Automated diagnostic system and method including disease timeline

• US 20020016529A1
• Filed: 02/14/2001
• Published: 02/07/2002
• Est. Priority Date: 02/14/2000
• Status: Active Grant

• Current Assignee: Healthways SC, LLC (Warner Bros. Discovery, Inc.)
• Original Assignee: First Opinion Corporation (Tivity Health, Inc.)
• Inventors: Iliff, Edwin C.
• Granted Patent: US 6,569,093 B2
• Time in Patent Office: Days
• 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 method of automatically diagnosing a medical condition by use of a predicted timeline of symptoms, the method comprising:

generating a plurality of timelines which are each representative of a typical course of a disease in terms of how and when the symptoms of the disease typically arise, vary, and subside over time;

automatically asking one or more questions of a patient so as to elicit a symptom indicative of a chief complaint;

automatically receiving answers from the patient in response to the questions;

automatically identifying a disease corresponding to the chief complaint;

correlating the chief complaint to a timeline for the disease;

automatically asking one or more questions to elicit the presence and time of a first significant symptom on the timeline for the disease;

adding an incremental weight to a cumulative score for the disease if the first significant symptom is established; and

establishing the diagnosis when the cumulative score exceeds a predetermined threshold.

2. The method defined in claim 1, wherein the chief complaint includes a symptom and a severity for the symptom.

3. The method defined in claim 1, wherein each disease is associated with one timeline.

4. A method of automatically diagnosing a medical condition by use of a predicted timeline of symptoms, the method comprising:

generating a plurality of timelines which are each representative of a typical course of a disease via a characteristic pattern of symptom magnitudes over time; and

automatically selecting a particular disease based on a pattern of symptom magnitudes associated with a patient being similar to the timeline associated with the particular disease.

5. The method defined in claim 4, wherein each disease is associated with one timeline.

6. The method defined in claim 4, additionally comprising automatically asking questions of the patient.

7. The method defined in claim 6, additionally comprising creating a timeline of symptom magnitudes indicative of the patient based on answers to the questions.