Computer architecture and process of patient generation, evolution, and simulation for computer based testing system using bayesian networks as a scripting language

• US 7,024,399 B2
• Filed: 10/08/2002
• Issued: 04/04/2006
• Est. Priority Date: 04/05/1999
• Status: Expired due to Term

• Current Assignee: American Board of Family Medicine, Inc.
• Original Assignee: American Board Of Family Practice, Inc.
• Inventors: Hagen, Michael D., Sumner, Walton II
• Primary Examiner(s): DAVIS, GEORGE B
• Application Number:
  US10/265,599
• Publication Number:
  US 20030130973A1
• Time in Patent Office: 1,274 Days
• Field of Search: 706/45, 706/46, 706/47
• US Class Current: 706/45
• CPC Class Codes: G09B 7/00 Electrically-operated teaching apparatus or devices working with questions and answers mechanically operated G09B3/00; computing arrangements G06F
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/00 ICT specially adapted for the handling or processing of medical references

Abstract

A method and system for patient generation and evolution for a computer-based testing system and/or expert system. One or more belief networks, which describe parallel health state networks are accessed by a user or a computer. A knowledge base, at least in part, is scripted from the one or more belief networks by the computer. A model patient at least in part, is instantiated by the computer from the scripted knowledge base. Optionally, the model patient is evolved by the computer in accordance with the parallel health state networks and responsive to a received course of action.

Claims

1. A system communicatable with a computer network, comprising:

a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said processor, said instructions including;

(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;

(b) accessing at least one first belief network which describes each of the plurality of parallel health state networks;

(c) accessing at least one second belief network which describes rates of progression within and/or between said plurality of parallel health state networks, and to describe task factors that affect the rates of progression;

(d) accessing at least one third belief network which supports plan critiques of queries of and treatment prescribed by the user;

(e) receiving patient;

(f) instantiating a virtual patient having characteristics consistent with the received patient data and based, at least in part, on the at least one first belief network and the at least one second belief network;

(g) generating one of a query to the user for a specific medical finding concerning the actual patient, and a course of action based, at least in part on the virtual patient and the at least one third belief network;

(h) receiving the specific medical finding from the user responsive to the generated query; and

(i) evolving the virtual patient in accordance with at least one of the at least one first belief network and the at least one second belief network, and responsive to the received specific medical finding.

2. The system according to claim 1, wherein the instructions further comprise:

(j) repeating the instructions (g) through (i) until the user has dispensed treatment of the actual patient based on the generating course of action; and

(k) storing the evolved virtual patient for subsequent access by the user.

3. The system according to claim 2, wherein the instruction further comprise:

(l) repeating the instructions (i) through (k) upon each said subsequent access by the user at least until the treatment of the actual patient is completed.

4. A system communicatable with a computer network, comprising:

a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said processor, said instructions including;

(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;

(b) accessing at least one first belief network which describes each of the plurality of parallel health state networks;

(c) accessing at least one second belief network which describes rates of progression within and/or between said plurality of parallel health state networks, and to describe task factors that affect the rates of progression;

(d) accessing at least one third belief network which support reveal structures to limit display of patient test data to patient test data specifically requested by the user;

(e) accessing at least one fourth belief network which supports plan critiques of queries of and treatment prescribed by the user;

(f) scripting a knowledge base from the at least one first belief network and the at least one second belief network;

(g) instantiating a model patient based, at least in part, from the scripted knowledge base;

(h) receiving one of a course of action and a query for a specific medical finding concerning the model patient from the user responsive to the instantiated model patient;

(i) displaying, if the query is received, the specific medical finding to the user based at least in part on the at least one third belief network, and repeating the instruction (h); and

(j) evolving the model patient in accordance with at least one of the at least one first belief network and the at least one second belief network and responsive to the received course of action.

5. The system according to claim 4, wherein the instructions further comprise:

(k) repeating the instructions (h) through (j) until the user has completed treatment of the model patient.

6. The system according to claim 5, wherein the instruction further comprise:

(l) generating an optimum combination of treatment and queries based on the at least one fourth belief network and the instantiated model patient; and

(m) evaluating the query and the treatment by the user in comparison to the generated optimum combination of treatment and queries.

7. A computer network appliance comprising:

a thin client programmably connected via a computer network to a single web hosting facility, the single web hosting facility including a server communicatable with a user via the computer network, said server being in communication with a processor and a computer-readable medium storing instructions executable by said precessor, said instructions including;

(a) accessing a plurality of parallel health state networks describing at least one of a plurality of primary networks defining disease evolutions, a plurality of secondary networks defining risk factors affecting progression through a primary network of the plurality of primary networks, and a plurality of tertiary networks defining at least one of causal probabilistic medical complications attributed to at least one stage in the primary network and medical complications attributed to management of the at least one stage;

(b) accessing at least one first belief network, which describes each of the plurality of parallel health state networks;

(c) accessing at least one second belief network, which describes rates of progression within and/or between said plurality of parallel health state networks, and describes task factors that affect the rates of progression;

(e) accessing at least one third belief network, which supports plan critiques of queries of and treatment prescribed by the user;

(f) receiving patient data;

(g) instantiating a virtual patient having characteristics consistent with the received patient data and based, at least in part, on at least one of the at least one first belief network and the at least one second belief network;

(h) generating one of a query to the user for a specific medical finding concerning the actual patient, and a course of action based, at least in part on the virtual patient and the at least one third belief network;

(i) receiving the specific medical finding from the user responsive to the generated query; and

(j) evolving the virtual patient in accordance with at least one of the at least one first belief network and the at least one second belief network, and responsive to the received specific medical finding.

8. The system according to claim 7, wherein the instructions further comprise:

(k) repeating the instructions (h) through (j) until the user has dispensed treatment of the actual patient based on the generating course of action; and

(l) storing the evolved virtual patient for subsequent access by the user.

9. The expert system according to claim 8, wherein the instruction further comprise:

(m) repeating the instructions (h) through (l) upon each said subsequent access by the user at least until the treatment of the actual patient is completed.

10. A method for educating or evaluating a user, comprising the steps of:

instantiating a virtual patient for display to the user, the virtual patient including a plurality of health states;

receiving from the user at least one of a query for a medical finding concerning the instantiated virtual patient and a course of action; and

one of;

generating, responsive to the received query, a specific medical finding at least in part from a first causal probability network defining a health state reveal structure corresponding to the instantiated virtual patient;

generating, responsive to the received query, an indication of an inappropriate query, based, at least in part, on a second causal probability network defining a medical practice management plan; and

generating, responsive to the received course of action, an indication of an inappropriate course of action, based, at least in part, on the second causal probability network.

11. The method according to claim 10, wherein the medical practice management plan includes healthcare provider approved medical finding queries.

12. A computer system for evaluating or educating a user, compromising:

a processor;

a computer-readable medium storing instructions executable by said processor, said instructions including at least one of;

generating a virtual patient based, at least in part, on at least one first belief network, which describes a plurality of parallel health state networks;

generating the virtual patient based, at least in part, on at least one second belief network, which describes rates of progression within and/or between the plurality of parallel health state networks; and

generating patient test data concerning the virtual patient, based, at least in part, on at least one third belief network, which supports reveal structures to limit display of the patient test data to patient test data specifically requested by the user.

13. The computer system according to claim 12, wherein said computer system is communicatable with a user via a computer network.

14. A computer system for evaluating or educating a user, compromising:

a processor;

a computer-readable medium storing instructions executable by said processor, said instructions including at least one of;

generating a virtual patient based, at least in part, on at least one causal probabilistic network, which describes rules of progression within and/or between the plurality of parallel health state networks; and

generating patient test data concerning the virtual patient, based, at least in part, on the at least one causal probabilistic network, which supports reveal structures to limit display of the patient test data to patient test data specifically requested by the user.

15. The computer system according to claim 14, wherein said computer system is communicatable with a user via a computer network.

16. A computer system for evaluating or educating a user, compromising:

a processor,

a computer-readable medium storing instructions executable by said processor, said instructions including at least one of;

generating a virtual patient based, at least in part, on a plurality of parallel health state networks;

generating the virtual patient based, at least in part, on rates of progression within and/or between the plurality of parallel health state networks; and

generating patient test data concerning the virtual patient, based, at least in part, on reveal structures limiting display of the patient test data requested by the user.