback and DTMF detection. The VP board 122 further
is interconnected with a set of speech files 180 that are stored
on a portion of hard disk 152 and with one of the telephone lines
106 that connects via the telephone network 108 (FIG. 1) to the
patient's telephone 110. The VR board 124 further connects with
the voice print vocabularies 182, previously described, also stored
on a portion of hard disk 152. The algorithm processor 160 utilizes
the speech recognition, speech playback, and DTMF detection resources
as directed by the medical algorithm that is retrieved from the
node table 174 and the list files 176.
Referring to FIGS. 4, 5a and 5b, several data structures are utilized
at run time. These data structures are described as follows: A.
Port Status Block (PSB). A port status block is created at run time
for each VP board 122 channel. The PSB contains flags, buffers and
tables that hold the state information of the channel, retain responses
from the caller, and keep track of where to transfer control in
response to voice recognition and telephony events. The PSB keeps
track of whether the caller prefers to use spoken or touch tone
responses, the caller's last response, the number of consecutive
errors the caller has made, and other context sensitive parameters.
B. Node Block. This structure 196 contains the node number, the
type attribute (link, menu, yes/no, hangup, prompt, wait, return)
and pointers to: a. Help list--a Play list of help information;
b. Play or Message list--a list of one or more messages or speech
files to play in sequence at each node; c. Next table or list--contains
entries for each possible response to a yes/no or menu node that
are evaluated at run time to determine the next node to branch to;
and d. Work list--things to do before message playback starts. The
load_node( ) routine 194 in util.c builds the node block structure
196 in memory by first reading in a node record 190 from the node
table 174. Then linked lists are attached to the pointers help,
play, next and work. These lists come from the list files 176, in
subdirectory path \list\listxx \xxyy, where xxyy is the node number,
wherein each list file 192 is associated with a unique node. C.
Symbol Table. Each patient has their own associated symbol table.
A portion of a symbol table 212 is shown in FIG. 5b. The symbol
table is loaded at run time with memory variables that hold patient
specific data (age, sex, and items from medical history) and algorithm
specific data. The items in the symbol table can be flagged for
storage to the patient's medical history. D. Run Time Stack (RTS).
Each Dialogic VP board 122 channel has a RTS associated with it.
The RTS is used by the parser. The algorithm programmer can push
to and pop from the RTS, e.g., to temporarily store a value of a
variable.
The work list has the non-playback tasks that are performed at
each node. There is one work list for each node, and it is identified
with the work keyword in the ASCII node definition file. The work
list may be empty. Each time the system transits to a new node,
it will execute the work list. If the patient repeats a node, the
system will not execute the work list again; it will simply replay
the message(s). If the patient requests the system 100 to back up
the node map, the system will execute the work list of the node
it backs up to. Typical tasks in the work list involve manipulating
objects on the run time stack or in the symbol table, testing for
the presence of memory variables, configuring past medical history
or current medical condition objects, or writing database records.
An example of a complex work list follows: "Test OBJECT2; Phone=DIGBUF;
Push Age" This example tests for the presence of a patient
record object labeled "OBJECT2", loads the contents of
the digit buffer into memory variable Phone, and pushes the value
of memory variable Age onto the run time stack.
Each node has the "next" table or list. The next list
indices range from 1 to 9, inclusive. The next list contains either
a single node number, or an if expression. For all node types, except
the Hangup node, there will be at least one next list: Link and
Prompt nodes: the next node is stored at table index 1. Yes/No node:
the next node for the Yes response is stored at table index 1, and
the No response is stored at index 2. This corresponds to the prompt,
"if the answer is yes, press 1; if no, press 2." Menu
node: the response number and the table index are the same. Even
though the actual data structure has a `0` index in the C programming
language, this index is not used in the next table because a `0`
response is reserved for operator assistance. Following is an example
of a next list: "If Male and Age>55 then 100 else 200"
is interpreted as: If the patient is both male and over 55 years
old then go to node 100 else go to node 200.
Speech files 180 may be of an arbitrary length. A message may be
informational, a list of menu options, or a yes/no question. A "two
paragraph" or "under one minute" limit has been adopted
as a style convention for the presently preferred embodiment. Typically,
a node is programmed as a sequence of Yes/No nodes, with "informational"
Link nodes interspersed as needed. When there is a lengthy discussion,
the speech is recorded in multiple files. To simplify algorithm
programming and enhance readability (viz., eliminate long chains
of link nodes), the Link node's play list may contain up to ten
message numbers.
Upon arrival at a Link node, the system positions a "current
message" pointer at the beginning of the play list (trivial
case: single message play list; interesting case: multiple message
play list). As playback proceeds, the current message pointer moves
down the play list. After the system plays the last message on the
list, it moves on to the next node.
If the caller issues a "backup" command, the system will
move the current message pointer back one message, and resume playback.
If the pointer was at the beginning of the list (e.g., trivial case),
the system backs up to the previous node and places the current
message pointer at the beginning of the play list. If there is more
than one message in the list, the system cues the pointer to the
last message in the list. The system then resumes playback. In the
"pause" mode, when the caller issues the "continue"
command, the system will resume playback at the current message.
The MDATA system 100 uses three basic operating modes: A. Real
Mode--involves an actual medical problem. In this mode the system
100 loads the past medical history, saves new past medical history
objects, and writes a meta record for each algorithm consulted.
The medical algorithm programmer is responsible for providing code
to jump past meta analysis in Information mode. B. Information Mode--involves
a "what if" scenario. In the Information mode the system
100 disregards past medical history, does not save newly configured
past medical history objects, does not write a meta record for each
algorithm consulted, and does not perform meta analysis. The patient
has an option in Information mode to change the age and sex parameters
to emulate a hypothetical patient. C. Pending Mode--handles the
situation when a patient's voice sample does not match the patient's
reference sample. Pending mode is utilized also when an assistant
is interacting with the MDATA system 100 on behalf of a patient
and both the assistant's and the patient's voice samples fail the
voice printing test. In the case where the assistant's voice sample
fails the voice printing test but the patient's voice sample passes
the test, Pending mode is not utilized. In Pending mode, the MDATA
system 100 considers the patient's medical history and performs
meta analysis during this consultation. However, a meta record is
not written for this consultation and any new medical information
gathered on this patient will not be written to the patient's medical
record. The new medical information is written to a "Pending"
file. The Pending file is verified off-line by a system administrator
or staff person, and then is added to the patient's medical record
only if the information can be verified.
One of the drawbacks of the traditional doctor-patient relationship
is the short amount of time that physicians are able to spend with
patients. The MDATA system 100, however, allows patients as much
time as they wish to learn about their problem as well as to obtain
information on any number of other medical topics.
Through the "Information mode" feature of the MDATA system
100, callers can learn about a disease process, an illness or the
latest treatment for any disease, without adding any information
to their personal medical record. Although the system 100 keeps
track of the interaction, it is labeled as an "Information
mode session." The record of the caller's path through the
system is not used as the basis for any future advice, nor is it
considered in generating system statistics.
The Information mode is not limited to complaints for which the
MDATA system 100 offers medical advice. Information about early
detection and treatment of many other diseases as well as the latest
advances in medicine can be made available through the Information
mode.
Referring to FIGS. 5b through 5g, as an example, a run time sequence
of steps of how a patient may traverse a main menu node map several
steps into a chest pain algorithm node map will be described. Six
nodes with a portion of an associated symbol table will be discussed.
At FIG. 5b, the algorithm processor 160 loads the first node #100,
represented by node block 210. The variables for Age, Sex, and Real
mode were loaded into the symbol table 212 during the login process
(which will be described hereinbelow). Throughout this example,
the help list is empty, i.e., no help information is played for
the patient. The work list sets the Problem variable of the symbol
table 212 to be Menu. Then the system 100 begins playback of message
#100. This message gives the patient a menu of choices to choose
from. The Digits entry equal to one means that a one digit response
is expected from the patient. The patient may respond by pressing
a touch tone (DTMF) key on the telephone or speak the choice response
into the telephone handset microphone. In this example, the patient
selects menu option "1". The parser evaluates the Next
list based on the patient selection and branches to node #101.
At FIG. 5c, the algorithm processor 160 loads node #101, represented
by node block 214. The work list is empty, so the system 100 goes
right to playing back message #101 which presents another menu of
choices to the user. The Next list has four nodes for possible branch
points. In this example, the patient selects menu option "1"
for a chest pain complaint. The parser evaluates the Next list based
on the patient selection and branches to node #2200.
At FIG. 5d, the algorithm processor 160 loads node #2200, represented
by node block 218. The work list command is to update the value
of Problem in symbol table 220 to CCHP (chest pain). Then the system
100 begins playback of message #2200. No response is required from
the patient for a Link type node. The Next list has two nodes for
possible branch points depending on the value of symbol table variable
Real. The parser evaluates the If expression in the Next list for
the value of Real and, in this example, branches to node #2201.
At FIG. 5e, the algorithm processor 160 loads node #2201, represented
by node block 222. The work list command is to write a Meta consultation
record for future use by a Meta function. The play list is empty
so no message is played. No response is required from the patient
for a Link type node. The main purpose of this node is to write
the Meta consultation record (because the system is currently in
Real mode for this patient). The Next list has only one node so
no decisions are necessary by the parser which, in this example,
branches to node #2205.
At FIG. 5f, the algorithm processor 160 loads node #2205, represented
by node block 226. The work list is empty in this node so the system
100 goes right to playing back message #2205 which presents a yes/no
type of question to the user. The Next list has two nodes for possible
branch points depending on the response of the patient. In this
example, the patient responds "no", and the parser evaluates
the Next list based on the patient selection and branches to node
#2210.
At FIG. 5g, the algorithm processor 160 loads node #2210, represented
by node block 230. The work list is empty in this node so the system
100 goes right to playing back message #2210 which presents a yes/no
type of question to the user. The Next list has two nodes for possible
branch points depending on the response of the patient. If the patient
answers "yes" to the question, the parser branches to
node #2211, but if the patient answers "no" to the question,
the parser branches to node #2215.
VI. Software Structure
Referring to FIG. 6, the system utilizes eight principal, separate
processes and seven related databases. A patient login process 250
is used by the system 100 to identify a patient who has previously
registered into the system by prompting for a patient identification
number (PIN). An assistant login process 272 is used by the system
100 to identify an assistant who has previously registered into
the system by prompting for an assistant identification number (AIN).
An assisted patient login process 276 is used by the system 100
to identify a patient who has previously registered into the system
by prompting for the patient identification number. If the caller
is the patient, a patient registration process 252 is used by the
system to register new or first-time patients. If the caller is
not the patient, an assistant registration process 274 is used by
the system to register new or first-time assistants. Then, if the
patient is not already registered, an assisted patient registration
process 278 is used by the system to register the patient. These
processes will be further described hereinbelow.
Once a caller has logged in or registered, the system provides
a choice of two other processes in the current embodiment. The first
of these processes is the evaluation process 254 that performs a
patient diagnosis. The second of these is a treatment table process
256 to obtain current treatment information for a particular disease
or diagnosis. In another embodiment, other choices are added to
access other medical information processes.
Associated with these eight processes are a patient and assistant
enrollment database 260, a consultation history database 262, a
patient response database 264, a medical history objects database
266, a patient medical history database 268, a pending database
269, and a patient medication database 270 that are described as
follows: A. The master patient and assistant enrollment database
260 is created at run-time by one of the registration processes
252, 274, or 278. This database 260 is read by the patient login
process 250 or the assisted patient login process 276 to validate
a patient's identity at login time and by the assistant login process
272 to validate an assistant's identity at login time. The database
260 is essentially a master file of all registered patients and
assistants indexed by their patient ID number or assistant ID number,
respectively. The patient ID or assistant ID, date of birth and
gender fields are entered by the on-line registration process; the
system administrator manually enters the name of the patient or
assistant in an off-line manner. The patient and assistant database
260 contains one record for each patient or assistant. This database
260 is indexed by the identification number. The system appends
the enrollment database 260 after a caller is successfully registered.
The "next ID number" is stored in a binary file, config.fos,
and is incremented after each successful registration. Each record
has the following fields:
TABLE-US-00004 Field Name Data Type Width Usage ID Numeric 10 ID
number TYPE Character 1 User type: "P" - patient, "A"
- assistant ASST_PERM Boolean 1 Permanent assistant flag ASST_EXP
Date 8 Expiration for permanent assistant RELATIONS Pointer 20 Pointers
to related patients/assis- tants ORGZTN Character 8 Organization
alphanumeric code NAME Character 20 Patient/Assistant name SEX Character
1 Gender YEAR Numeric 4 Year of birth MONTH Numeric 2 Month of birth
DAY Numeric 2 Day of birth ACCESS Date 8 Last access RV_PATH Character
20 Path name of recorded voice file
B. The consultation history or meta database 262 is created at
run-time by the evaluation process 254. A consultation record contains
alpha-numeric codes for the patient's complaint, the affected anatomic
system and the diagnosed cause of the patient's complaint. When
the meta function is invoked at run-time, it compares alphanumeric
strings provided by the evaluation process with the fields of all
the patient's meta records that fall within a time window specified
by the evaluation process. The meta function returns the number
of matches found, and an indication of the frequency of the patient's
complaint. Each patient has an individual meta file that is part
of the consultation history database 262. At the conclusion of the
evaluation process and dependent on the run-time operating mode
flag, the system will create a new meta record, populate its fields
with the information gathered during the evaluation process, and
append this record to either the consultation history database 262
or the Pending file 269. For example, information used in the new
meta record may come from a "Write Meta" command in a
node Work list. Each record has the following fields:
TABLE-US-00005 Field Name Data Type Width Usage DATE Date 8 Date
stamp PROBLEM Character 5 Patient complaint/symptom SYSTEM Character
5 Anatomical system affected CAUSE Character 5 Diagnosed cause of
complaint
C. The patient response database 264 is created at run-time by
the evaluation process 254. The response database 264 is an audit
trail: each record is time stamped and registers the patient's response
to each question. This database 264 can later be analyzed off-line
with a database program such as FoxPro/FoxBase to reveal how the
patient responded to questions during the evaluation process 254,
or a database program can be developed to gather response patterns
and statistics and generate appropriate reports. Each patient has
a response trace file that is part of the patient response database
264. The system 100 appends this response trace file with a response
record every time the patient answers a question or provides algorithm-requested
data. For human readability, the system also inserts "Begin
Call" and "End of Call" records in this file. Each
record has the following fields:
TABLE-US-00006 Field Name Data Type Width Usage DATE Date 8 Date
stamp MM/DD/YY TIME Character 8 Time stamp HH:MM:SS NODE Numeric
6 Current node number TYPE Character 5 Response type: DTMF or VOICE
RESP Character 5 Response command or digit string MODE Character
1 Consultation operating context VERSION Character 20 Version or
Begin/End call comment SENS_FACT Character 20 Current sensitivity
factor settings
D. The medical history objects database 266 is an auxiliary database
that supports a key feature of the MDATA system 100: past medical
history. The medical history objects database is a catalog of unique
alphanumeric codes, each code corresponding to a medical condition
or diagnosis that is not expected to change during the life of the
patient (e.g., a diagnosis for asthma is coded as "RWHZAST").
In addition to the alphanumeric codes, the MDATA system 100 uses
the "memo" field in a Foxpro database to store binary
objects. Currently, these binary objects are clinical sounds obtained
from the patient over the telephone. It is anticipated, that as
database technology gets more sophisticated (moving toward multi-media
and so forth), it will allow storing of larger and more complicated
binary files such as the following: a digitized x-ray, a digitized
CAT scan, a digitized MRI scan. In addition, as video-telephone
technology advances, it is anticipated that the system 100 will
store video images or even holographic images of the patient. For
every past medical condition there is a record in the medical history
objects database that contains the attributes of the medical condition,
and contains a pointer into the past medical history questionnaire.
The attributes of a medical condition include its data type (e.g.,
Boolean or numeric) and the number of digit positions needed to
store the value of a numeric value associated with this condition
(not applicable to Boolean type). The pointer field is useful for
obtaining medical history at run-time. If a patient has an incomplete
medical history questionnaire on file with the MDATA system 100,
then the pointer field allows the evaluation process to momentarily
suspend the evaluation, go to the medical questionnaire and ask
an individual question, collect and verify the patient's response,
and then resume the evaluation process. This "ask-when-you-need-it"
approach relieves the new patient of going through an exhaustive
medical history questionnaire before the first consultation of the
diagnostic process. Each record of the medical history objects database
has the following fields:
TABLE-US-00007 Field Name Data Type Width Usage LABEL Character
8 Object code name TYPE Character 1 Object data type DIGITS Numeric
3 Maximum number of digits in response CALL Pointer 6 Identifies
question(s) to be asked to configure this object AUDIO Binary N/A
Voice print IMAGERY Binary N/A Face print RFU Character 20 (For
future use)
E. The patient medical history (PMH) database 268 is created at
run-time by the evaluation process 254 or by use of a past medical
history questionnaire. The PMH database 268 is read by the evaluation
process during run-time. This database 268 contains each patient's
individual medical history. A new patient has an option to go through
the entire medical questionnaire at one time, thereby configuring
all the past medical history objects listed in the objects database
266. Alternately, the new patient can bypass the questionnaire and
go right into the diagnosis of a medical complaint. Then, if a medical
algorithm requires a past medical history object that has not yet
been configured, the evaluation process 254 invokes a past medical
history function before it continues with the algorithm. Each patient
has their own past medical history file, which is part of the PMH
database 268, that contains records which describe medical events
or conditions from the patient's life. The system 100 appends a
record to this file each time a past medical history object is configured
for the patient. The contents of this file are installed in the
symbol table when the patient logs in to the system 100. The medical
algorithm programmer is responsible for using a TEST command to
verify that necessary items are present in the symbol table before
algorithm execution. A side effect of a negative TEST result is
that the system 100 prompts the patient to provide that information.
The system 100 flags any new or modified items, and asks the patient
to confirm these values during an Exit Confirmation Loop which will
be described hereinbelow. Each record has the following fields:
TABLE-US-00008 Field Name Data Type Width Usage LABEL Character
20 The object's label TYPE Character 1 Object data type VALUE Character
10 Object's configured value CERT Numeric 3 Certainty of object's
value DATE Date 8 Object configuration date ICD9A Float 5 First
ICD-9 code .dwnarw. .dwnarw. .dwnarw. .dwnarw. ICD9E Float 5 Fifth
ICD-9 code
F. The "Pending" database file 269 holds medical information
gathered during Pending mode for offline verification. The Pending
database record structure is the same as that used for the past
medical history (PMH) database 268. The evaluation process writes
to the Pending database at run-time when it configures a new past
medical history object for a patient during a Pending mode interaction.
The contents of the Pending database are reviewed off-line by a
staff person, and if the information is verified, the staff person
appends the information to the patient's past medical history file.
G. An optional patient medication database 270 contains a file for
each patient containing information about medication they are taking,
or have taken in the past. The medication database 270 is created
by the evaluation process 254 at run time. A "Write Drug"
command builds a record and fills its fields with same-named memory
variables from the symbol table. The evaluation process 254 may
read the medication database 270 during run time as needed. The
treatment table 256 optionally reads the medication database 270
to determine the medication(s) being used by the patient.
TABLE-US-00009 Field Name Data Type Width GENERIC_NAME Character
20 TRADE_NAME1 Character 20 TRADE_NAME2 Character 20 TRADE_NAME3
Character 20 ICD-9-CM_CODE Character 10 ICD-9-CM_ECODE Character
10 ICD-9-CM_VCODE Character 10 OTHER Character 20 DOSAGE Character
20 ROUTE_OF_ADMINISTRATION Character 10 FREQUENCY Character 10 USE
Character 20 START_DATE Date 8 STOP_DATE Date 8 OTHER1 Character
20 OTHER2 Character 20
VII. Top-Level Flow
Referring to FIGS. 7a, 7b, 7c and 7d, the top level flow 300 of
the MDATA system 100 software will be described. The telephone number
used to access the MDATA system 100 may vary in various embodiments
of the system. If the sponsoring agency or hospital wishes to provide
access to the MDATA system 100 at no cost to the caller, then a
toll-free 800 service number can be used. If the sponsoring agency
or hospital wishes to recover the costs of running the MDATA system
100 from the caller, it may use a pay-per-call or premium charge
number (e.g., 900 service). "Current Procedural Terminology"
(CPT-4) codes are available to describe and bill third party payers
for telephone consultations. They are a listing of the descriptive
terms and identifying codes for reporting medical services and procedures.
CPT-4 codes are the most widely accepted nomenclature for reporting
physician services to insurance companies.
Beginning at a start state 302, a person 112 (FIG. 1) desiring
medical advice calls the telephone number for the MDATA system 100
on a telephone line 106. The caller may be the patient or may be
an "assistant", e.g., parent, relative, or friend, that
is helping the patient. Moving to state 304, the system 100 answers
the call automatically and greets the caller 112 with an introductory
greeting message by playing back a speech file stored on the hard
drive 152 by use of the VP board 122. Proceeding at state 306, the
MDATA system 100 asks each patient who calls the system a series
of "initial screening questions." These questions are
designed to identify patients who are critically ill; they are not
designed to identify the patient's problem. The initial screening
questions enable the system to filter out patients who require immediate
medical attention.
Moving to decision state 308, any patient found to be critically
ill is instructed to dial the emergency response telephone number
"911" at state 309 or will be automatically connected
to the nearest emergency medical services system in the patient's
area. The telephone call is terminated by the computer 102 at state
310. The following are examples of initial screening questions:
IS THIS A MEDICAL EMERGENCY? ARE YOU HAVING DIFFICULTY BREATHING?
ARE YOU EXPERIENCING SEVERE PAIN OR PRESSURE IN YOUR CHEST?
If the system determines that the patient is experiencing a medical
emergency, it may provide the patient with a menu of emergency medical
procedures at state 311. In situations where the patient or the
caller for the patient is far from the nearest emergency help, e.g.,
a rural setting, the caller may need to initiate emergency procedures
immediately. The menu of emergency medical procedures provides several
choices to the caller. If the caller presses touch tone key "1"
or speaks the word "one" into the telephone mouthpiece,
the computer 102 branches to state 312 wherein well known CPR (cardiopulmonary
resuscitation) information is recited. If the caller has a speakerphone
capability associated with the telephone 110 being used, the caller
may be able to listen to and perform the instructions given by the
system 100 in a hands-free manner away from the telephone. If the
caller presses touch tone key "2" or speaks the word "two"
into the telephone mouthpiece, the computer 102 branches to state
313 wherein well known Heimlich Hug information for choking is recited.
At the completion of either state 312 or state 313, the telephone
call ends at state 314.
If the patient is determined at state 308 not to have a medical
emergency, i.e., the MDATA system 100 is satisfied that no immediately
life threatening condition is present, the computer 102 moves to
a decision state 315 to determine if the caller is the actual patient.
If so, the computer 102 proceeds to a decision state 316 to determine
if the patient has previously registered or ever consulted with
the system 100, i.e., is not a new or first-time caller. If so,
the system 100 verifies the patient's identification and retrieves
their medical record at the patient login process 250, which will
be further described hereinbelow. At the completion of process 250,
the computer 102 proceeds through off-page connector C 317 to state
344 (FIG. 7d). If the patient is not registered, the MDATA system
100 proceeds to the patient registration process 252 for a new patient,
which will be described hereinbelow. At the completion of process
252, the computer 102 proceeds through off-page connector C 317
to state 344 on FIG. 7d.
If the caller is not the patient, as determined at state 315, the
computer 102 proceeds through off-page connector A 318 to state
320 on FIG. 7b. There will be times when the patient may not be
able to use the MDATA system 100 directly, e.g., due to injury,
weakness or altered level of consciousness. In these cases, an "assistant"
may interact with the system on behalf of the patient.
An assistant registers with the system through the assistant registration
process 274 which will be described hereinbelow. The assistant registration
record is identical to the patient registration record in structure,
but three fields have special significance for an assistant: ASST_PERM,
ASST_EXP, and RELATIONS. The ASST_PERM field is a Boolean flag that
can only be set true off-line by the system administrator who has
verified, through separate means, that a relationship exists between
a patient and an assistant. The relationships are one-to-many, i.e.,
a patient may have one or more assistants, and an assistant may
be related to more than one patient. The ASST_PERM flag may also
be constrained by the ASST_EXP field, which contains a timestamp
for the expiration of the ASST_PERM attribute. If the ASST_PERM
flag is true, then the RELATIONS pointers will point to one or more
patient records for whom this assistant is a "permanent assistant;"
otherwise the RELATIONS field will be empty.
The medical information gathered during an assisted consultation
is written to the patient's medical record only if the following
three conditions are met: (a) the assistant's ASST_PERM flag is
True (b) the ASST_EXP timestamp has not been reached (c) the assistant
has a relationship pointer to the patient record If any of these
conditions are not met, then any new medical information gathered
on this patient will be saved to the Pending file 269 for off-line
verification by the system administrator.
The system 100 establishes at state 315 whether the caller is the
patient, or an assistant. If the caller is not the patient, then
the system asserts that the caller is an assistant and, at a decision
state 320, determines if the assistant is registered. If the assistant
is not already registered with the system, the system enrolls the
new assistant at the assistant registration process 274. If the
assistant is already registered with the system 100, the computer
102 performs the assistant login process 272. At the completion
of either process 272 or process 274, the computer 102 advances
to a decision state 321.
If the patient is not already registered with the system 100, as
determined at decision state 321, then the system allows the assistant
to register a new patient at the assisted patient registration process
278. However, if the patient is already registered with the system
100, as determined at state 321, the computer 102 performs the assisted
patient login process 276. At the completion of process 278 or process
276, the computer 102 proceeds through off-page connector B 327
to a decision state 334 on FIG. 7c.
At decision state 334, the computer 102 determines if the patient's
date of birth is in the patient's medical record. If so, the computer
proceeds through off-page connector C 317 to state 344 on FIG. 7d.
If not, the system 100 attempts to get the patient's date of birth.
Moving to state 335, the system 100 asks the assistant if the patient's
date of birth is known. If so, the computer 102 advances to state
336 to request the patient's date of birth. At state 337, the system
100 recites the patient's date of birth obtained at state 336. At
a decision state 338, the assistant determines if the date of birth
is correct as recited by the system 100. If not, the computer 102
loops back to state 336 to request the patient's date of birth again.
If the patient's date of birth is correct, as determined at state
338, the computer 102 flags the date of birth for saving in the
patient's medical record at state 339, and proceeds to state 344
on FIG. 7d.
If the patient's date of birth is not known, as determined at state
335, the computer 102 proceeds to state 340 wherein the system requests
the assistant to provide an approximate age of the patient. The
age is an important parameter used in the evaluation process 254
and treatment table 256. At state 341, the system 100 recites the
patient's approximate age obtained at state 340. At a decision state
342, the assistant determines if the age is correct as recited by
the system 100. If not, the computer 102 loops back to state 340
to request the patient's approximate age again. If the patient's
approximate age is correct, as determined at state 342, the system
100 advises the assistant at state 343 to get the patient's actual
date of birth before the next consultation, and proceeds to state
344 on FIG. 7d. The system 100 uses the approximate age in the consultation
during the evaluation process 254 and the treatment table 256.
At state 344 on FIG. 7d, the system 100 presents the caller with
a system selection menu. Here, the caller is asked to select from
among four choices: diagnostic system, treatment table, a future
process/function, or end call as described below: A. Diagnostic
System: The system starts the evaluation process 254 at a menu,
where it asks the patient to begin identification of the complaint.
B. Treatment Table: The system takes the patient to the treatment
table process 256 at a menu, where it asks the patient to select
a treatment selection method. C. Future Process/Function: A future
process or function 280, undefined in the present embodiment, that
reads and/or writes the databases shown in FIG. 6. D. End Call:
The system performs several steps and then terminates the telephone
call. In either process 254 or 256, the computer 102 functions as
an interpreter as performed by algorithm processor 160 in following
the node map created by the algorithm programmer. At the exit point
of the evaluation process 254, the system 100 gives the patient
the option of selecting another complaint. At the end of the treatment
table process 256, the system gives the patient the option of selecting
another treatment.
At the completion of the evaluation process 254, treatment table
process 256, or future process 280, the system 100 loops back to
state 344 and recites the system selection menu to the caller. If
the caller chooses the End Call selection at state 344, the MDATA
system 100 moves to a decision state 345. At decision state 345,
the system 100 determines if process 254, process 256, or process
280 did not occur in Information mode, i.e., did occur in either
Real mode or Pending Mode, and examines the patient's symbol table
to determine if any of the configured memory variables are past
medical history conditions that need to be saved to the patient's
medical history file. If both conditions are true at state 345,
the system 100 advances to a decision state 346 to determine if
the consultation is being performed in Real mode. If not, the consultation
is being performed in Pending mode, and the system 100 then writes
any new patient information obtained during the consultation to
the Pending file 269. If state 346 proves to be true, i.e., Real
mode, for each past medical condition that needs to be saved, the
MDATA system 100 asks the patient at state 348 to grant permission
to save the datum to the patient's medical history file and to confirm
that the datum is correct. For example, during a consultation for
cough, the MDATA system 100 learned that the patient has been diagnosed
as being HIV positive. The system 100 will ask, "May I record
the information about your HIV diagnosis in your medical record?"
If the patient responds "yes", then the system 100 will
ask, "Please verify that your diagnosis for HIV was positive,
is this correct?" If the patient responds "yes",
then the system 100 writes this fact to the patient's medical history
file. After confirmation, each data item is stored in the patient's
file in the patient medical history database 268 (FIG. 6).
At the completion of either updating the history database 268 at
state 348, state 345 proves to be false, or at the completion of
state 347, the system 100 moves to a decision state 349. Before
the MDATA system 100 ends the consultation with the patient, it
presents a summary of all the advice it has given. The patient is
asked to write down and repeat back the key points. The MDATA system
100 then gives the patient the option of receiving a summary of
the consultation session and specific recommendations provided by
the system by either facsimile or first class mail. If a fax is
desired, the system 100 asks the patient for a fax number at state
350. The patient also has the option to send a summary of the consultation
to his or her health care provider or specialist. Proceeding to
state 351, the computer 102 adds the transcript of the current telephone
session to a fax queue for subsequent transmission. At the completion
of state 351 or if the system 100 determined at state 349 that the
session transcript was not to be faxed, the telephone call is terminated
at state 352.
VIII. Login Process
Referring now to FIGS. 8a and 8b, the patient login process 250
defined in FIG. 7a will be described. This process 250 is called
if the patient has previously called and registered with the system
100. Beginning at a start state 358, the computer 102 moves to state
359 and initializes a match flag to true. The match flag is checked
later in this process 250 in conjunction with setting the mode of
the consultation. Proceeding to state 360, the computer 102 prompts
the patient for the patient ID (identification) number (PIN) that
is assigned during the registration process. The patient registration
process 252 will be described in conjunction with FIGS. 9a and 9b.
Proceeding to a decision state 361, the computer 102 determines
whether the PIN is valid. If not, the computer 102 determines, at
a decision state 362, if less than three tries at entering the PIN
have been attempted. If so, the computer 102 loops back to state
360 to repeat the request for the PIN. However, if three attempts
at entering the PIN have been made, as determined at state 362,
the computer 102 plays a polite message that advises the patient
that the login attempt failed and terminates the call at state 363.
The computer 102 reports the failed login attempt to the system
administrator at the sponsoring agency, hospital or other organization.
The patient is allowed to reregister as a new patient, however,
to permit access to the needed medical information. The system administrator
resolves this type of situation off-line.
If the patient has correctly entered a valid PIN, as determined
at state 361, the computer 102 moves to a decision state 364 to
determine if the patient identified by the PIN has a voice print
or sample voice waveform on file in the system 100. If not, the
computer 102 proceeds to state 365 to record the voice print of
the patient, e.g., the patient's pronunciation of his or her full
name. The patient's voice print may not be on file, for example,
if the patient could not provide a voice print during the assisted
patient registration process 278 in a prior consultation. At the
completion of recording the voice print at state 365, the computer
102 advances to state 366 wherein the match flag is set to false
to indicate that the patient's voice print was recorded during the
current login.
If the patient identified by the PIN has a voice print on file
in the system 100, as determined at state 364, the computer 102
proceeds to state 367 and prompts the patient to pronounce his or
her full name. Moving to a decision state 368, the computer 102
determines whether the voice sample obtained at state 367 passes
the matching criteria. If not, the computer proceeds to state 369
and recites a message that the current voice sample does not pass
the matching criteria. In the presently preferred embodiment, the
current voice sample is compared to the reference voice sample recorded
during the patient registration process 252 or the assisted patient
registration process 278. Because the voice samples did not match,
as determined at state 368, the computer 102 sets the match flag
to false at state 370. In this case, the match flag is set to false
to indicate that one of the security checking methods has failed.
However, the process 250 continues at state 372 after the match
flag is set to false at either state 366 or 370.
If the voice sample passed the matching criteria at state 368,
the computer 102 advances to state 371 and recites a message that
the current voice sample passed the matching criteria. This security
check condition is now satisfied, and the match flag remains set
to true. At the completion of state 371 the computer 102 moves to
state 372. At state 372, the computer 102 verifies the sex and age
of the patient by reciting the sex and age, as stored in the enrollment
database 260 (obtained during the patient registration process 252),
to the patient. At a decision state 373, the patient responds to
the correctness of the recited information. If the sex or birth
date information is not correct, the computer 102 moves to state
374 to request the correct information. The computer 102 then proceeds
back to state 372 to verify the information received at state 374.
If the result of the decision state 373 is true, i.e., the sex and
age are correct, the computer moves through off-page connector A
375 to a decision state 376 on FIG. 8b to determine if the patient
desires to conduct the telephone session in Real mode or Information
mode. If Information mode is desired, the computer 102 moves to
a decision state 377 to determine if the patient's sex and age are
to be used during the Information mode consultation. If not, the
computer 102 moves to state 378 to request an age and sex to use
in a hypothetical situation during the Information mode session.
Moving to a decision state 379, the computer 102 recites the sex
and age obtained at state 378, and asks the patient to confirm that
this information is correct. If not, the computer 102 moves back
to state 378 to request the age and sex again. When decision state
379 is true or the patient's age and sex are to be used during this
consultation, as determined at state 377, the computer 102 moves
to state 380 and sets the operating mode to be Information mode.
If decision state 376 is determined to be Real mode, the computer
102 moves to a decision state 381 to check if the match flag is
true. If not, the system 100 advises the patient, at state 382,
that the current consultation is to be performed in Pending mode.
The operating mode is set to be Pending mode at state 383. If the
match flag is true, as determined at state 381, the computer 102
sets the operating mode to be Real mode at state 384.
At the completion of setting the operating mode at either state
380, state 383, or state 384, the computer moves to a decision state
386. At decision state 386, the computer 102 determines if the patient
desires to review the touch tone commands described during the registration
process. If so, the computer 102 advances to state 388 and recites
the touch tone commands. At the completion of state 388 or if the
patient did not wish to review the touch tone commands, the computer
102 proceeds to a decision state 390 wherein the computer 102 determines
if the patient desires to review the voice keywords described during
the registration process. If so, the computer 102 advances to state
392 and recites the voice keywords. At the completion of state 392
or if the patient did not wish to review the voice keywords, the
computer 102 proceeds to a decision state 394 wherein the computer
102 determines if the patient desires to enable prompting. If so,
the computer 102 advances to state 396 and enables prompting. If
not, prompting is disabled at state 398. To "enable prompting"
means that the patient would like to be prompted for responses.
This is referred to as "hard" prompting, since this will
remain in effect for the duration of the call. If hard prompting
is off, and the system 100 has difficulty recognizing patient responses,
the computer 102 turns on "soft" prompting. After the
next successful recognition, the computer 102 turns off soft prompting.
At the completion of state 396 or 398, the computer 102 returns
at state 400 to the top level flow (FIG. 7).
Referring now to FIGS. 12a and 12b, the assistant login process
272 defined in FIG. 7b will be described. This process 272 is called
if the assistant has previously called and registered with the system
100. Beginning at a start state 940, the computer 102 moves to a
state 942 and prompts the assistant for the assistant ID (identification)
number (AIN) that is assigned during the registration process. The
assistant registration process 274 will be described in conjunction
with FIGS. 14a and 14b. Proceeding to a decision state 944, the
computer 102 determines whether the AIN is valid. If not, the computer
102 determines, at a decision state 946, if less than three tries
at entering the AIN have been attempted. If so, the computer 102
loops back to state 942 to repeat the request for the AIN. However,
if three attempts at entering the AIN have been made, as determined
at state 946, the computer 102 plays a polite message that advises
the assistant that the login attempt failed and terminates the call
at state 948. The computer 102 reports the failed login attempt
to the system administrator at the sponsoring agency, hospital or
other organization.
If the assistant has correctly entered a valid AIN, as determined
at state 944, the computer 102 proceeds to state 950 and prompts
the caller to pronounce his or her full name. Moving to a decision
state 951, the computer 102 determines whether the voice sample
obtained at state 950 passes the matching criteria. If not, the
computer proceeds to state 952 and recites a message that the current
voice sample does not pass the matching criteria. In the presently
preferred embodiment, the current voice sample is compared to the
reference voice sample recorded during the assistant registration
process 274. Because the voice samples did not match, as determined
at state 951, the computer 102 sets the operating mode to Pending
at state 953. In this case, Pending mode is set to indicate that
one of the security checking methods has failed. However, the process
272 continues at state 960 on FIG. 12b after Pending mode is set
at state 953.
If the voice sample passed the matching criteria at state 951,
the computer 102 advances to state 954 and recites a message that
the current voice sample passed the matching criteria. This security
check condition is now satisfied. Next, three additional checks
are performed on the assistant identified by the AIN obtained at
state 942. At a decision state 955, the computer 102 determines
if the permanent assistant flag is true, as stored in the patient
and assistant enrollment database 260. If so, the computer 102 advances
to a decision state 956 to determine if the expiration date for
the permanent assistant is in the future, i.e., the expiration date
has not been reached yet. If so, the computer 102 advances to a
decision state 957 to determine if a relationship exists between
the assistant and a patient, i.e., the assistant has a relationship
pointer to the patient record. If so, the operating mode is set
to Real at state 958, and then the computer 102 advances through
off-page connector A 959 to state 960 on FIG. 12b. However, if any
of the decision states 955, 956, or 957 prove to be false, the computer
102 moves to state 953 wherein the operating mode is set to Pending.
States 960 through 964 are similar to states 372 through 374 of
the patient login process 250 (FIG. 8). Because of this similarity,
only significant differences are discussed in the interest of avoiding
repetitiveness. States 960, 962 and 964 verify the assistant's age
and sex, rather than the patient as in states 372, 373 and 374.
States 966 through 980 are similar to states 386 through 400 of
the patient login process 250 (FIG. 8b). The main distinction is
that states 966 980 pertain to the assistant and states 386 400
pertain to the patient.
Referring now to FIGS. 13a and 13b, the assisted patient login
process 276 defined in FIG. 7b will be described. This process 276
is called if both the patient and the assistant have previously
called and registered with the system 100. This process allows the
patient flexibility by permitting the assistant to provide help
during the login and subsequent consultation. Beginning at a start
state 990, the computer 102 moves a state 992 and prompts the assistant
for the patient ID (identification) number (PIN) that is assigned
during the registration process. As previously defined in FIG. 7,
the assisted patient registration process 278 is called if the patient
is not already registered. Process 278 will be described in conjunction
with FIGS. 15a and 15b. Proceeding to a decision state 994, the
computer 102 determines whether the PIN is valid. If not, the computer
102 determines, at a decision state 996, if less than three tries
at entering the PIN have been attempted. If so, the computer 102
loops back to state 992 to repeat the request for the PIN. However,
if three attempts at entering the PIN have been made, as determined
at state 996, the computer 102 plays a polite message that advises
the caller that the login attempt failed and terminates the call
at state 998. The computer 102 reports the failed login attempt
to the system administrator at the sponsoring agency, hospital or
other organization. If the assistant doesn't know the PIN and the
patient cannot provide it, the assistant is allowed to reregister
the patient as a new patient at process 278 to permit access to
the needed medical information. In this case, the assistant may
have to estimate the age of the patient if the patient has, for
example, an altered state of consciousness. The system administrator
resolves the record-keeping in this situation off-line.
If the assistant has correctly provided a valid PIN to the system
100 at state 994, the computer 102 moves to a decision state 993
to determine if the patient identified by the PIN has a voice print
or sample voice waveform on file in the system 100. If not, the
computer 102 moves to a decision state 1003 to determine if the
patient can provide a voice sample. If not, the computer 102 proceeds
through off-page connector B 997 to state 1008 on FIG. 13b. If the
patient can provide a voice sample, as determined at state 1003,
the computer 102 moves to state 995 to record the voice print of
the patient, e.g., the patient's pronunciation of his or her full
name. The patient's voice print may not be on file, for example,
if the patient could not provide a voice print during the assisted
patient registration process 278 in a prior consultation. At the
completion of recording the voice print at state 995, the computer
proceeds through off-page connector B 997 to state 1008 on FIG.
13b.
If the patient identified by the PIN has a voice print on file
in the system 100, as determined at state 993, the computer 102
proceeds to state 999 and asks whether the patient can provide a
voice sample to the system. If not, the computer 102 proceeds through
off-page connector B 997 to state 1008 on FIG. 13b. States 1000,
1002, 1004, 1006 are similar to states 367, 368, 369, 371, respectively,
of the patient login process 250 (FIG. 8). Because of this similarity,
only significant differences are discussed in the interest of avoiding
repetitiveness. At the completion of state 1004, i.e., the patient's
voice sample does not pass the matching criteria, the computer 102
proceeds through off-page connector B 997 to state 1008 on FIG.
13b. At the completion of state 1006, i.e., the patient's voice
sample does pass the matching criteria, the computer 102 proceeds
through off-page connector A 1001 to state 1005 on FIG. 13b.
At the completion of state 995, i.e., the patient's voice print
is recorded, state 999 or state 1003, i.e., the patient cannot provide
a voice sample, or state 1004, i.e., the voice sample match fails,
the system continues process 276 at state 1008 on FIG. 13b. For
the three situations just described in this process 276, the computer
102 sets the operating mode to Pending at state 1008. The system
100 then advises the caller at state 1009 that new patient information
will not be saved to the patient's medical record because the consultation
is in Pending mode until the information is verified off-line.
At the completion of state 1006, i.e., the voice sample passes,
the computer 102 continues process 276 at state 1005 wherein the
operating mode is set to Real. The system 100 then advises the caller
at state 1007 that new patient information will be saved to the
patient's medical record.
At the completion of state 1009 or state 1007, the computer 102
moves to state 1010. States 1010, 1012 and 1014 verify the patient's
age and sex, similar to states 372, 373 and 374 (FIG. 8). States
1016 through 1030 are similar to states 386 through 400 of the patient
login process 250 (FIG. 8). The main distinction is that states
1016 1030 are directed to the assistant and states 386 400 are directed
to the patient.
IX. Registration Process
Referring now to FIGS. 9a and 9b, the patient registration process
252 defined in FIG. 7a will be described. This process 252 is called
if the patient has not previously called and registered with the
system 100. During the first consultation, the MDATA system 100
obtains the patient's age and sex. This is the minimum amount of
information that the MDATA system requires in order to give medical
advice. The more information the MDATA system has about a patient,
however, the more specific is its advice.
The MDATA system 100 assigns each of its patients a unique patient
identification number. In addition, when a patient initially registers,
the patient's own pronunciation of his or her name is recorded,
digitized and saved to their medical record. Then, when the patient
calls back, the previous recording is retrieved and the patient
is asked to repeat their name exactly as they did during registration.
The two recordings are then compared to see if they match. This
use of "voice printing" helps to further ensure the security
and confidentiality of a patient's medical record.
Beginning at a start state 420, the computer 102 proceeds to state
422, requests the sex of the patient, and verifies by repeating
the response given by the patient. Moving to a decision state 424,
the patient responds by indicating to the system 100, via touch
tone key or a voice response, whether the repeated information is
correct. If not, the computer 102 loops back to state 422 to request
the information again. When the information is correct at state
424, the computer 102 proceeds to states 426 and 428 to request
and verify the birth date of the patient in a similar fashion to
states 422 and 424.
When the decision state 428 is determined to be true, the computer
102 proceeds to state 427 and requests the patient to pronounce
his or her full name. Moving to state 429, the full name is digitized
and stored in a subdirectory on the hard drive 152 (FIG. 1) indexed
by a Patient Identification Number (PIN). File names are of the
form: <PIN>.vox. The computer 102 accesses a file to retrieve
the next available PIN. The path name to the recorded voice file
is saved in the patient's record in the enrollment database 260.
In subsequent telephone sessions with the system 100, the patient's
voice waveform will be compared to the recorded voice waveform for
security and other optional purposes. When the voice waveform is
stored, the computer 102 moves to state 431 and provides the PIN
to the patient. The patient is informed of the importance to save
the PIN for use in future consultations with the system 100.
At the completion of state 431, the computer 102 moves to a decision
state 430 to determine if the patient has a MDATA system user pamphlet
available. If so, the computer 102 moves to state 436 and requests
the patient to turn to the pamphlet page that documents the touch
tone keys, voice keywords, and modes. If not, the computer 102 moves
to a decision state 432 to determine if the patient would like the
system 100 to pause to enable the patient to get paper and a writing
instrument for writing user instructions. If so, the computer 102
pauses at state 434 for 30 seconds. At the completion of the pause
at state 434, if the user did not desire a pause at state 432, or
after the patient is instructed to turn to the proper page of the
pamphlet, the computer 102 proceeds to state 440 of FIG. 9b via
the off-page connector A 438.
At state 440, the system 100 provides an explanation of the touch
tone keys to the patient. These keys were described above in relation
to the discussion on Voice Keywords and DTMF Command Keys. Moving
to state 442, the computer 102 asks if the patient desires to hear
the explanation of keys again. If so, the computer 102 repeats state
440. If not, the computer 102 advances to state 444 wherein an explanation
of the voice keywords is provided to the patient. These keywords
were previously described above. Moving to state 446, the computer
102 asks if the patient desires to hear the explanation of keywords
again. If so, the computer 102 repeats state 444. If not, the computer
102 advances to state 448 wherein an explanation of Real and Information
modes is provided to the patient. These modes were previously described
above. Moving to state 450, the computer 102 asks if the patient
desires to hear the explanation of the modes again. If so, the computer
102 repeats state 448. If not, the computer 102 advances to state
452 wherein a summary of new user information is recited to the
patient. The summary includes a recap of the two methods of controlling
the system: voice key words and DTMF, and the two interaction modes:
Real and Info. The computer 102 returns at state 454 to the top
level flow (FIG. 7).
Referring now to FIGS. 14a and 14b, the assistant registration
process 274 defined in FIG. 7b will be described. This process 274
is called if the caller is not a registered patient and has not
previously called and registered as an assistant with the system
100. States 1050 through 1090 are similar to states 420 through
454 of the patient registration process 252 (FIG. 9). Because of
this similarity, only significant differences are discussed in the
interest of avoiding repetitiveness. States 1052, 1056, 1060, 1062
and 1064 pertain to the assistant rather than the patient as in
states 422, 426, 427, 429 and 431 (FIG. 9a), respectively. State
1060 records the assistant's pronunciation of his or her full name
and state 1062 saves it in the patient and assistant enrollment
database 260. The system 100 provides an assistant identification
number (AIN) at state 1064. The AIN is used similarly to the PIN
in the access of files or records. The remaining states 1066-1090
are directed to the assistant also.
Referring now to FIGS. 15a and 15b, the assisted patient registration
process 278 defined in FIG. 7b will be described. This process 278
is evoked if the caller is not the patient and the patient has not
previously called and registered with the system 100. States 1110
through 1150 are similar to states 420 through 454 of the patient
registration process 252 (FIG. 9). Because of this similarity, only
significant differences are discussed in the interest of avoiding
repetitiveness. The main difference is that the assistant is interacting
with the system 100 on behalf of the patient during this process
278, and therefore, the operating mode is set to Pending at state
1111. States 1112 and 1116 obtain the patient's sex and age, respectively.
If the patient cannot provide the age to the assistant and the system,
the assistant provides an estimated age. The estimated age can be
corrected during a subsequent consultation with the system 100.
At state 1119, the system 100 asks whether the patient can provide
a voice sample of his or her full name. If so, the voice waveform
is recorded and saved in enrollment database 260 (FIG. 6) at states
1120 and 1122. If the patient cannot provide a voice sample at state
1119, the system 100 informs the assistant, at state 1121, that
the patient's voice sample will be requested during the subsequent
consultation. Then, whether or not a voice sample is recorded, the
system 100 provides a patient identification number (PIN) of the
patient to the assistant and the patient (if coherent) at state
1123. The caller is instructed to safeguard the PIN for future consultations
by either the patient or the assistant on behalf of the patient.
If the assistant and/or patient desires to hear the PIN again, as
determined at a decision state 1124, the computer 102 repeats the
PIN at state 1123. The computer 102 proceeds through off-page connector
A 1125 to a decision state 1126 on FIG. 15b. The remaining states
1126 1150 in process 278 are directed to the assistant rather than
the patient, as in states 430 454 of process 252 (FIG. 9).
X. Evaluation Process
Referring now to FIGS. 10a and 10b, the evaluation process 254
defined in FIG. 7d will be described. This process 254 is called
if the patient has selected the Diagnostic System choice in the
system selection menu (FIG. 7d, state 344). Beginning at a start
state 470, the computer moves to state 471 and recites a identification
method menu to request complaint identification. After the initial
screening questions (state 306, FIG. 7a) are completed and a medical
record (registration function 252) has been opened, the MDATA system
100 asks the patient to describe the complaint. The identification
of the patient's problem is one of the most important steps in the
evaluation process. The system 100 has built-in safeguards to ensure
that the patient understands the questions and that the MDATA system
100 understands the patient's complaint. For example, the system
keeps tables of synonyms so that any problem regarding the semantics
of a question or a response can be quickly resolved. The complaint
may be identified in one of four ways: by anatomic system 472, by
cause 476, by alphabetic groups 480 or by catalog number 482.
The easiest and most frequently used way to identify the complaint
is by anatomic system, i.e., "what system is your problem in?".
Anatomic system 472 refers to basic body systems such as cardiovascular,
respiratory, nervous system, digestive, ear/nose/throat, ophthalmology,
gynecology/obstetrics, urology, blood/hematology, skin, and endocrine.
After the patient has identified the anatomic system of their complaint,
they are asked a series of "System Screening Questions"
at state 473. For each anatomic system, there are some symptoms
or combinations of symptoms that, if present, would mandate immediate
intervention, such that any delay, even to go any further through
the menuing process, could cause harm. For example, if the patient
has identified the cardiovascular system as the anatomic system
in which his or her complaint lies (i.e., chest pain), the MDATA
system 100 will ask the cardiovascular system screening questions.
For example, the patient would be asked, "Do you have both
pressure in your chest and shortness of breath? If these symptoms
are present together, immediate intervention is necessary. With
the thrombolytic agents that are available today, time is critical
in order to save myocardial cells. Just a few minutes can mean the
difference between being able to resuscitate a patient or not.
Therefore, at state 474, the system 100 determines if a serious
medical condition exists. If so, the system 100 moves to state 486,
plays a message that advises the patient to seek immediate medical
attention and ends the evaluation process 254 at a terminal state
488. If it is determined at state 474 that a serious medical condition
does not exist, the system 100 proceeds to a complaint menu at state
475 and recites a list of algorithms dealing with the problem that
corresponds to the anatomic system selected. The patient then selects
an algorithm from the list.
If the patient is not sure of the anatomic system, the system 100
attempts to identify the problem by requesting the cause. Cause
476 refers to a cause for an illness or disease such as trauma,
infection, allergy/immune, poisoning, environmental, vascular, mental,
genetic, endocrine/metabolic, and tumor. Once the patient has identified
what they think is the cause of their problem (e.g., trauma, infection),
the MDATA system 100 asks the "Cause Screening Questions"
at state 477. These questions are asked to make sure that the patient
is not suffering from an immediate life-threatening problem. For
example, if infection were chosen as the cause, the system would
first rule out the possibility of epiglottitis or meningitis before
proceeding. Therefore, at state 478, the system 100 determines if
a serious medical condition exists. If so, the system 100 moves
to state 486, plays a message that advises the patient to seek immediate
medical attention and ends the evaluation process 254 at a terminal
state 488. If it is determined at state 478 that a serious medical
condition does not exist, the system 100 proceeds to a complaint
menu at state 479 and recites a list of algorithms dealing with
the problem that corresponds to the cause selected. The patient
then selects an algorithm from the list.
Alphabetic groups 480 lists the items in the anatomic system group
and the cause group together in alphabetic order. Moving to state
481, the system determines if the selected item is from the cause
subgroup of the combined alphabetic groups. If so, the system 100
proceeds to the "Cause Screening Questions" at state 477.
If not, the system moves to the "System Screening Questions"
at state 473.
Enter Catalog number state 482 refers to the ability of the patient
to select and enter an individual medical algorithm from a catalog
of medical algorithms listed in the patient guide distributed to
all patients. At the completion of state 475, 479, or 482, the complaint
has been identified, and the computer 102 proceeds to state 483
wherein a series of "initial" problem screening questions
are presented to the patient. There is a different set of problem
screening questions for every complaint for which advice is offered.
For the purpose of this discussion, "Headache" will be
used as an example to describe how the system approaches the diagnosis
of a problem and provides treatment recommendations. As with many
problems, there are some causes of headache that require immediate
medical attention. Quite often, when a problem is very serious,
any delay, even to discuss it further, can adversely affect the
patient's outcome. The problem screening questions identify, at
a decision state 484, the subset of patients whose headaches may
require immediate medical care. If a serious medical condition exists,
the patient is advised to seek immediate medical attention at state
486. The computer 102 then ends the evaluation process at state
488 and returns to state 344 in FIG. 7d.
The following is an example of a problem screening question for
headache: ARE YOU CONFUSED, LETHARGIC, OR LESS ORIENTED THAN USUAL?
By asking a question about the patient's level of consciousness,
a dilemma has been confronted. What does the MDATA system 100 do
about the patient whose problem itself prevents them from appropriately
responding to questions or following advice?
There are some conditions that, by their very nature, may prevent
patients from answering questions correctly. For this reason, the
MDATA system 100 utilizes a "mental status examination"
function 508. The mental status examination is a series of questions
used to assess the patient's orientation. This function 508 allows
the MDATA system 100 to assess the patent's ability to respond to
questions and to follow advice. Although only shown in FIG. 10b,
the mental status examination function 508 is incorporated into
the dialogue of any problem whose presentation could include an
altered level of consciousness. Function 508 will be further described
in conjunction with FIG. 16.
The MDATA system 100 will, of course, be accessed by patients in
whom an altered level of consciousness is not expected based on
the problem that the patient has. The system 100 does anticipate
the possibility of the patient having an altered level of consciousness
in some problems, e.g., when a patient consults the system for striking
his or her head, and invokes the mental status exam function 508.
However, an intoxicated patient, calling for some other complaint,
e.g., a sprained ankle, is one example where the patient may not
be able to understand instructions from the system 100. For this
reason, the MDATA system also utilizes a "semantic discrepancy
evaluator routine" (SDER) function 510. The SDER function provides
information to the patient and then, after a predetermined period
of time, asks the patient to repeat or select the information. The
patient's answer is then evaluated within system 100. If discrepancies
are determined, the system automatically invokes the mental status
examination function 508. In another embodiment, the system 100
asks the patient for some information in different ways at different
times, and then compares the patient's responses to determine if
they are consistent. If not, the system automatically invokes the
mental status examination function 508. Although only shown in FIG.
10b, the SDER function 510 is embedded throughout system 100, and
is randomly evoked by the computer 102. Function 510 will be further
described in conjunction with FIG. 17.
Continuing with the headache example at state 483, the MDATA system
100 asks the next problem screening question in order to help exclude
the possibility of meningitis, a very serious infection of the central
nervous system. IS BENDING YOUR NECK FORWARD SO THAT YOUR CHIN TOUCHES
YOUR CHEST EITHER PAINFUL OR NOT POSSIBLE? If the answer to this
question is "yes", a serious medical condition exists
at state 484 and the system 100 instructs the patient to seek immediate
medical attention at state 486.
The initial screening questions (state 306, FIG. 7a) and the problem
screening questions (state 483) can usually be completed within
a minute or so. Once the MDATA system 100 has excluded the causes
of headache that require immediate medical attention, the system
becomes a little less formal and more conversational in the subsequent
states. The examples given, of course, do not represent all the
initial or problem screening questions.
If no serious medical condition exists, as determined at state
484, the computer 102 proceeds to a decision state 490 wherein the
system 100 identifies those patients who are "re-entering"
the system from an earlier consultation. This occurs most frequently
when the system 100 needs to monitor a patient's symptom over time,
or if the system is initially unable to make a specific diagnosis
and would like the patient to re-enter the system again, typically
within a few hours. The system sets an internal re-enter flag to
identify the situation where a patient is calling again for the
same complaint. If the flag is set at state 490, the computer 102
proceeds to state 492 and branches to a re-enter point in the evaluation
process depending on which medical algorithm has been evoked. The
computer 102 moves via off-page connector A 494 to state 506 (FIG.
10b) to the appropriate re-enter point.
If the re-enter flag is not set, as determined at state 490, the
computer 102 moves via off-page connector B 496 to a decision state
499 to determine if the consultation is being performed in Real
mode or Pending mode. If not (i.e., the consultation is in Information
mode), the computer proceeds to state 506 to continue the evaluation
process. If the consultation is in Real or Pending mode, the computer
102 calls a "meta" function 500 wherein patients are subjected
to several "meta" analyses. This concept will be explained
in conjunction with FIG. 11, but, in general, it refers to the system's
ability to evaluate the patient's present problem in the context
of their past use of the system. The Meta function 500 matches various
parameters against a predetermined meta threshold. When the MDATA
system 100 opens a patient's consultation history file in database
262 (FIG. 6), it calculates how many times the patient has consulted
the system for the same complaint. For each problem, the MDATA system
100 allows a specified number of system consultations, per unit
of time, before it takes action. If the meta threshold is reached,
as determined at a decision state 502, the MDATA system 100 makes
a recommendation based on this fact alone at state 504. For example,
let us assume that the threshold was set at five headaches in two
months. If the patient consulted the MDATA system 100 for headache
more than four times in two months, the threshold would be reached
and the system would make an appropriate recommendation. The threshold,
of course, is different for each complaint, and may be modified
by a set of sensitivity factors that will be described hereinbelow.
Alternately, the system 100 uses a time density ratio (TDR) calculated
by the meta function 500 to determine if a recommendation should
be given to the patient.
At the completion of state 504, or if the meta threshold was not
reached at state 502, the computer 102 proceeds to state 506 to
continue the evaluation process. State 506 includes a medical algorithm
as selected by the patient in states 475, 479, or 482. Although
not necessarily a complete list, types of medical algorithms include:
Headache, Convulsion or Seizure, Chest Pain, Heatstroke, Altered
Level of Consciousness, Tremor, Dizziness, Irregular Heartbeat,
Fainting, Shortness of Breath, Chest Injury, Depression, Head Injury,
Cough, Croup, High Blood Pressure, Hyperventilation, Numbness, Wheezing,
Inhalation Injury, and Strokes. In addition to meta and past medical
history functionality, at least some of the listed medical algorithms
rely upon knowledge of age and/or sex of the patient as provided
in the presently described system 100 at time of registration (see
FIGS. 9a and 13a).
Depending on the medical algorithm and the exact patient condition,
one or more auxiliary functions may be called by state 506 as follows:
the mental status examination function 508, the SDER function 510,
a past medical history function 512, a physical self examination
function 514, a patient medical condition function 516, and a symptom
severity analysis function 518. These functions will be described
hereinbelow.
Returning to the headache example, after the meta analyses (function
500) are completed, the MDATA system 100 assesses the severity of
the patient's headache on a one-to-ten scale. The importance of
this purely subjective quantization of the symptom's severity will
become apparent later in this description.
Although the MDATA system's paradigm is fundamentally an algorithmic
one, the underlying logic of the diagnostic process for headache
will be described. The MDATA system 100 begins the diagnostic process
for headache by referring to three lists stored internally in the
computer 102.
The first list is a ranking of the most common causes of headache
in the general population. The most common cause is ranked first,
the second most common is ranked second, and so on. In other words,
the first list ranks all the causes of headache in the general population
in decreasing frequency of occurrence.
The second list is a ranking of the various causes of headache
according to the seriousness of the underlying cause. The more serious
causes are positioned toward the top of the list, the less serious
toward the bottom. For example, meningitis, brain tumor, and subarachnoid
hemorrhage would be the top three causes on the second list.
The third list is quite similar to the second list. It ranks the
causes of headache according to the rapidity with which intervention
is necessary. The causes of headache that require immediate intervention,
such as meningitis and subarachnoid hemorrhage, are toward the top.
The problem screening questions (state 483) were developed from
this list.
During the evaluation process 254, the MDATA system 100 asks the
patient a series of "diagnostic screening questions."
From the answers to these questions, along with any physical signs
elicited from the patient (from function 514), under the direction
of the MDATA system 100, the system establishes the most likely
cause of the patient's headache.
The following are examples of diagnostic screening questions for
headache: DO YOU EXPERIENCE MORE THAN ONE KIND OF HEADACHE? DO YOU,
OR DOES ANYONE ELSE, KNOW THAT YOU ARE GOING TO GET A HEADACHE BEFORE
THE ACTUAL PAIN BEGINS? DO YOUR HEADACHES FREQUENTLY WAKE YOU UP
AT NIGHT? DO YOUR HEADACHES USUALLY BEGIN SUDDENLY?
Based upon the answers to the diagnostic screening questions, the
MDATA system 100 reorders the first list. The first list then becomes
a list of the possible causes of headache in decreasing levels of
probability in the patient seeking consultation. The first list
is now patient specific. If the MDATA system 100 concludes that
migraine is the most likely cause of the patient's headache, then
migraine will now be ranked at the top of the first list.
The MDATA system 100 is knowledgeable about the difference between
classic, common, and all other variants of migraine, but for this
discussion the general term "migraine" will be used. After
reordering the first list and placing migraine at the top, the MDATA
system 100 then asks several questions related specifically to migraine
headaches. These are called the "migraine screening questions."
The probability that the patient actually has a migraine headache
is calculated from the answers to these questions. Each cause of
headache has its own set of screening questions, physical examination
signs, and, if the patient has the MDATA system's Home Diagnostic
and Treatment Kit, appropriate laboratory tests.
The following are examples of migraine screening questions: IS
EITHER NAUSEA OR VOMITING ASSOCIATED WITH YOUR HEADACHE? ARE VISUAL
DISTURBANCES ASSOCIATED WITH YOUR HEADACHE?
After obtaining the answers to the migraine screening questions,
if the probability that the patient is suffering from a migraine
headache does not reach an established threshold, the next cause
of headache on the reordered first list is considered and pursued
as a diagnosis.
If the probability of having a migraine headache does reach the
threshold, the MDATA system 100 asks the patient several more questions
designed to confirm the presence of migraine, given the fact that
the system has already determined that it is the most likely diagnosis.
These are called the "migraine confirmation questions."
Just as each cause of headache has a set of screening questions,
each cause of headache also has a set of confirmation questions.
The following are examples of migraine confirmation questions:
DOES ANYONE WHO IS RELATED TO YOU BY BLOOD HAVE MIGRAINE HEADACHES?
WHEN YOU HAVE A HEADACHE DO YOU FEEL MORE LIKE LYING DOWN OR WALKING
AROUND?
From the answers to the migraine confirmation questions, the MDATA
system 100 calculates the probability of confirmation of migraine.
In Bayes' terms (which refer to the probability of certainty of
a diagnosis) this is called a "conditional probability."
If the probability of migraine headaches reaches threshold, but
the probability of confirmation of migraine does not reach threshold,
then, as mentioned, the system pursues the next diagnostic cause
of headache on the patient specific list.
If the probability of the second cause of headache (say cluster)
reaches threshold, then the "cluster confirmation questions"
are asked. If they reach threshold, then again the serious causes
of headache are excluded as a diagnosis.
The MDATA system 100 stores the scores of all the screening and
confirmation questions in what are called "session memory variables"
that are installed in the symbol table. It is, in part, these scores
that are then used to determine the probability of one diagnosis
versus another.
For example, if the answers to the cluster confirmation questions
do not reach threshold, then the scores of the screening and confirmation
questions of migraine and cluster are compared to see which cause
is the more probable.
Whichever has the higher score, or exceeds the other by a predetermined
threshold, is then assumed to be the more probable cause. The list
is, if necessary, again reordered. This time it becomes the final
diagnostic list which is a list of differential diagnoses in decreasing
levels of probability for this patient.
All of the headache scoring thresholds are modified or modulated
by a series of sensitivity factors as are all aspects of the system
in which scalar thresholds are used. The sensitivity factors are
discussed hereinbelow in section XVIII. For example, if it was found
that a subset of patients in which the diagnosis of meningitis was
not being made as early as it should be, then the sensitivity factor
modifying the temperature threshold could be decreased so that now,
a patient with a lower temperature would be instructed to seek an
immediate evaluation.
Before discussing the results with the patient, however, the MDATA
system 100 must again rule out the serious causes of headache. The
problem screening questions have already filtered out those patients
who have a serious cause of headache, such as meningitis, that requires
immediate medical intervention.
The MDATA system 100 now proceeds to eliminate those causes of
headache that, although serious, do not require immediate medical
attention. For example, although a brain tumor is a serious cause
of headache, it is not as immediately life threatening as meningitis
or subarachnoid hemorrhage. To accomplish this task, the MDATA system
100 sequentially analyzes the serious causes of headache that are
located at the top of the second list. The MDATA system 100 again
asks the patient the set of screening questions associated with
each of the serious causes of headache. This time, however, the
MDATA system 100 makes sure that the probability of having any of
the serious causes of headache is sufficiently low in order to exclude
them from diagnostic consideration. Only after this is accomplished
will the system discuss its conclusion and recommendations with
the patient.
The discussion that the MDATA system would have with the migraine
headache patient would include the following: Its diagnostic impression,
or its diagnostic impressions in decreasing levels of probability.
Its estimate of the level of probability of migraine. Whether or
not the system feels it has excluded the serious causes of headache
to a level of certainty that satisfies the system. What tests, if
any, should be obtained to confirm or exclude a diagnosis. How soon
to see a physician. What kind of physician to see (e.g., family
practitioner, internist, or neurologist). What kind of information
to bring to the physician when a consultation is obtained. Questions
to ask the physician. The latest treatment for migraine.
Even if the MDATA system 100 cannot determine with sufficient certainty
what is causing the headache, it can still provide patients with
valuable information and advice. For example, the patient may be
told the following: "At this time, the MDATA system is unable
to pinpoint a particular cause of your headache with the degree
of certainty required to make specific recommendations. The MDATA
system, however, suggests a consultation with a neurologist. You
can either call your family practitioner or internist and ask for
a referral. "While you are waiting to be seen by the neurologist,
there are many things that you can do in order to help the physician
diagnose your headache. Many headache experts have found that a
record of when their patients' headaches occur and how bad they
are is very helpful in finding both the cause of the headache as
well as the best treatment. "In order to assist you, the MDATA
system will send you a blank calendar on which you can record the
time and severity of your headaches. In addition, there is space
for you to record what seems to bring on the headaches, makes them
worse, or makes them better. The MDATA system will also send you
a questionnaire to fill out and give to your doctor, containing
a list of questions asked by some of the world's leading headache
experts when they are trying to arrive at a diagnosis." A full
set of instructions will be provided.
The MDATA system is able to customize the information given to
patients to accommodate the individual needs of a sponsoring agency
or group such as a Health Maintenance Organization (HMO) or a Managed
Care Plan. For example, if the system finds that the patient should
see a physician, the MDATA system can determine from a patient's
medical record whether they have an established relationship with
an appropriate specialist. If they do, the specialist's name and
phone number, or a list of participating specialists for their HMO
or Managed Care Plan and any specific instructions, will be given
to the patient with the recommendation to make an appointment within
a specific time frame.
At the conclusion of state 506, the system may or may not have
a reasonably certain diagnosis available. For example, the headache
algorithm provides a diagnosis of migraine in response to a particular
set of patient symptoms. In situations where the MDATA system 100
cannot determine with sufficient certainty what is causing a particular
problem (no diagnosis) or in a situation where a diagnosis is available
but additional information is desirable, e.g., to determine a trend,
a re-enter flag may be set by the system 100. At a decision state
520, the computer 102 determines if re-enter criteria are met for
the current algorithm and patient situation. If so, the computer
sets the re-enter flag at state 522 for this problem so a subsequent
telephone consultation by the patient will allow for additional
information to be added to the patient record by the system in full
knowledge of the previous call. This additional information may
yield a better diagnosis.
If the re-enter criteria were not met, as determined at state 520,
the computer 102 proceeds to a decision state 524 to determine if
the patient desires to hear treatment information for the current
problem. If so, the computer 102 calls the treatment table process
256, which will be described in conjunction with FIGS. 22 and 23.
If the patient does not wish to hear treatment information at this
time, the computer 102 advances to a decision state 528 to determine
if the patient would like to investigate another complaint through
the evaluation process 254. If so, the computer 102 moves via off-page
connector C 530 to state 471 on FIG. 10a to repeat the process 254.
However, if the patient does not wish to pursue another complaint,
the computer returns at state 532 to the top level flow (FIG. 7d).
XI. The Meta Function
Referring now to FIGS. 11a and 11b, the meta function 500 defined
in FIG. 10b will be described. One of the many ways the MDATA system
100 is qualitatively different from prior ways of providing medical
advice is in its use of the "meta function." As mentioned
earlier, "meta" refers to the system's ability to evaluate
the patient's present problem in the context of his or her past
use of the system. The meta function allows the system 100 to make
an inference based upon the number and frequency of previous patient
consultations (or, "medical complaints") and the system's
previous diagnostic assessments. Every patient who has previously
used the MDATA system 100 undergoes the meta analysis.
Input Parameters
The meta function 500 has five input parameters listed at state
540 as follows: i. Problem String (PS)--a four character alphanumeric
string indicating the patient's complaint. The first character of
this string is taken from the Systems column of Table 2. For example,
`N` denotes the nervous system. The second through fourth characters
identify an individual complaint, e.g., "NHDA" identifies
headache. Other examples:
TABLE-US-00010 CCHP Chest Pain NINJ Head injury RINH Inhalation
of toxic fumes
ii. System String (SS)--a four character alphanumeric string that
indicates the affected anatomic system. The first character is taken
from the Systems column of Table 2. The second through fourth characters
are encoded with subsystem identification, or filled with the `*`
wildcard character. For example, "N***" will match all
cases that involve the nervous system. iii. Cause String (CS)--a
ten character alphanumeric string that indicates the cause of the
patient's complaint. The first character is taken from the Causes
column of Table 2. The second through tenth characters are filled
in as needed to more closely specify the cause of interest. A very
broad example is "I*********" which denotes any infection.
Other examples which illustrate how the cause string can become
very specific:
TABLE-US-00011 IV******** Viral infection IB******** Bacterial
infection IBN******* Gram negative bacterial infection IBNM******
Meningococcal gram negative bacterial infection
iv. Beginning Time (T.sub.1)--a timestamp value which indicates
the date and time to be used for the beginning of the time window
under consideration. v. Ending Time (T.sub.2)--a timestamp value
which indicates the date and time to be used for the end of the
time window.
Table 2 lists code letters used as the first letter of the meta
string parameter:
TABLE-US-00012 TABLE 2 Causes Systems A - allergy B - bones/orthopedics
E - environment C - cardiology I - infection D - gastro-intestinal
M - mental G - gynecology P - poison H - hematology (blood) T -
trauma L - larynx (ENT) V - vascular N - nervous X - genetic (chromosomal)
O - opthamology Y - nutritional/metabolic/endocrine R - respiratory
Z - tumor (cancer) S - skin U - urology
A set of meta function analyses involves the identification of
trends in the patient's medical history. For example, if a patient
went to his or her doctor with a history of gradually worsening
headaches (either more painful, more frequent, or both) the physician
would consider this worsening trend in his or her management of
the case. The MDATA system 100 also does this.
Meta Analysis
The algorithm author passes input parameters to the meta function
by using the keyword Meta, followed by the input parameters enclosed
in parentheses. The format for the meta function is: Meta(PS, SS,
CS, T.sub.1, T.sub.2)
Two types of analysis are performed by the meta function: i. Pattern
Matching ii. Time density i. Pattern Matching
In pattern matching analysis, the meta function compares the input
strings with the record fields in the patient's consultation history
database 262. The use of the `*` wildcard character in the input
string will cause the meta function to ignore the corresponding
character position in the record field, thereby enabling the meta
function to examine only the fields of interest. By providing input
strings that are either general or specific, the fields of interest
for analysis are selected. For example, Meta("NHDA", "****",
"**********", T.sub.1, T.sub.2) will cause the meta function
to only consider past consultations for the problem of headache,
regardless of the anatomic system and cause involved.
Through the use of a common syntax, the meta process supports four
types or modes of pattern matching analysis, shown here through
examples: (a) Problem Analysis: Meta("NHDA", "****",
"**********" 06/01/93, 12/31/1993)
Here the meta function will find the number of complaints of headaches
that occurred between Jun. 1, 1993 and Dec. 31, 1993. (b) Anatomic
System Analysis: Meta("****", "D***", "***********",
6/01/93, 12/31/93)
Here the meta function will find the number of complaints involving
the gastro-intestinal system between Jun. 1, 1993 and Dec. 31, 1993.
For example, if a patient consulted the MDATA system 100 once for
abdominal pain, once for vomiting, and once for diarrhea, but each
on a different occasion, the system would recognize that these are
all problems involving the gastrointestinal tract. (c) Cause Analysis:
Meta("****", "****", "IB*********",
06/01/93, 12/31/93)
Here the meta function will find the number of complaints that
were found to be caused by bacterial infection between Jun. 1, 1993
and Dec. 31, 1993. The problems (complaints) caused by bacterial
infection could be in different parts of the body. (d) Combination
Analysis: Meta("NHDA", "****", "I**********",
6/01/93, 12/31/93)
Here the meta function will find the number of complaints of headache
that were found to be caused by infection between Jun. 1, 1993 and
Dec. 31, 1993.
ii. Time Density
If the pattern matching analysis finds at least three matching
records in the patient's consultation history database 262, then
the meta function performs a time density analysis. Time density
refers to the amount of time between each consultation. If the amount
of time between consultations is getting shorter, then the frequency
of consultation suggests that the nature of the complaint is getting
worse. Time density analysis reveals when a problem is getting better,
and when it is getting worse.
Time density analysis uses the meta records that matched the pattern
matching criteria. The computer designates the most recent meta
record `n`, the next most recent is record `n-1`, and the second
most recent is record `n-2`. The time stamp of each meta record
is examined, and two time difference values, X and Y, are determined
according to the formula: X=time difference (n-2, n-1) Y=time difference
(n-1, n)
The ratio of these time differences produces the time density ratio
(TDR): Time Density Ratio=X/Y
The significance of the time density ratio value can be seen through
the following examples:
Example 1: Time between consultations is the same.
TABLE-US-00013 Consultation Date of Consultation n-2 Jun. 01, 1993
n-1 Jun. 08, 1993 n.sup. Jun. 15, 1993
Calculate: X=time difference (06/01/93, 06/08/93)=7 days Y=time
difference (06/29/93, 06/15/93)=7 days Time Density Ratio=7 days/7
days=1.0 Example 2: Time between consultations is getting shorter.
TABLE-US-00014 Consultation Date of Consultation n-2 Jun. 01, 1993
n-1 Jun. 22, 1993 n.sub. Jun. 29, 1993
Calculate: X=time difference (06/01/93, 06/22/93)=21 days Y=time
difference (06/29/93, 06/22/93)=7 days Time Density Ratio=21 days/7
days=3.0 When consultations are occurring at even intervals, then
the TDR value is close to unity. If the frequency of consultations
is decreasing, then the TDR value will be less than 1.0. This would
be typical of a problem that is resolving itself. If the frequency
of consultations increases, then the TDR value will be greater than
one. In the second example, the TDR value of 3.0 indicates a consultation
rate increase of three times during the analysis period. This would
be typical of a problem that is rapidly getting worse. Return Values
After the meta function returns, two local memory variables are
installed in the symbol table and contain the results of the meta
analysis: i. Match Counter (MC)--an integer that contains the number
of meta string matches found within the time window. ii. Time Density
Ratio (TDR)--a floating point value that expresses whether the frequency
of meta string matches is increasing or decreasing. After calling
the meta function, the algorithm author can then make decisions
based upon the values returned in these two memory variables. For
example: Meta("NHDA", "****", "**********",
06/01/93, 12/31/93) If MC>=3 then 100 else 101 The meta function
counts the number of complaints of headache between Jun. 1, 1993
and Dec. 31, 1993. If the number of complaints found (MC) is greater
than or equal to 3, then the evaluation process branches to node
100; otherwise it branches to node 101. Another Example: Meta("****",
"****", "I**********" 06/01/93, 12/31/93) If
TDR>=2.0 then 200 else 201 The meta function is invoked to count
the number of diagnoses attributed to a cause of infection. If the
infection caused diagnoses found have a time density ratio greater
than or equal to 2.0, then the evaluation process branches to node
200; otherwise it branches to node 201. Referring again to FIG.
11a, the meta function 500 initializes at state 540 by popping the
input parameters off the run-time stack and storing them in local
memory variables: PS for problem string, SS for anatomic system
string, CS for cause string, T.sub.1 for the beginning date and
T.sub.2 for the ending date. After the start state 542, the computer
moves to state 544 and initializes the pattern match counter to
zero.
The computer 102 then moves to state 546 wherein it begins the
pattern matching analysis. The computer 102 reads the first meta
record in the patient's consultation history database 262 and moves
to a decision state 548 wherein it examines the record's timestamp.
If the timestamp falls within the time window established by the
input parameters T.sub.1 and T.sub.2, then the computer will move
to state 550; otherwise it moves to state 554. At state 550, the
computer 102 compares the contents of the meta record problem field
with the input string PS, the meta record anatomic system field
with the input string SS and the meta record cause field with the
input string CS. If all these fields match the respective input
strings, then the computer moves to state 552 wherein the match
counter MC is incremented, and then the computer moves to state
554. If there is any mismatch between a meta record field and its
respective input string, then the computer moves to state 554 and
does not increment MC.
At decision state 554, the computer 102 determines if there are
more meta records to process. If so, the computer 102 moves to state
556 wherein it reads the next record and then moves back to state
548 to perform the time window determination. The meta function
iterates through this pattern matching until all of the meta records
have been read. When there are no more meta records to be processed,
the computer moves through off-page connector A 558 to a decision
state 560 on FIG. 11b wherein a determination is made if the value
of the match counter MC is greater than or equal to 3. If so, then
the computer moves to state 564 wherein it begins the time density
analysis.
At state 564, the computer 102 locates the three most recent meta
records whose fields matched the input strings. The computer designates
the most recent meta record `n`, the next most recent is record
`n-1`, and the second most recent is record `n-2`. The computer
then moves to state 566 wherein it calculates X, the time difference
between the timestamps of records n-2 and n-1, and Y, the time difference
between records n-1 and n. The computer 102 then moves to state
568 wherein it calculates the time density ratio (TDR) as the time
X divided by time Y.
If the computer 102 determined at state 560 that there were less
than three matches, then it would move to state 562 wherein it sets
the value of the time density ratio (TDR) to 0.0, which indicates
that the time density analysis could not be performed. At the completion
of establishing the value of TDR at either state 562 or 568, the
computer 102 moves to terminal state 570 wherein the meta process
terminates, returns the match counter MC and the time density ratio
TDR, and returns control to the evaluation process 254 (FIG. 10).
The interaction of the meta analyses for cause and for anatomic
system can be conceptualized by means of a simple geometric metaphor.
Consider a two dimensional array in which the causes of disease
(trauma, infection, allergy/immune, and so forth) are placed on
the "Y" axis, or ordinate, and the anatomic systems of
the body (cardiac, respiratory, nervous system, and so forth) are
placed on the "X" axis or abscissa. Disease then can be
represented by, or is produced at, the intersection of the lines
drawn from the applicable cause and the anatomic system.
As a very simple illustration, consider the two-dimensional array
shown in Table 3 (FIG. 24). The array of Table 3 shows an infection
in the central nervous system represented at the intersection of
the cause of disease (infection) and the anatomic system involved
(the nervous system).
Of course, each cause of disease can be further divided into subcauses.
For example, infection would be broken down (or subdivided) into
bacterial and viral, and bacterial would be further broken down
into gram positive and gram negative, and gram positive would be
further yet broken down into streptococcus, and so on. The anatomic
systems could be broken down in a similar way.
As a patient uses the system 100, and as the meta analyses for
cause and for anatomic system attribute causes to disease processes
and record the anatomic systems involved, a three-dimensional cube
(a "meta cube") is produced composed of these stacked
two-dimensional arrays. The "Z" axis coordinate of each
layer is the time of the patient's consultation obtained from the
system clock (i.e., the moment that the actual intersection of the
cause and anatomic system occurs indicating the diagnosis).
The "meta cube" then represents a summation of the patient's
interaction with the system 100 through time. Although much of the
patient's past history is stored using ICD-9-CM codes as well as
conventional text strings in fields of the patient's medical record,
the "meta cube" technique allows very useful analyses
to be done.
Using the same modeling metaphor, the "Z" axis coordinate
can be used to represent the practice of medicine. Here the "Z"
coordinate is again time, but in this representation, time refers
to a spectrum of ages from pediatrics to geriatrics. Thus, each
coronal plane represents specialties by time, e.g., pediatrics,
adolescent medicine, adult, geriatric. A vertical plane describes
a specialty by anatomic site, such as neurology or cardiology, while
a horizontal plane describes a specialty which practice is bounded
(subsumed) by (on) cause, such as oncology or infectious disease.
To further this metaphor, the rapidity with which intervention is
necessary could be a fourth dimension of the model, and the frequency
of an occurrence of a disease is the fifth dimension. Ethical and
moral responsibility could be a sixth dimension of the model.
Node Map Traverse Analysis
The MDATA system 100 uses a "neural net emulator" program
to determine if patterns produced by patients, as they traverse
down the nodes (creating "node tracks" of the algorithms
in the course of a consultation, may be early predictors of disease.
Somewhat like the "meta cube," the "node tracks"
can be superimposed, rather than stacked, upon one another to create
a two-dimensional array. This time, however, the pattern produced
represents the sum of the patient's previous consultations. In the
MDATA system 100, this is called a "node track traverse analysis."
For example, the MDATA system 100 may discover that the pattern
that is produced when a patient consults the system, at different
times, for episodes of diarrhea, cough, and oral candidiasis may
be predictive of AIDS. Or, that the pattern produced when a patient
consults the system for increased frequency of urination and weight
loss may be predictive of diabetes mellitus.
XII. Mental Status Examination
Referring to FIGS. 16a and 16b, the mental status examination function
508 defined in FIG. 10b will be described. The mental status examination
is a series of questions used to assess the patient's orientation
that allows the system 100 to determine the patient's ability to
respond to questions and to follow advice. The examination is automatically
incorporated into the dialogue of any problem whose presentation
could include an altered level of consciousness. If an operator
or nurse monitoring a telephone consultation at any time feels there
may be a problem with the caller's ability to understand or respond
to questions, the mental status examination may also be manually
invoked.
If the MDATA system 100 determines that the patient is not sufficiently
oriented based on the results of the mental status examination,
the system 100 will ask to speak to someone other than the patient.
If no one else is available, the MDATA system 100 can contact the
emergency medical services system in the patient's area if the system
knows the patient's present geographic position.
Beginning at a start state 680 of FIG. 16a, the computer 102 initializes
the value of a variable Score to be zero. Moving to state 682, the
computer asks the patient Question #1. In the presently preferred
embodiment, the question is "what day of the week is it?"
If the person answers the question correctly, as determined by a
decision state 684, the computer 102 increments the value of Score
by one. After Score is incremented or if the patient did not answer
the first question correctly, the computer 102 moves to state 688
wherein the computer 102 asks the patient Question #2. In the presently
preferred embodiment, the question is "what month of the year
is it?" If the person answers the question correctly, as determined
by a decision state 690, the computer 102 increments the value of
Score by one. After Score is incremented or if the patient did not
answer the second question correctly, the computer 102 moves to
state 694 wherein the computer 102 asks the patient Question #3.
In the presently preferred embodiment, the question is "who
is the President of the United States?" If the person answers
the question correctly, as determined by a decision state 696, the
computer increments the value of Score by one. After Score is incremented
at state 698 or if the patient did not answer the third question
correctly, the computer 102 moves through off-page connector A 699
to a decision state 700 on FIG. 16b.
At decision state 700, the computer 102 compares the score to the
mental status exam threshold at a decision state 700. If the score
meets or exceeds the threshold, then the mental status exam returns
to the evaluation process at state 701 and the diagnostic evaluation
continues. If the score does not reach or exceed the threshold value,
the computer 102 moves to state 702 wherein the operating mode flag
is set to Pending. The MDATA system 100 will then ask, at a decision
state 703, if someone else is available to continue the consultation.
If no one else is available, any new information gathered up to
this point in the session is saved to Pending file 269 at state
704 and then, at state 705, the telephone call with the patient
is transferred to a medical staff person. If someone else is available,
as determined at state 703, and is able and willing to continue
the evaluation process of the patient, as determined at state 706,
the computer 102 asks the person if he or she is a registered assistant
at state 707. If the person responds "yes", the computer
102 invokes the assistant login process 272 at start state 940 on
FIG. 12a. If the person is not a registered assistant, the computer
102 invokes the assistant registration process 274 at start state
1050 on FIG. 14a. After assistant registration or login, the computer
102 moves to terminal state 708 wherein the mental status examination
process terminates and the evaluation process 254 resumes. At the
end of the evaluation process 254, any new information gathered
during the session will be written to the patient's past medical
history file at state 348 or to pending file 269 at state 347 on
FIG. 7d, depending on whether the session continued in real or pending
mode. In the presently preferred embodiment, the value of Score
could be zero, one, two, or three. Of course, in other embodiments,
different questions to be asked of the patient may be utilized in
the mental status exam function 508.
XIII. Semantic Discrepancy Evaluator Routine
Referring to FIG. 17, the semantic discrepancy evaluator routine
(SDER) 510 defined in FIG. 10b will be described. The SDER 510 uses
one or more questions that ask for the same information at different
times, and in other embodiments, in different ways. The answers
given by the patient are then compared within the system 100 to
help determine the mental status of the patient.
Beginning at a start state 712, the computer 102 moves to state
716 and recites a message to the patient. In the presently preferred
embodiment, the message is "remember this three digit number
. . . NUMBER", where the computer generates a random three
digit number (i.e., in the range 100 to 999 inclusive) as NUMBER
which is kept in a session memory variable.
Then, after a predetermined time interval at state 718, the computer
102 moves to state 720 and recites a request of the patient. In
the presently preferred embodiment, the request is "please
tell me the three digit number." The computer 102 then compares
the number given by the patient in response to state 720 against
the NUMBER kept in the memory variable at a decision state 722.
If the numbers match, the computer 102 returns at state 724 with
a status of pass to the evaluation process (FIG. 10b). If the numbers
do not match, the computer 102 returns at state 726 with a status
of fail to the evaluation process. In the presently preferred embodiment,
if the return status of the SDER 510 is "fail", the evaluation
process 254 automatically invokes the mental status examination
function 508.
XIV. Past Medical History Routine
Referring to FIG. 18, the Past Medical History Routine (PMHR) 512
defined in FIG. 10b will be described. The contents of a patient's
past medical history file, which is part of the PMH database 268,
are loaded to the symbol table when the patient logs in to the system
100. During the evaluation process 254, a TEST is performed by the
computer 102 before a particular medical algorithm is initiated
to verify that necessary items are present in the symbol table.
The effect of a negative TEST result is that the system 100 prompts
the patient to provide the missing past medical history information
via the PMHR 512.
The PMHR 512 uses an input parameter "condition label"
(L) as indicated at State 740. The "Condition label" is
unique, e.g., PMHRLTB1 corresponds to the first PMH object tested
in the croup (RLTB) algorithm: diagnosis for croup in children.
The label is passed so that PMHR 512 knows what questions to ask.
The ability of the system 100 to ask a past medical history question
in the middle of the evaluation process 254 is a feature that saves
the patient from having to answer the entire PMH questionnaire during
the registration process. The Boolean result, or scalar value, is
stored in the symbol table under this label (PMHRLTB1), and the
algorithm can use it in decision making, e.g., If PMHRLTB1=True
Then 4310 Else 4320.
Beginning at a start state 742, the computer 102 moves to state
744 and prompts the patient for the missing medical condition data.
Moving to state 746, the computer 102 repeats the information provided
at state 744 and asks the patient if the repeated information is
correct. Moving to a decision state 748, the patient responds by
indicating whether the repeated information is correct. If the data
is not correct, the computer 102 proceeds to state 750 to determine
if the patient would like to attempt the data entry step again.
If so, the computer 102 loops back to state 744 and prompts the
patient for the data again. If not, the computer 102 returns at
state 754 to the evaluation process (FIG. 10b).
If the newly-entered data is correct, as determined at state 748,
the computer 102 advances to state 752 and installs the condition
label (L) and the data value in the symbol table for the patient.
The computer 102 then returns at state 754 to the evaluation process
254.
XV. Physical Self Examination
Referring to FIG. 19, the Physical Self Examination function 514
defined in FIG. 10b will be described. A physical examination can
actually be done by the patient under the direction of the MDATA
system 100. The MDATA system 100 is designed to function primarily
based upon responses to carefully crafted questions, i.e., history,
and physical findings elicited from the patient. There are times,
however, when the addition of certain laboratory tests can increase
the accuracy of the diagnosis as well as help determine the appropriate
treatment recommendations. For this reason, a MDATA system Home
Diagnostic and Treatment Kit is available for use by patients. If
the patient has the Home Diagnostic and Treatment Kit, including
visual field cards, Snelling chart, and possibly the MDATA system's
"tele-stethoscope" to assess intracranial or carotid bruits,
this information will be used in the diagnostic process as well.
The MDATA system 100 is also able to play tones of different frequencies
and intensities to emulate audiometric testing for hearing acuity.
This allows, for example, the MDATA system 100 to detect the unilateral
decrease in hearing caused by an acoustic neuroma.
Beginning at a start state 770, the computer 102 branches to one
or more physical self examination procedures depending on the current
problem and what equipment if any is available for use by the patient.
These procedures include: home diagnostic tests 772, vital signs
774, observable physical signs 776, clinical sound recording 778,
and tele-stethoscope 780.
A variety of home diagnostic tests 772 are available for use by
the patient. New advances in biotechnology, including a new generation
of urine dipsticks such as a "Multistix 8 SG" produced
by Ames and monoclonal antibody tests such as "ICON.RTM. STREP
B" produced by Hybritech.RTM., allow an entire spectrum of
laboratory tests to be performed at home by the patient under the
direction of the MDATA system. For example, urine dipsticks can
be used to check for blood, nitrites, leukocytes, or leukocyte esterase
indicating cystitis or a bladder infection.
In order to use much of the monoclonal antibody technology, however,
a small amount of blood must be obtained by using a fingertip lancet.
This is already successfully being done by diabetics at home who
use a glucometer to measure their blood sugar after pricking their
finger to get a small sample of blood.
The MDATA system Home Diagnostic and Treatment Kit also contains
equipment to allow the patient, or someone else, to measure the
patient's vital signs 774. A blood pressure cuff and thermometer
are included with instructions for their use as well as instructions
to measure pulse and respiratory rate.
The patient may be directed by the system 100 to observe various
physical signs 776. For example, a headache patient will be asked
to palpate their temporal artery area, and to look at themselves
in the mirror to identify the ptosis and tearing of a cluster headache
or to identify the steamy cornea that may occur with acute narrow
angle glaucoma.
As an example of how the MDATA system Home diagnostic and Treatment
Kit could be helpful, consider a woman who (using the MDATA system's
urine pregnancy test based on ICON.RTM. II HCG ImmunoConcentration.TM.
Assay, produced by Hybritech.RTM.) finds out that she is pregnant.
This is her first pregnancy. Later, when consulting the system for
headache, a urine dipstick indicates protein in her urine and the
measurement of her vital signs shows a significant rise in her blood
pressure. This is a classic presentation of preeclampsia.
Instead of going to a doctor's office, patients could also use
the MDATA system's Home Diagnostic and Treatment Kit to collect
samples at home and then send them to a designated lab for analysis
as needed. This saves time for the patient and is especially useful
if the patient has difficulty in traveling. Costs should also be
minimized in this type of laboratory analysis.
The MDATA system 100 records clinically relevant sounds 778 of
a patient such as the cough of bronchitis, the seal bark cough of
croup or the inspiratory stridor of epiglottitis. These sounds are
digitized and stored in the patient's medical record. Then, using
the re-enter feature of the system 100, the system can monitor,
for example, a patient's cough over time to be sure that the cough
is resolving as it should.
The general concept of recording and analyzing a cough is disclosed
in the article A microcomputer-based interactive cough sound analysis
system, C. William Thorpe, et al., published in Computer Methods
and Programs in Biomedicine, 1991. The cough sound analysis system
describes the filtering, amplification, recording, and software
processing of a cough sound. The MDATA system 100 uses the telephone
handset microphone in conjunction with an amplifier to procure the
clinical sounds. These sounds are then transmitted to the system
100 where they are filtered, digitized using VP board 122 and recorded
to a file in the patient medical history database 268 on the hard
drive 152 (FIG. 1).
The MDATA system 100 is building a library of clinical sounds that
allows patterns or profiles to be developed that relate the wave
form of the clinical sound to the probability of a particular diagnosis.
For example, the MDATA system 100 could compare the cough of a patient
to the sound library to see if the cough of the patient is similar
to those that eventually have been diagnosed as lung cancer.
In addition, the patient's record of the pronunciation of his or
her name may be periodically recorded and compared to previous recordings.
This allows the MDATA system 100 to potentially detect and evaluate
the hoarseness that could be produced by a nodule on the patient's
vocal cords.
A "tele-stethoscope" 780 is a device that allows the
sounds a physician would hear through a stethoscope to be transmitted
over the telephone. The tele-stethoscope 780 is functionally similar
to that described in the 1992 Arthur D. Little report entitled "Telecommunications:
Can It Help Solve America's Health Care Problems?". The tele-stethoscope
780 permits the MDATA system 100 to greatly expand the spectrum
of its sound analyses to include heart murmurs, the bruits of intracranial
aneurysms, breathing sounds like the wheezes of asthma and the rales
of congestive heart failure, or even the bowel sounds of an intestinal
obstruction.
There is more information in clinical sounds than can be represented
by a two-dimensional pattern matching model. Transforms, e.g., Fourier,
are used to shift different aspects of sounds into domains that
can be quantified. The sounds are then pattern matched using an
n-dimensional array. Consider a simple two dimensional array where
time is represented on the X coordinate and amplitude is measured
on the Y coordinate. For example, a cough may be recorded at two
times several days apart. In this example, the computer 102 superimposes
the waveform from one cough upon the other cough. The non-overlapping
parts of the pattern both above and below represent the difference
in the domain being measured between the two sounds. The area under
these two curves is integrated to obtain the area. The sum of the
areas of the two curves represents the difference between the two
sounds in the domain being measured. The resultant area is then
subjected to one or more sensitivity factors which are discussed
hereinbelow. Hence, the more sensitive the system, the sooner it
makes a match.
In a similar way, a sound pattern may be considered with time on
the X coordinate and frequency on the Y coordinate. The same methodology
is used to quantify the differences between the two curves. Thus,
in a similar way, all aspects of sound can be measured.
In this pattern matching scheme, different weights are given to
the different aspects of the sound depending upon which clinical
sound is measured. In most sounds, the amplitude and frequency are
the most important aspects. The weight or the relative importance
of an aspect is different for each of various clinical sounds, such
as heart murmurs, bruits, wheezes, coughs, stridor and so forth.
When value(s) from any of the procedures 772 780 are procured by
the system 100, the computer 102 moves to state 782, recites the
value and requests the patient to confirm the value. If the patient
indicates that the value is correct, as determined at a decision
state 784, the computer 102 proceeds to state 786 and installs the
value into the symbol table associated with the current patient.
If the value is not correct, as determined at decision state 784,
the computer 102 proceeds to state 790 to determine if the patient
would like to try providing the value again. If so, the computer
102 loops back to the beginning of the function 514. If the patient
does not wish to try again, as determined at state 790, or if state
786 is completed, the computer 102 returns at state 788 to the evaluation
process (FIG. 10b).
Referring to FIG. 20, the Patient Medical Condition Routine 516
defined in FIG. 10b will be described. In the course of executing
a particular medical algorithm in the evaluation process 254 (as
shown at state 506), the computer 102 may request additional medical
condition information of the patient. This information reflects
the current condition of the patient, which is in contrast to the
information requested by the past medical history routine 512 (FIG.
18) for past history information. The states 800 through 814 of
the routine 516 are essentially the same as states 740 through 754
of routine 512, except that in routine 512 the condition label (L)
denotes a value for which a past medical history question is to
be asked during the evaluation process, while in routine 516 the
condition label denotes a new value desired by the algorithm. Therefore,
states 800-814 are not further described herein.
XVI. Symptom Severity Analysis
Referring now to FIGS. 10a, 10b, and 21, the symptom severity analysis
function 518 defined in FIG. 10b will be described. A review and
further description of the re-enter feature, which is associated
with symptom severity analysis, is also provided here.
An important feature of the MDATA system 100 is its ability to
follow or monitor a patient over time. If the MDATA system 100 is
in the process of diagnosing a patient's complaint but is not certain
what action should be taken (states 520 522 of FIG. 10b), system
100 may ask the patient to re-enter the system at a designated time,
usually within a few hours.
When the patient calls the MDATA system at the designated time,
the system takes the patient through the initial problem screening
questions (state 483 of FIG. 10a) in order to exclude those problems
that require immediate medical attention. The system detects that
the patient is a re-enter case (state 490 of FIG. 10a), and then
determines the re-entry point in the evaluation process based upon
the patient's previous interaction with the system (state 492 of
FIG. 10a). For example, if the MDATA system established a diagnosis
of migraine, that is, if both the probability of migraine and the
probability of confirmation of migraine reached threshold values,
the patient would not repeat the diagnostic process, which is the
usual case.
Occasionally, however, a patient for whom a diagnosis has not been
established will be asked to re-enter the system 100. This patient
is again asked the diagnostic screening questions, in addition to
the initial screening questions (state 306 of FIG. 7a) and problem
screening questions (state 483 of FIG. 10a). If the MDATA system
100 is not able to establish a diagnosis for a re-enter patient,
he or she is referred to a physician for further evaluation.
In addition to the re-enter feature, the MDATA system 100 has the
capability to call patients back in order to monitor their progress.
The same trending methodologies are used regardless of who initiates
the call, i.e., the system or the patient. Using this capability,
the MDATA system 100 can provide regular or periodic monitoring
of elderly patients in their homes as well as inform patients when
a new therapy becomes available.
Many problems for which the MDATA system 100 offers advice have
absolute thresholds for the initial quantization of the severity
of a symptom. For example, chest pain that is described by a patient
as being 10 on a 10-scale of severity, would reach the problem-specific
initial symptom-severity threshold and would mandate a consultation
with a physician.
Interestingly, with headache, an initial severity characterized
by the patient as 10 on a 10-scale would not, in itself, necessarily
require an immediate consultation with a physician. If, in addition,
the headache came on suddenly and, as was mentioned earlier, was
described as the worst headache of the patient's life, the MDATA
system 100 would consider this to be suggestive enough of a subarachnoid
hemorrhage to advise an immediate consultation with a physician.
Continuing in the headache example, after a re-enter patient with
an established diagnosis is asked the initial and problem screening
questions, the MDATA system 100 again assesses the severity of the
patient's headache. Reassessing the severity of the headache, by
having the patient re-enter the system, establishes two points of
reference. The system 100 is now able to analyze any changes in
the level of severity as well as calculate the rate of change in
severity over time.
The symptom severity analysis function 518 has a Number of Points
(N) as an input parameter as indicated at state 830. Number of Points
refers to the points of reference established during the initial
consultation for a particular problem and during subsequent re-enter
consultation(s). Beginning at a start state 832, the computer determines
the value of (N), i.e., the number of reference points, at a decision
state 834. If it is determined that N=2, the computer 102 moves
to state 836 to compute the slope of a line connecting the two reference
points using standard mathematical techniques. Proceeding to state
838, a variable named Power is set to be one because only two reference
points are used at state 836. The computer 102 returns at state
840, with output parameters Slope and Power as determined by function
518, to the evaluation process (FIG. 10b).
Using the returned Slope and Power parameters in the evaluation
process 254, if the MDATA system 100 determines that the severity
of the headache, for example, is increasing too rapidly, that is,
if a slope of the line connecting two points on a graph of the severity
reaches a set threshold, system 100 will make an appropriate recommendation.
If the MDATA system 100 finds that the severity of the headache
is staying the same or is getting worse but is doing so at a relatively
slow rate, it may ask the patient to re-enter the system a second
time (i.e., for a third consultation), usually within a shorter
period of time. The third consultation gives the MDATA system 100
three points of reference from which to trend the severity of the
headache. Thus, when the function 518 is called by the evaluation
process, the value of (N) is three, as determined at state 834,
and the computer 102 branches to state 844. At state 844, the computer
102 determines the slope and power of a line connecting the three
reference points. The presently preferred embodiment uses the well-known
Runge-Kutta method, which is a numerical approximation technique
for solving differential equations. Other embodiments may use other
well-known, standard curve fitting functions at state 844.
If the system 100 determines that yet one or more additional consultations,
i.e., beyond three consultations, are desired, e.g., to establish
a trend with certainty, it will again request the patient to re-enter
the system at a later time. In this situation, the three most recent
reference points are used in the calculation at state 844.
The system 100 then performs a "sequential symptom-severity
slope analysis" to determine if the symptom is getting worse
too rapidly as follows. The slopes of the lines connecting the first
and second point, the second and third point, and then the first
and third point are calculated. If any of these reach a problem-specific
threshold, the appropriate recommendation is given.
If the sequential symptom-severity slope analysis does not reveal
the need to seek medical attention, then the MDATA system 100, in
addition to calculating the rate of change in the severity of the
symptom with respect to time (the slope analysis), now calculates
the rate of change of the rapidity with which the headache is getting
worse. This is the first derivative.
Table 4 (FIG. 25) illustrates this relationship. Time maps onto
the "X" axis and the symptom's severity maps onto the
"Y" axis. Note that a line connecting these three points
forms a gently sloping straight line. The MDATA system 100 using
this data determines that, although the symptom is getting worse,
it is doing so in an arithmetical or linear way. That is, although
the severity of the symptom is increasing, the symptom's rate of
change is not increasing.
In contrast, a line connecting the three points on the graph of
Table 5 (FIG. 26) forms a sharply upturned curve. The MDATA system
100 using the data of Table 5 determines that, not only is the symptom
rapidly getting worse, but more significantly, the rate at which
the symptom is getting worse is also increasing. In the MDATA system
100, this analysis is termed an "exponential symptom-severity
filter." All patients who re-enter the system a second time
are subjected to this analysis.
It is important to note that the severity of a problem, e.g., a
headache, is not necessarily related to the seriousness of the underlying
cause. The MDATA system 100 is programmed such that when any symptom
gets rapidly worse, medical intervention is frequently advised as
necessary. This concept is valid for many symptoms.
Returning to the symptom severity analysis function 518 (FIG. 21),
if the function 518 is called with N=0, or N=1, the computer branches
to state 842. At state 842, the Slope and Power parameters are set
to zero, and the computer 102 returns these parameters at state
840 to the evaluation process (FIG. 10b). The values set at state
842 essentially flag an error condition that is acted on by the
evaluation process 254.
XVII. Treatment Table
Referring to FIG. 22, the Treatment Table process 256 defined in
FIG. 7d will be described. The MDATA system 100 is modularized in
its approach to diagnosis and treatment. In medicine, diagnosis
simply means figuring out what is causing the problem, and treatment
refers to what action should be taken once the cause of the problem
is known.
Diagnosis is composed of history, physical examination, imaging
studies, and laboratory tests. Again, history is by far the most
important factor in making the diagnosis. In fact, in medical school,
students are taught that if they don't have a good idea of the diagnosis
by the end of the history, they are doing something wrong.
The treatment side of medicine is conceptually different from diagnosis
in that, while the basic principles of making the diagnosis remain
the same, treatment is continually changing. Treatment is fundamentally
a "look-up" table with the diagnosis, age and sex on the
left and the most current treatment on the right as shown in Table
6. Or, treatment can be thought of like the cubbyholes or boxes
of a post office. Each individual box holds the treatment for a
given disease. The information given is age and sex specific. The
contents of the box are constantly changing, but the location of
the box does not. For example, what is thought to be the best antibiotic
to treat meningitis in a two-year-old child could literally change
from week to week as more antibiotics are developed and approved
or more controlled studies are published.
TABLE-US-00015 TABLE 6 Simplified TREATMENT TABLE Example Diagnosis
Treatment meningitis in a antibiotic of choice two-year old child
as of current date
The MDATA system 100 maintains a treatment table that can be updated
instantaneously to provide the most current treatment recommendations.
The treatment table can be directly accessed by patients who already
know their diagnosis. For example, asthma patients can consult the
system as often as they wish to see what the absolute latest treatment
is for their condition. In fact, links are maintained between the
treatment table and the patient medical history files 268. In this
way, when a new treatment is introduced for any of the ICD-9-CM
codes listed in the MDATA system 100, patients can be contacted
and asked to either call the system 100 back at their convenience
or have the MDATA system 100 fax or mail the information to them.
The MDATA system 100 can also notify patients' doctors when a new
treatment is identified.
The concept of using a table is also helpful with regard to two
aspects of the diagnostic process that often do change: the imaging
modality of choice (like X-ray, Computerized Tomography (CT), Magnetic
Resonance Imaging (MRI)), and the laboratory test(s) of choice.
Therefore, the MDATA system 100 also maintains a table for imaging
modality of choice as well as laboratory test(s) of choice in the
work-up or diagnosis of a particular complaint. By modularizing
these aspects of the diagnosis, as new imaging techniques, like
Positron Emission Tomography (PET) scanning, and new laboratory
tests, like recombinant DNA technology, are discovered, only the
tables have to be altered, not the medical algorithms themselves.
The treatment table will be further described in a general way
as process 256 in FIG. 22. The treatment table process 256 begins
at start state 860 and proceeds to state 862 wherein the computer
prompts the caller to choose a treatment selection method: i. Treatment
selected from layered menus, or ii. Treatment selected via direct
entry of a catalog number.
The first selection method entails the use of the menu-driven treatment
selection process 864 which will be described hereinbelow in conjunction
with FIG. 23. The second selection method at state 866 uses a treatment
table catalog message number. This catalog is part of the patient
information package, a section of which appears in Table 7. The
treatment table catalog is organized by anatomic area and diagnosis,
and when applicable, by age and gender. After the patient selects
a catalog number, the computer 102 stores the selection in a memory
variable `M`. As an alternate selection method, the system 100 allows
the patient to directly enter the ICD-9-CM code for their problem.
In this case, the computer 102 will look-up the ICD-9-CM code in
an internal cross-reference table to identify the catalog number,
and set the memory variable `M` to this catalog number.
TABLE-US-00016 TABLE 7 Portion of Treatment Table Catalog NEUROLOGY
Diagnosis Message Epilepsy 1101 Meningitis 2 years old & younger
1201 over 2 years old 1202 Depression Male Under age 50 1301 50
years and older 1303 Female Under age 50 1302 50 years and older
1304
Once the value of the memory variable `M` is established by process
864 or state 866, the computer 102 moves to state 868 and plays
treatment message `M` to the patient. At the conclusion of treatment
message playback, the computer 102 moves to a decision state 870.
At state 870 the computer 102 checks for existence of society message
`M`. The society message category contains information about organizations
that assist patients with a particular disease. If the society message
`M` does not exist, the computer 102 moves to a decision state 874.
Otherwise, the computer 102 will move to state 872 wherein it plays
society message `M` to the patient. At the end of the society message
`M`, the computer moves to state 874.
At state 874, the computer 102 checks for the existence of an over-the-counter
(OTC) message `M`. The OTC message category contains information
about generally available over-the-counter medications and home
treatment for a particular diagnosis. If the OTC message `M` does
not exist, the computer moves to state 878. Otherwise, the computer
102 moves to state 876 wherein it play OTC message `M` to the patient.
At the end of the OTC message `M`, the computer 102 moves to state
878.
At state 878 the computer 102 plays a terminal menu to the patient
which allows the patient to either select another treatment, or
to exit from the treatment table process 256. If the patient wishes
to hear another treatment message, the computer 102 moves back to
the treatment selection method menu state 862. If the patient wishes
to exit the treatment table process 256, the system moves to state
880, wherein the treatment table process 256 terminates and returns
to the top level flow (FIG. 7d) at state 344.
An example of the treatment, society and OTC messages for epilepsy
are given in Table 8. Note that since the OTC message is empty,
the computer 102 would skip over the OTC message playback and proceed
directly to the terminal menu.
TABLE-US-00017 TABLE 8 Treatment Table Messages for Epilepsy Treatment
Message As of Dec. 20, 1993, according to Emergency Medicine: Concepts
and Clinical Practice, Third Edition, by Drs. Rosen, Barkin, et.
al., pages 1800 and 1801, the initial treatment of generalized tonic-clonic
seizures, i.e., grand mal seizures, is as follows: After efforts
to discover and treat acutely correctable causes like hypoglycemia,
the following pharmacologic agents are indicated: 1. Intravenous
administration of lorazepam, with a loading dose of 0.1 mg/kg and
an infusion rate not to exceed 2 mg/min. Which is usually followed
by: 2. Intravenous administration of phenytoin, with a loading dose
of 15 to 18 mg/kg and an infusion rate not to exceed 0.75 mg/kg
per minute. If lorazepam is not effective, and in those individuals
allergic to phenytoin: 3. Intravenous administration of phenobarbital,
with a loading dose of 8 to 20 mg/kg and an infusion rate not to
exceed 0.75 mg/kg per minute. If the above is not successful: 4.
A neuromuscular blocking agent like pancuronium, with an intra-
venous dose of 0.03 to 0.1 mg/kg. 5. Intravenous administration
of paraldehyde, with a loading dose of 0.1 to 0.15 ml/kg, diluted
with saline to a 4% to 6% solution and slowly infused over 1 hour.
Society Message "For further information on epilepsy, contact:
Epilepsy Foundation of America 1828 L Street, N.W., Suite 406 Washington,
D.C. 20036 (202) 293-2930 In addition to the national headquarters,
there are 100 local chapters. The San Diego chapter can be contacted
at (619) 296-0161." OTC Message None.
Referring now to FIG. 23, the menu-drive treatment selection process
864 defined in FIG. 22 will be described. The menu-driven treatment
selection process 864 begins with start state 890 and proceeds to
state 892 wherein the computer 102 recites an area menu to the patient
and requests selection of one area. The complete menu is not shown
in state 892. The areas are arranged by anatomic system. For example,
if a patient has epilepsy, the patient can simply select this from
the anatomic system menu for the neurological system.
Based on the patient's selection, the computer 102 branches to
a selection area menu state, such as neurological area menu state
894, wherein the computer 102 recites a list of diagnoses to the
patient and requests selection of a diagnosis. In some cases the
diagnosis is further subdivided by gender, age or both gender and
age. At state 904, for example, for a diagnosis of meningitis, the
computer 102 would prompt the patient to select from a secondary
menu between a treatment for a child two years old or younger and
a treatment for somebody over two years old. Then, based on the
patient's selection, the computer 102 sets a memory variable `M`
to the value of the selected diagnosis message number at state 908
or 910. State 906 is another example secondary level menu which
has four choices based on gender and age. These four choices are
associated with four states, 912, 914, 916, 918, wherein the computer
102 sets the memory variable `M` to the value of the diagnosis message
number that was selected at state 906. After the catalog number
has been stored in memory variable `M`, the computer 102 moves to
return state 923 wherein the menu-driven treatment selection process
terminates and returns control to the treatment table process 256.
Area 2 menu 896 and AreaN menu 898 are indicative of menus similar
to menu 894 but for different anatomic systems. Menu 896 and 898
may have secondary menus, similar to menus 904 and 906 under menu
894. Then, states 920 and 922 are indicative of the computer 102
setting memory variable `M` to the value of the diagnosis message
number selected from the parent menu 896 or 898, respectively.
XVIII. The MDATA System Paradigm
The MDATA system paradigm is based on several fundamental principles.
They are as follows: Centralization of medical information Accessibility
of medical information Modularity of medical information Modifiability
of the system.
As mentioned earlier, one of the purposes of the MDATA system 100
is to bring together highly qualified medical experts, encode their
knowledge in a central location, and make this information available
to everyone.
Although the issue of accessibility has been discussed several
times, it is important to understand its significance. Accessibility
in the MDATA system 100 refers both to the way in which the medical
information can be retrieved from the system 100 by non-medically
trained personnel as well as to the need for people everywhere to
easily and promptly obtain medical information. By using the already
established worldwide telecommunications network, the MDATA system
100 can provide universal and nearly instantaneous access to high
quality, 100%-consistent medical advice.
In the MDATA system 100, the concepts of modularity and modifiability
are inextricably intertwined. Modularity is the key to the MDATA
system's ability to provide patients with the most current medical
information available. The MDATA system's modular design and object
oriented techniques allow the individual components of the system
to be modified or updated without generating a ripple effect on
other information in the system 100.
In contrast, the print media suffers from an inability to quickly
adapt to changing information. Once a book or journal is published,
it cannot be modified until its next publishing date. The MDATA
system 100, however, can be modified within hours of a new discovery
in medicine. Easy modifiability is another way in which the MDATA
system 100 is qualitatively different from previously published
algorithms.
Once the medical algorithms for the MDATA system 100 are written
and programmed, they can then be continuously updated and refined
as advances in medicine are made. Unfortunately, physicians today
are simply not able to keep up with the explosion of new medical
information and technology. This ability to nearly instantaneously
modify the MDATA system 100 is a powerful feature of the system.
It is presently possible for a computer to search the world's medical
literature daily. Any articles pertaining to a particular topic
can automatically be requested and the information used to update
the system.
In addition, the MDATA system 100 is currently using optical character
recognition technology to digitize its medical database. Then, using
indexing techniques, the MDATA system 100 is able to search for
and retrieve any information desired. For example, the system can
search for the character string "headache" and retrieve
any amount of surrounding text or graphic information. This information
is then collected, collated, printed and referred to the physician(s)
maintaining the headache algorithm. This process will become easier
as more of the world's medical literature is digitized.
Global Factors--Sensitivity and Selectivity
Another way in which the MDATA system is modifiable is in its use
of global sensitivity/selectivity factors. As with every decision,
there is always a balance to be achieved between risk and benefit,
and so with the MDATA system 100. One of the questions the MDATA
system 100 tries to answer is whether the patient needs to be seen
immediately by a physician. This leads to this discussion about
sensitivity and selectivity.
Sensitivity and selectivity are statistical terms that refer to
how accurately a decision can be made. In this case, sensitivity
refers to the number of patients which the MDATA system 100 did
not think needed to be seen by a physician but that actually did.
If the program were to be so sensitive that no disease process
that eventually required meaningful physician intervention would
be treated at home (no false negatives), then every single complaint
would necessitate a visit to the doctor, which is a useless system.
On the other hand, too selective a system (no false positives) i.e.,
no unnecessary visits to the doctor's office, would necessitate
that an attempt be made at home treatment for every complaint, which
is a useless and dangerous system.
So again, a balance must be reached between these two ends of the
spectrum. To achieve this, the sensitivity/selectivity ratio of
the entire MDATA system 100 can be changed by setting or tuning
a plurality of sensitivity factors. These sensitivity factors affect
the following functions: meta thresholds, reenter horizon threshold,
frequency of call back, symptom-severity filters, sequential slope
filters, exponential symptom-severity filters, and probabilities
of diagnoses in the treatment table. In addition, as in the headache
example, the scoring of the screening questions already weighted
is modulated or modified by the sensitivity factors.
Experience from the regionalization of trauma centers in this country
shows an interesting trend over time with respect to sensitivity
and selectivity. It has been shown that the inverse relationship
between sensitivity and selectivity, when plotted over time, yields
a sinusoidal wave form in which the amplitude of the wave form gradually
decreases with time as the system is "fined tuned" as
shown in Table 9 (FIG. 27). The MDATA system's sensitivity factors
are designed to do just that, i.e., fine tune the system over time
to find the right balance between sensitivity and selectivity.
In addition to the use of global factors, the MDATA system 100
maintains what are termed "emergency filter response sets."
When a patient replies "yes" to any of the problem screening
questions, the recommendation or message that follows is called
an emergency filter response or "EFR." The EFR sets are
modularized so that the system can customize the message that the
patient hears. This allows the system 100 to match the EFR sets
to the desired level of sensitivity or selectivity as well as provide
information specific to an HMO or Managed Care Plan.
System Sensitivity Factors
There are ten sensitivity factors that affect threshold determination
in the MDATA system 100: S1=system-wide (usually established by
the system administrator and affects the entire MDATA system) S2=the
anatomic system of the body involved (e.g., nervous system in headache
example) S3=cause (e.g., infection causes meningitis) S4=problem
specific (established by the algorithm author at the beginning of
an algorithm) S5=question specific (within a particular algorithm)
S6=organizational specific (e.g., HMO, hospital) S7=patient specific
S8=a reserved sensitivity factor for later use S9=a reserved sensitivity
factor for later use S10=a reserved sensitivity factor for later
use
Initially, the sensitivity factors have a value of 1.0. The sensitivity
factor's value is usually inversely proportional to sensitivity;
i.e., if the value is decreased, sensitivity increases.
The sensitivity factors are applied to the threshold constant value
in the relational expression component of an IF-Then or If-Then-Else
statement of a medical algorithm. For example, let's assume that
the system 100 is in the meningitis algorithm and that a temperature
greater than 102 degrees will trigger a recommendation to go to
a hospital. An example of a threshold calculation without sensitivity
factors follows: If temp>102 then X else Y where X denotes the
recommendation to go to the hospital and Y denotes a different branch
point. Following is the same example, but including sensitivity
factors: If temp>(102*S1*S2*S3*S4*S5*S6*S7*S8*S9*S10) then X
else Y
The use of the sensitivity factors permits anticipation of change.
Tuning the initial product of the sensitivity factors from "1.00"
to "0.95" would decrease the temperature at which the
system recommends a trip to the hospital. Each threshold calculation
or other use of the sensitivity factors may use any number of (e.g.,
two factors) and any combination of the factors. Additionally, any
combination of factors may be modified from the initial 1.0 value
in any particular threshold calculation.
Age criteria is also modified by use of the sensitivity factors.
For example: If Age>45*S1*S4 then X else Y.
Examples of areas the system 100 could be tuned follow: Anatomic
system (e.g., cardiovascular)--the system is missing too many heart
attacks; Cause (infection)--the system is missing too many injuries
(trauma); Problem specific (e.g., headache)--the headache algorithm
is missing too many cases of meningitis or subarachnoid bleeds;
Question specific (each question in an algorithm can be modified)--this
would change the "weight" of a question in a series of
weighted questions like the migraine screening questions; Patient
specific--one patient might want to be VERY careful while another
might say, "in general I don't go to the doctor until I'm really
sure something is wrong with me"; Organizational (e.g., Kaiser
patients)--Kaiser hospital management may say that the system is
missing too many cases of meningitis and may request to be more
careful with their patients (send them in with a lower temperature).
The sensitivity factors affect the following system 100 functions:
(a) Re-enter Feature--the sensitivity factors affect the re-enter
horizon, i.e., the amount of time after which the system 100 considers
a repetition of the same complaint to be a new problem. If sensitivity
increases, the re-enter horizon becomes sooner. (b) Meta Function--the
sensitivity factors affect the matching and time density ratio thresholds.
By reducing the values of the system-wide and problem sensitivity
factors, e.g., from 1.0 to 0.9, the matching threshold and the time
density ratio are decreased: Example 1 Without Sensitivity factors:
Meta("NHDA", "****", "**********"
06/01/93, 12/31/93) If MC>=3 then 100 else 101 Example 1 with
Sensitivity factors: Meta("NHDA", "****", "**********",
06/01/93, 12/31/93) If MC>=(3*S1*S4) then 100 else 101 Example
2 Without Sensitivity factors: Meta("****", "****",
"I*********", 06/01/93, 12/31/93) If TDR>=2.0 then
200 else 201 Example 2 With Sensitivity factors: Meta("****",
"****", "I**********" 06/01/93, 12/31/93) If
TDR>=(2.0*S1*S4) then 200 else 201 Thus, there is no necessity
to change the algorithms themselves. In other words, the factors
can be modified rather than changing the algorithms. (c) Problem
Questions--To take the headache example previously used, the sum
of the scores of the screening and confirmation questions (and sometimes
the questions themselves) is multiplied by the sensitivity factors.
The questions are also weighted, of course, depending upon how important
each question is to the diagnosis. The sum of the weighted scores
is compared against the threshold value that will result in either
making the diagnosis of say migraine (in response to the migraine
screening questions) or confirming the diagnosis of migraine in
response to the migraine confirmation questions. Thus, if we wanted
to increase the sensitivity of diagnosing subarachnoid hemorrhage,
we would not have to write another algorithm, but rather, simply
multiply the screening and confirmation scores by the sensitivity
factors. For example, if the threshold for the MDATA system 100
to make a diagnosis of subarachnoid hemorrhage based on the sum
of the weighted subarachnoid screening questions threshold is set
at, say 75%, then that percentage of the sensitivity variable would
make this diagnosis with a smaller score and, thus, pick up more
cases. Thus, individual diagnoses within an algorithm can be "tuned"
independently, and in some cases, this even applies to the individual
questions themselves. (d) Symptom Severity and Symptom Severity
Trend Analysis--the sensitivity factors alter the absolute value,
the first, second and third slope thresholds. With increased sensitivity,
a more gently sloping line triggers an earlier medical evaluation.
In the algorithm, when the system 100 makes use of any quantitatable
parameter to make a decision, all of these are joined, influenced
or multiplied by the sensitivity factors. As a very simple example,
if the MDATA system 100 would normally make a recommendation, partly
based on the age of the patient (e.g., if you are male and you are
over 50 and . . . ), the decision can be triggered if the patient
is 49 or 48 and so on. (e) Home Diagnostic and Treatment Kit--if
the patient has a MDATA system treatment kit or a blood pressure
cuff, the level at which a fever or blood pressure effects a decision
can be changed. (f) Mental Status Examination--the mental status
examination can be modified at a system, or problem (algorithm)
level. (g) Clinical Sound Library--the pattern matching process
(as in the clinical sound library) is quantifiable by modifying
the sensitivity factors.
XIX. Video Imaging Of the Patient
There are four main types of video imaging: static black and white,
static color, video black and white and video color. Each of these
main types is now discussed.
Images as basic as static black and white images can provide useful
information to the system 100. Static black and white imaging is
used with neural net pattern matching. This process permits analyzing
for example, facial features to aid in the detection of certain
diseases, such as the characteristic facies of Cushing's syndrome
or the exophthalmos of Graves disease.
Color static imaging allows color frequency analysis to detect
diseases that are not as readily detected with static black and
white imaging, such as cyanosis of respiratory failure or the scleral
icterus of hepatitis. Color thus provides an incremental benefit
in the level of disease detection.
Real time black and white video imaging allows for the evaluation
of physical signs such as pupillary responses, extra ocular muscle
function, lid lag, and nystagmus. Cranial nerve function can be
remotely evaluated, along with, for example, the distinction between
central and peripheral VII nerve function.
Color video imaging, especially using fiber optics, adds much more
capability in the evaluation of a patient's condition. For example,
color video imaging is very useful in evaluating capillary refill
or monitoring the response of a patient with cyanosis to supplemental
oxygen. Another embodiment of the system 100 may employ inexpensive
laser sources to perform real time holographic imaging.
XX. Benefits of the MDATA System
It is rare when the humanitarian and entrepreneurial interests
of a venture overlap. The confluence of purpose that exists in the
MDATA system is striking. It is a "win-win" proposition
from every perspective.
Not only will the MDATA system 100 substantially reduce the overwhelming
costs of our current health care system, but for the first time
in history, every person can have access to high quality, 100%-consistent
and affordable medical advice and information. No matter from what
perspective one views the MDATA system 100, its benefits are substantial.
The health care consumer obviously gains the most. Now, whenever
he or she has a medical problem, or any member of their family,
an immediate consultation can be obtained. The knowledge that the
best health care information and medical advice is only a telephone
call away can assuage the anxiety of everyone from new mothers to
elderly patients confined to their homes.
By endorsing the MDATA system 100, federal, state and local governments
could discharge their obligation to provide a universal and affordable
level of health care for all of their citizens. In addition, the
MDATA system 100 helps care for patients who cannot pay, thus relieving
primary care physicians of the necessity to provide care without
reimbursement. For the first time, Health Maintenance Organizations
and Managed Care Plans will be able to effectively screen patients
by telephone in order to ensure that patients are best matched with
the services they need.
Specialists can use their talents, not on the repetition of familiar
rituals, but will be free to concentrate on those more challenging
problems that cannot easily be resolved by the MDATA system 100.
They will also benefit from an increased number of patient referrals
as well as having a well-constructed patient history when a consultation
is sought.
Physicians themselves can access the MDATA system 100 in order
to stay informed about new information and technological advances
in the medical field. This is particularly true with the treatment,
imaging, and laboratory test databases.
Medical information is a continually renewable resource because
it is not consumed in its dissemination. The opportunity exists,
through the MDATA system 100, for the United States to provide much
needed medical information to the world and, at the same time, bring
capital into this country. In the process, this country could maintain
its leadership in innovation, technology, and software development.
The United States and the world are facing a health care crisis
so monumental that it is difficult to comprehend. There are diseases
that threaten our very survival as a species. All of us know the
apprehension and bewilderment we feel when an illness strikes. When
this occurs, we need answers to specific medical questions, answers
that are absolutely up-to-date, instantly available, and affordable.
The key is information: information about prevention, early detection
of disease, and about its most efficient treatment. The MDATA system
100 can provide this information through the simple use of the telephone,
to nearly every inhabitant of the planet. In addition, the MDATA
system 100 converts and explains complicated medical terminology
and concepts into language easily understood by everyone.
People do not have to be ill to consult the MDATA system 100, just
curious. Patients do not have to schedule appointments, they can
simply pick up the telephone. Although many patients will later
be seen by a physician, the MDATA system 100 can provide immediate
help for everyone. The MDATA system 100 at once establishes egalitarian
access to health care information. Although many patients in this
country receive state-of-the art medical care, there is a large
segment of the population that is deprived of one the most basic
health care and medical information. The MDATA system 100 begins
to close this enormous gap.
The MDATA system 100 begins to effect a restructuring of the health
care delivery system in which both health care consumers and providers
participate in the improvement of the system itself. The MDATA system
100 and its patients will be in partnership to provide the most
current, economical, and concise treatment available. The upside
potential is unlimited. Whether one believes health care is a right
or a privilege, there can be no doubt that it is fundamentally necessary.
Whether one believes we have a civic responsibility or a moral obligation
to care for one another, it must be done. The fundamental simplicity
of the structure of the MDATA system 100 belies its power as a highly
useful tool in the delivery of health care.
XXI. Optional System Configuration
A second embodiment of the MDATA system entails a major shift of
how the questions and responses are delivered to the patient. Rather
than the use of a telephone, the voice processing and voice response
technology, the system software is published via media such as floppy
disks, CD ROM, or PCMCIA cards for use on a patient's personal computer.
This second embodiment is referred to as the screen version or the
(Stand-Alone) SA-MDATA system. The computer could be, for example,
a desktop computer, a laptop or notebook computer, or a handheld,
pen-driven computer. The system questions are displayed on a display
screen that is part of the computer or is connected to the computer.
The patient uses a keyboard or a pointing/writing device connected
to the computer to respond to the questions. The patient files are
maintained and updated within the computer or on removable storage
devices. The diagnosis, advice, and treatments can be displayed
on the screen and also printed in hardcopy form on a printer (if
available). New versions of the SA-MDATA system are either mailed
to subscribers are available via modem. These new versions may include
updates of the treatment table for new treatments. Another embodiment
of the SA-MDATA system may include using specialized receiver devices
that receive encoded FM signals on a demand basis when an event
(a new treatment) triggers the device, such as described in U.S.
Pat. No. 5,030,948.
A unique and separate authoring language (called File Output or
FO) was used to develop the medical algorithms used in the screen
version embodiment of the system 100. Through the use of FO, the
contents of text files are presented online to users, and then the
users respond to questions and directions issued by the text files.
FO is designed as a typical, generalized authoring language, in
which commands are embedded into text files (herein called FO files)
to perform specific screen and keyboard functions. FO files are
in effect programs written in the FO "language" that communicate
(via FO) with the user online.
FO adds no text of its own. In fact, FO does not need to know what
text file content it is executing. The programmer or author of a
FO file is in complete control of the text content and the sequence
in which it is presented. Using the various commands described in
the Authoring Language Syntax, the author can display text, format
the screen, ask the user questions, input responses from the user,
select different text files for execution, and generally control
and direct the entire session.
This version of FO is intended as a development version that gives
the user much freedom at the keyboard. The user can interrupt a
presentation and edit the FO file being presented. The assumption
here is that the user is in fact the author or an alpha tester charged
with verifying and correcting file content.
A FO file is any standard sequential ASCII text file with variable-length
lines terminating with a Carriage Return (ASCII 13). Any line with
a period in column one is treated as a command. A line without a
leading period is treated as a print command.
The FO program processes a FO file by reading it one line at a
time into memory. If the line is a text line, it is printed and
the next line is loaded. If the line is a command line, the command
is executed. If the command involves a wait on the user (such as
a .M command), FO continues loading the FO file behind the scenes
until it has been completely loaded. In this manner, FO executes
the FO file as it is loading it. Once loaded, the FO file remains
entirely in memory.
The system software for the screen version embodiment is written
in Borland Turbo Pascal version 3.0. A second version of the system
software for the screen version embodiment of the system 100 is
written in Microsoft G.W. Basic and is run in interpretive mode.
In yet other embodiments, other databases/files or algorithms can
be used. The general system, method and procedures would remain
the same. For example, a specialty field such as sports medicine
could be added to the system.
The MDATA system 100 described herein finds application in many
environments, and is readily adaptable for use therein. For example,
the system finds use in any application that is step-oriented and
can be algorithmically described. For example, the system could
give car diagnostic services over the phone to a caller. Then, when
the car is brought to a service facility for repairs (treatment),
the caller will be informed and have a good idea of what the problem
is and probable repairs will be. Accordingly, the claims are to
be interpreted to encompass these and other applications of the
invention within their scope and are not to be limited to the embodiments
described herein.
XXII. Summary of Advantages of the Present Invention
One of the main problems of the health care crisis is the limited
access to health care information when it is needed. The MDATA system
provides up-to-date medical information and advice that is instantly
available twenty-four hours a day. The advice that is given is 100%
consistent.
The quality of the advice is much better if a physician can stop,
research, and anticipate all possible causes of a problem and then
systematically go about dealing with all of these possible causes.
In medical practice, a physician just does this from memory.
No humans are necessary to actually give the medical advice. The
MDATA system is automated which helps to bring down the cost of
health care.
An exact record of the questions asked and the answers given is
stored in the patient's database. The MDATA system time-and-date
stamps the responses to the questions (as transaction records) so
that an exact reconstruction of the patient's interview(s) can be
generated for use by a physician or other health care professional.
The system also keeps a record of what version of an algorithm has
been consulted as well as the sensitivity factor set for that consultation.
At the conclusion of the interaction, the MDATA system can tell
the patient how long the consultation has taken and what charges
have been incurred, if any.
When possible, the MDATA system 100 takes into account the past
medical history of the patient, especially those pieces of information
learned from past consultations with the MDATA system 100, before
advice is given. In addition, the advice given is different depending
upon the age and sex of the patient. The "meta" functions
provide another advantage by allowing the MDATA system 100 to evaluate
a problem in the context of the patient's prior consultations with
the system.
While the above detailed description has shown, described and pointed
out the fundamental novel features of the invention as applied to
various embodiments, it will be understood that various omissions
and substitutions and changes in the form and details of the device
illustrated may be made by those skilled in the art, without departing
from the spirit of the invention.
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