Automated diagnostic system and method including encoding patient data

• US 6,746,399 B2
• Filed: 11/05/2002
• Issued: 06/08/2004
• Est. Priority Date: 02/14/2000
• Status: Expired due to Term

• Current Assignee: Healthways SC, LLC (Warner Bros. Discovery, Inc.)
• Original Assignee: First Opinion Corporation (Tivity Health, Inc.)
• Inventors: Iliff, Edwin C.
• Primary Examiner(s): Hindenburg, Max F.
• Assistant Examiner(s): Astorino, Michael C
• Application Number:
  US10/289,533
• Publication Number:
  US 20030073887A1
• Time in Patent Office: 581 Days
• Field of Search: 600/300-301, 128/904, 128/920-925, 128/897, 128/898, 706/2, 706/45
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 70/60 relating to pathologies
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
• CPC Class Codes: Y10S 128/904 Telephone telemetry
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

Structure-based processing includes a method of diagnosing diseases that works by arranging diseases, symptoms, and questions into a set of related disease, symptom, and question structures, such as objects or lists, in such a way that the structures can be processed to generate a dialogue with a patient. A structure-based processing system organizes medical knowledge into formal structures and then executes those structures on a structure engine to automatically select the next question. Patient responses to the questions lead to more questions and ultimately to a diagnosis. An object-oriented embodiment includes software objects utilized as active, intelligent agents where each object performs its own tasks and calls upon other objects to perform their tasks at the appropriate time to arrive at a diagnosis. Alternative symptoms, synergies, encoding of patient responses, multiple diagnostic modes, disease profiles or timelines, and the reuse of diagnostic objects enhance the processing of the system and method.

Claims

1. A computerized medical diagnosis system, comprising:

a) means for defining a spectrum of terms representative of a subjective description for an aspect of a medical symptom;

b) means for presenting the spectrum of terms to a patient during a diagnosis session;

c) means for selecting a term from among the spectrum of terms;

d) means for repeating a)-c) for other aspects of the medical symptom;

e) means for encoding the selected terms; and

f) means for indexing a database of diseases with the encoded terms thereby diagnosing a disease.

2. A computerized medical diagnosis system, comprising:

a) means for defining a spectrum of terms representative of a subjective description for a selected aspect of a medical symptom;

b) means for defining diagnostic weights for each term of the spectrum;

c) means for presenting the spectrum of terms to a patient during a diagnostic consultation;

d) means for receiving a selected term from among the spectrum of terms;

e) means for corresponding the selected term to a weight;

f) means for applying the weight corresponding to the selected term to a diagnostic score so as to diagnose a medical condition;

g) means for repeating the acts a)-f) for other aspects of the medical symptom so as to receive other selected terms; and

h) means for encoding the selected terms into a code.

3. The system defined in claim 2, additionally comprising:

means for repeating the acts c)-h) at a predetermined later time;

means for analyzing a change of the code over time; and

means for assigning a weight for the change of the code for the medical symptom over time.

4. The system defined in claim 3, wherein the predetermined later time is later in the diagnostic consultation.

5. The system defined in claim 3, wherein the predetermined later time is during a subsequent diagnostic consultation.

6. The system defined in claim 3, additionally comprising means for storing the code over time in a patient medical history.

7. The system defined in claim 6, additionally comprising means for retrieving past codes from the patient medical history.

8. The system defined in claim 3, wherein the means for analyzing the change of the code over time includes means for computing a synergy based on the codes.

9. The system defined in claim 8, wherein the means for computing a synergy based on the codes includes means for determining a slope, trend, area or volume of a plot of the codes over time.

10. The system defined in claim 2, wherein the aspects are selected from a group comprising quality, severity, location, size, symmetry, timing, localizability, and migration.

11. The system defined in claim 10, wherein the quality aspect includes the terms:

pinprick, knifing, tearing, fullness, tightness, and pressure.

12. The system defined in claim 10, wherein the severity aspect includes terms defining a magnitude range.

13. A method of developing a data structure of aspects of a medical symptom for use in diagnosis of medical conditions, the method comprising:

identifying a plurality of aspects of a particular medical symptom;

defining a spectrum of terms for each aspect of the plurality of aspects;

assigning a corresponding diagnostic weight for each term of each spectrum of terms; and

storing the aspects, the spectrum of terms for each aspect and the corresponding diagnostic weights in a data structure for use in diagnosis of diseases associated with the medical symptom.

14. The method defined in claim 13, wherein the aspects are identified from a group comprising quality, severity, location, size, symmetry, timing, localizability, and migration.

15. A computerized medical diagnosis system, comprising:

a computerized device;

a data structure for a spectrum of terms representative of a subjective description for each of a plurality of selected aspects of a medical symptom, wherein each aspect has a different spectrum of terms and wherein each term of the spectrum has a corresponding diagnostic weight; and

a diagnosis program configured, during a diagnostic consultation, to;

a) present a spectrum of terms for one aspect of the medical symptom to a patient,

b) receive a selected term from among the spectrum of terms,

c) apply a weight from the data structure corresponding to the selected term to a diagnostic score so as to diagnose a medical condition,

d) repeat a)-c) for other aspects of the medical symptom so as to receive other selected terms, and

e) encode the selected terms into a code.

16. The system defined in claim 15, wherein the diagnosis program is further configured to:

repeat a)-e) at a predetermined later time;

analyze a change of the code over time;

assign a code change weight for the change of the code for the medical symptom over time; and

apply the code change weight to the diagnostic score.

17. The system defined in claim 16, wherein the predetermined later time is later in the diagnostic consultation.

18. The system defined in claim 16, wherein the predetermined later time is during a subsequent diagnostic consultation.

19. The system defined in claim 16, wherein the diagnosis program is further configured to store the code over time in a patient medical history.

20. The system defined in claim 15, wherein the aspects are selected from a group comprising quality, severity, location, size, symmetry, timing, localizability, and migration.