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

• US 7,809,585 B1
• Filed: 01/23/2003
• Issued: 10/05/2010
• 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:
  US10/350,483
• Time in Patent Office: 2,812 Days
• Field of Search: 705/2, 705/3, 600/300, 707/100, 707/104.1, 707/5, 707/9, 707/3, 707/102, 706/15, 706/46
• US Class Current: 705/3
• 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 method for developing an effective medical treatment/therapy regimen for a patient, the method comprising:

establishing, on a computer, a clinically relevant diagnosis for the patient, the diagnosis relevant to the patient'"'"'s chief complaint;

querying, using the computer, a database for a set of recommended intervention action established on the basis of the clinically relevant diagnosis of the patient;

receiving, on the computer, the set of recommended intervention actions based on the database query, the actions ranked in order of preference for treatment of a condition indicated by the clinically relevant diagnosis of the patient;

analyzing, on the computer, the set of recommended intervention actions in accordance with one or more clinical decision support dimensions, wherein the clinical decision support dimensions further comprise a surgical history dimension, a current medications dimension, a current allergies dimension, a social history dimension, a demographic/family history dimension, a diagnostic test findings dimension, a vital signs dimension, a physical examination findings dimension, and a diagnostic possibility dimension, wherein analyzing the set of recommended intervention actions further comprises analyzing a recommended action using a rule that determines a relationship between the one or more clinical decision support dimensions;

classifying an interaction of each recommended intervention into a contraindication category; and

adjusting, on the computer, the ranking and a total number of recommended intervention actions in the set of recommended intervention actions in order of preference for treatment of the condition indicated by the clinically relevant diagnosis, based on the rule and the contraindication category.

2. The method according to claim 1, wherein the relationships between and among the clinical decision support dimensions include at least a drug-drug interaction relationship, a drug-disease interaction relationship, and a drug-allergy interaction relationship.

3. The method according to claim 2, wherein the recommended intervention action comprises a pharmacotherapy regime, the method further comprising:

developing an initial list of effective medications on the basis of the condition situs in combination with a demographic/family history dimension;

stratify the initial list of effective medications on the basis of sensitivity to causative mechanism;

evaluate each medication for contraindications on the basis of co-existing disease, co-existing medications, co-existing allergies, and co-existing diagnostic test results;

exclude any medications having said contraindications; and

automatically developing a final, optimal list of effective medications.

4. The method according to claim 3, wherein each of the clinical decision support dimensions are specific to a particular patient and maintained in a database associated to that patient.

5. The method according to claim 4, wherein the recommended intervention actions are selected from the group consisting of a counseling program, pharmacotherapy, surgical therapy, diagnostic testing, and specialist referral.

6. The method of claim 1, wherein the contraindication category is one of no contraindication, a relative contraindication and an absolute contraindication.