Ingenix, Inc.

Optuminsight, Inc.

Gerald Lutgen

Badri N Prasad

Krista Van Vorst

Adam Bock

Tomás Valdivia

Xingue Huang

Archelle Georgiou

Louise H Anderson

Felix Friedman

A computer implemented system and method for matching drugs and diseases involves matching drugs identified in a specific patient's prescription claim records with diseases identified in the patient's medical claims. A weighted relationship is generated between the matched drugs and diseases by calculating a link weight in accordance with a preprogrammed formula for each of the diagnosis codes identified in the patient's medical claims that is identified as associated with the disease identified and the drug. The link weight provides a statistical match association value to each of the matched diseases identified by way of a diagnosis code in the patient's medical claim and the drug identified in the prescription claim.

System and method of drug disease matching

A computer implemented system and method for matching drugs and diseases and generating a weighted relationship between the matched drugs and diseases. The system stores a quantity of patient medical history billing records identifiable as patient prescription claim records and medical claim records. The system also stores a grouping of drug codes and groupings of diagnosis codes. The system is configured to match drugs identified in a specific patient's prescription claim records with diseases identified in the patient's medical claims. The system generates a weighted relationship between the matched drugs and diseases by calculating a link weight in accordance with a preprogrammed formula for each occurrence of the diagnosis codes identified in the patient's medical claims that is identified as associated with the disease identified and the drug upon which the query is being processed. The link weight provides a statistical match association value to each of the matched diseases.

A system and method is provided for determining a probability that a member of a health plan has a disease or condition within one or more disease categories, by using data from the member's pharmacy claims. Logistic regression models are generated for each condition category using therapeutic drug categories, provider information, and/or other variables including member demographic information.

System for determining a disease category probability for a healthcare plan member

A method for using claims data to identify high-risk members of a healthcare plan is disclosed. In one embodiment, the present invention includes searching the plurality of claims of members selected by a filtering criteria to identify the presence of an intervention flag, to identify factors influencing care intervention, and identifying a medical episode driving the member's cost. In one embodiment, the intervention flag the medical episode are displayed in association with an identification of the member. In another embodiment, the member selection criteria includes selection based on the member's predicted future health care utilization.

Method for high-risk member identification

A system and method for modeling healthcare utilization based on usage data from physician claims, hospital claims, and pharmacy claims. The method includes extracting from a claims file the portion of the data from a base period that is relevant to modeling healthcare utilization in a target period by computing a utilization score based on the usage data. The models may be used concurrently by calibrating them with the base period equal to the target period and they may be also be used prospectively by calibrating the models with the target period representing a future time period.

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Saint Paul, MN, United States of America

Gerald Lutgen