REMOTE CLINICAL CARE SYSTEM

• US 20130226601A1
• Filed: 08/24/2012
• Published: 08/29/2013
• Est. Priority Date: 08/24/2011
• Status: Abandoned Application

• Current Assignee: Acupera, Inc.
• Original Assignee: Acupera, Inc.
• Inventors: Razmi, Ronald M., Hubbard, Kelvin
• Application Number:
  US13/594,667
• Publication Number:
  US 20130226601A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

An automated system and method provides real time disease-specific guidance to both providers and patients to enable accurate diagnosis and treatment. Content based on knowledge of specific diseases and patient history is used to determine most likely diagnoses remotely. This system uses information provided by a patient'"'"'s medical records (EHR/EMR), remote monitoring devices, results of laboratory tests, diagnostic tests, and other available information.

Claims

1. A method utilizing an interface and a processor for determining a probable diagnosis for a patient, said method comprising:

(a) providing to the processor a matrix of possible diagnoses and presenting symptoms, wherein each presenting symptom has an assigned conditional probability value for each possible diagnosis;

(b) providing to the processor a list of pre-existing diagnoses for the patient, wherein the processor generates a patient-adjusted matrix of possible diagnoses and presenting symptoms having patient-adjusted probability values based upon the patient'"'"'s pre-existing conditions and risk factors;

(c) answering on the interface one or more questions to determine if the patient has a presenting and additional symptoms and device readings;

(d) determining the patient-adjusted probability value for each possible diagnosis based upon the presence or absence of the presenting symptom as determined in step (c);

(e) calculating an accumulated patient-adjusted probability value for each possible diagnosis by adding the value determined in step (d) to any previous values determined in step (d); and

(f) assigning a probable diagnosis to the patient if an accumulated patient-adjusted conditional probability value determined in step (e) exceeds a pre-determined diagnostic threshold value;

or

(g) repeating steps (c) through (e) if no accumulated patient-adjusted probability value determined in step (e) exceeds a pre-determined threshold value or all questions have been exhausted.

2. A method as in claim 1, wherein the interface is selected from a group consisting of a tablet, a kiosk, a computer, a smart phone, and a telephone.

3. A method as in claim 1, wherein the processor comprises a central processor or a group of distributed processors.

4. A method as in claim 1, wherein the interface and processor are networked from remote locations.

5. A method as in claim 1, wherein the interface and the processor are located in an integral unit, wherein at least one of the matrix of possible conditions and presenting symptoms and the list of patient pre-existing conditions is maintained at a remote location.

6. A method as in claim 1, further comprising prioritizing the order of questions asked in step (c) based on the patient'"'"'s pre-existing conditions.

7. A method as in claim 1, further comprising prioritizing the order of questions asked in step (c) based upon the probability values for each condition determined in step (d) when steps (c) through (e) are being repeated in accordance with step (g).

8. A method as in claim 1, wherein at least some of the questions are answerable with a yes or no.

9. A method as in claim 1, further comprising inputting presenting test data into the interface wherein step (d) relies on both the presenting symptoms and on the presenting test data to determine the patient-adjusted probability value for each condition.

10. A method as in claim 1, further comprising answering on the interface one or more additional questions to determine severity of a condition after a probable diagnosis has been assigned in step (f).

11. A method as in claim 1, wherein the diagnoses include at least some conditions selected from the group consisting of COPD, congestive heart failure (CHF), diabetes, asthma, depression, and hypertension.

12. A method as in claim 1, wherein the presenting symptoms include at least some symptoms selected from the group consisting of chest pain, trouble breathing, presence of a cough, green sputum, radiating arm pain, and fever.

13. A method as in claim 1, wherein the test data include at least some test data selected from blood pressure, heart rate, temperature, glucose level.

14. A system for determining a probable diagnosis for a patient, said system comprising:

a database providing a matrix of conditional probability values for each of a plurality of possible diagnoses based upon each of a multiplicity of presenting symptoms;

a database providing a list of pre-existing diagnoses for the patient;

an interface;

a processor which communicates with the interface and receives data from the matrix database and the list database, wherein the processor is configured to perform the following steps;

(a) generate a patient-adjusted matrix of patient-adjusted conditional probability values based upon the patient'"'"'s pre-existing conditions and risk factors;

(b) generate and present question(s) on the interface, wherein answer(s) input on the interface determine if the patient has a symptom;

(c) determine the patient-adjusted probability value for each possible diagnosis based upon the presence or absence of each symptom;

(d) calculate an accumulated patient-adjusted probability value for each possible diagnosis by adding the value of all of the patient-adjusted conditional probability values that have been determined for that possible diagnosis; and

(e) assign a probable diagnosis to the patient when an accumulated patient-adjusted probability value exceeds a predetermined diagnostic threshold value;

or

(f) repeat steps (b) through (d) if no accumulated patient-adjusted probability value exceeds a predetermined threshold and additional questions which have not been previously answered are available to ask the patient.

15. A system as in claim 14, wherein the interface is selected from a group consisting of a tablet, a kiosk, a computer, a smart phone, and a telephone.

16. A system as in claim 14, wherein the processor comprises a central processor or a group of distributed processors.

17. A system as in claim 14, wherein the interface and processor are networked from remote locations.

18. A system as in claim 14, wherein the interface and the processor are located in an integral unit, wherein at least one of the matrix of possible diagnoses and symptoms and the list of patient pre-existing conditions and risk factors are maintained at a remote location.

19. A system as in claim 14, wherein the processor is further configured to prioritize the questions asked in step (c) based on the patient'"'"'s pre-existing diagnoses and risk factors.

20. A system as in claim 14, wherein the processor is further configured to prioritize the questions asked in step (c) based upon the conditional probability values for each diagnosis determined in step (d) when steps (c) through (e) are being repeated in accordance with step (g).

21. A system as in claim 14, wherein the processor is further configured to input presenting test data into the interface wherein step (c) relies on both the symptoms and on the presenting test data to determine the patient-adjusted conditional probability value for each possible diagnosis.

22. A system as in claim 14, wherein at least some of the questions are answerable with a yes or no.

23. A system as in claim 14, wherein the processor is further configured to answer on the interface one or more additional questions to determine severity of a condition after a probable diagnosis has been assigned in step (f).

24. A system as in claim 14, wherein the diagnoses include at least some conditions selected from the group consisting of COPD, congestive heart failure (DHF), diabetes, asthma, depression, hypertension.

25. A system as in claim 14, wherein the presenting symptoms include at least some symptoms selected from the group consisting of chest pain, trouble breathing, presence of a cough, green sputum, radiating arm pain, fever.

26. A system as in claim 14, wherein the test data include at least some test data selected from blood pressure, heart rate, temperature, glucose level.