System and method for a patient-specific and optimization of medical therapy by simultaneous symbolic reasoning in all clinical dimensions

• US 8,032,394 B1
• Filed: 11/07/2008
• Issued: 10/04/2011
• Est. Priority Date: 06/12/2002
• Status: Active Grant

• Current Assignee: Humana Incorporated
• Original Assignee: Anvita, Inc. (Humana Incorporated)
• Inventors: Ghouri, Ahmed
• Primary Examiner(s): O'Connor; Gerald J.
• Assistant Examiner(s): Pass; Natalie
• Application Number:
  US12/267,338
• Time in Patent Office: 1,061 Days
• Field of Search: 705/2, 705/3, 704/9, 600/300
• US Class Current: 705/2
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• 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 70/20 relating to practices or guidelines
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage

Abstract

A particular system and methodology by which a drug or medical therapy regimen is defined for any particular patient in a manner that takes not only a drug or therapy'"'"'s effectiveness into account, but also an entire spectrum of relevant clinical dimensions so as minimize the possibility of harmful interactions while simultaneously maximizing pharmacotherapy potential. Furthermore, as a consequence of its construction, no medically relevant rule can be overlooked by the reasoning system. The system and methodology utilizes a computerized dimensional indexing system implementing multiple databases and performs therapeutic determinations by symbolic structural reasoning with respect to database elemental indices.

Claims

1. A computerized method for providing multidimensional medical decision support, the method comprising:

defining and storing, in a computer database, a set of input variables for a patient being evaluated, each input variable associated to a corresponding relevant clinical dimension for establishing a diagnosis for a patient, the relevant clinical dimensions are a chief complaint, a history of present illness, a past medical history, a past surgical history, a medication, an allergy, a vital sign, a physical exam (PE) and a diagnostic test;

defining and storing, in the computer database, interdimensional relationships between and among the relevant clinical dimensions so as to define at least drug-disease, and drug-allergy testing interaction relationships;

entering, into the computer, particular values for the input variables in the course of examining a patient;

selecting at least a portion of the set of input variables from the group of relevant clinical dimensions consisting of a current complaint dimension, a medical history dimension, a surgical history dimension, a current medications dimension, a laboratory results dimension, a social history dimension, and a family history dimension;

the computer automatically identifying particular ones of the interaction relationships specific to the particular patient being examined, wherein the particular ones of the interaction relationships are identified to a physician during the course of the examination;

displaying the particular ones of the interaction relationships specific to the particular patient during the examination of the patient by the physician; and

the computer automatically inferences in real time and presents treatment choices that are simultaneously adjusted, in a patient and context-specific fashion, for interaction safety, therapeutic efficacy, economic factors, and correct dosing.

2. The method according to claim 1, further comprising:

selecting at least an additional portion of the set of input variables from the group of relevant clinical dimensions consisting of a diagnostic test findings dimension, a vital signs dimension, a physical examination findings dimension, and a diagnostic possibility dimension.

3. The method according to claim 2, further comprising:

topologically mapping the inter-relationships between and among the relevant clinical dimensions; and

assigning a severity score to each mapped association between and among the clinical dimensions so as to define a strength of each mapped association.

4. The method according to claim 3, further comprising:

defining a set of output variables for a patient being evaluated, each output variable associated to a corresponding relevant intervention action for establishing a treatment regime for a patient; and

wherein the interaction relationships identified to the physician automatically inform an intervention action in accordance with the existence and strength of a mapped association between clinical dimensions.

5. The method according to claim 4, wherein the relevant intervention actions are selected from the group consisting of counseling, pharmacotherapy, procedural intervention, diagnostic testing, and specialist referral.

6. The method according to claim 5, wherein the chief complaint dimension defines a differential diagnosis selected from a recognized standardized medical reference of clinically relevant diagnoses.

7. The method according to claim 6, wherein the recognized standardized medical reference comprises the ICD9.

8. The method according to claim 7, wherein ICD9 or equivalent disease codes are automatically entered into an electronic patient medical record.