METHOD FOR HIGH-RISK MEMBER IDENTIFICATION

1 - 30 . (canceled)

31 . A computer-implemented high risk member identification method, comprising a computer performing the following:

identifying a group of members to be analyzed using a computer software application, each group member having an associated relative risk value, wherein the relative risk value for each member is a function of predicted future healthcare resource utilization for the member;

filtering the group members using the computer software application to identify members having an associated relative risk value that exceeds a threshold value of relative risk, thereby identifying a subset of the group members for potential intervention;

analyzing healthcare claim data associated with each subset member using the computer software application to ascertain the presence or absence of each of a plurality of intervenability factors present to the subset member, wherein the intervenability factors for each subset member are identified based upon aspects of each subset member's healthcare history that are amenable to intervention by an intervention agent;

using the computer software application to assign each subset member a number of intervenability factors representing a total number of the intervenability factors present in the subset member's healthcare claim data;

using the computer software application to assign a relative risk ranking to each subset member based upon the subset member's associated relative risk value and the number of intervenability factors assigned to the subset member; and

displaying (a) a list of the subset members ordered by respective relative risk rankings and (b) the relative risk value for each subset member on an electronic display.

32 . The method of claim 31 , wherein the intervenability factors include at least one of the following: (a) whether the member visited the emergency room during the focus period, (b) whether the member had any in-patient hospital admissions during the focus period, (c) whether the member incurred any out-of-network costs during the focus period, (d) whether the member visited more than three different provider specialists during the focus period, (e) whether the member was prescribed multiple pharmaceuticals during the focus period, (f) whether the member has no appropriate provider for a chronic episode during the focus period, (g) whether the member missed a target intervention during the focus period, or (h) whether the member fails to obtain fills of prescribed medication during the focus period.

33 . The method of claim 31 , further comprising creating a database of the healthcare claim data for the subset members, wherein the database includes all medical diagnoses and healthcare utilization patterns for each subset member during a focus period, including any physician claims, facility claims and pharmacy claims associated with each subset member during the focus period.

34 . The method of claim 31 , further comprising using the computer software application to determine one or more top medical episodes driving risk of each subset member, wherein the top medical episodes are determined by examining the subset member's claim data by diagnosis code or medical episode to determine which of the subset member's medical conditions has the highest associated cost.

35 . The method of claim 31 , further comprising:

receiving a selection of one or more displayed subset members input into the computer software application by an intervention agent; and

displaying demographic information, a utilization summary, risk factors including behavioral risk factors and self-care characteristics, and the intervenability factors for each subset member selected by the intervention agent on the electronic display.

36 . The method of claim 35 , wherein the intervention agent may filter the displayed subset members by zipcode, county, group numbers, products, member ID or member names.