Method for high-risk member identification

• US 7,640,175 B1
• Filed: 12/08/2000
• Issued: 12/29/2009
• Est. Priority Date: 12/08/2000
• Status: Active Grant

• Current Assignee: Optuminsight, Inc. (UnitedHealth Group Incorporated)
• Original Assignee: Ingenix Incorporated (UnitedHealth Group Incorporated)
• Inventors: Lutgen, Gerald L., Georgiou, Archelle, Prasad, Badri N.
• Primary Examiner(s): O'Connor; Gerald J.
• Assistant Examiner(s): PASS, NATALIE
• Application Number:
  US09/733,215
• Time in Patent Office: 3,308 Days
• Field of Search: 705 2- 4, 705/1, 705/35, 705/38, 705/8, 705/10, 705/5, 435/7.1, 706/21, 600/300, 600/310, 600/345
• US Class Current: 705/3
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

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.

Claims

1. 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;

creating a database of 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;

analyzing the claim data of 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 care history that are amenable to intervention by an intervention agent, and wherein the intervenability factors include;

(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, and (h) whether the member fails to obtain fills of prescribed medication during the focus period;

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 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;

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;

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;

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, the intervenability factors, and the one or more top medical episodes for each subset member selected by the intervention agent on the electronic display.

2. The method of claim 1, wherein the intervention agent may filter the displayed subset members by zipcode, county, group numbers, products, member ID or member names.