BlueCross BlueShield of Tennessee, Inc., an Independent Licensee of the BlueCross BlueShield Association. This document has been classified as public Information. Identifying Individuals with Chronic Conditions: The Impact of Using Different Identification Methodologies on Quality of Care Assessment and Care Management Tanja Rapus Benton, Ph.D., Soyal Momin, M.S., M.B.A., David Reisman, B.S., Allen Naidoo, Ph.D., Ken Patric, M.D. Contact: Tanja Rapus Benton Bio-Statistical Research Scientist BlueCross BlueShield of Tennessee

2 Chronic Conditions and Quality of Care Importance of managing chronic conditions –Evidence-based treatment guidelines for chronic conditions established to: Improve quality of care Improve clinical outcomes First step: Identify candidates for targeted intervention programs –Different methodologies are available to identify individuals with chronic conditions Two important questions emerge: 1) Does choice of methodology affect the number of individuals who are identified as candidates? 2) Could this potentially impact measurement of quality at the member and provider level?

3 Identifying Individuals With Chronic Diseases Several approaches: –Use an episode grouper methodology to identify individuals with chronic conditions –Create Health Status Indicators that identify and flag individuals with specific conditions over time Identification logic differs based on approach used How well do these approaches converge? i.e., Is there a large, moderate or small disparity between the number of individuals identified by each method?

4 Research Objectives To assess the level of convergence between Health Status Indicators ® (HSI ® ) and Ingenix Episode Treatment Groups ® (ETGs ® ) in identifying chronic disease states –ETG ® and HSI ® methodologies differ –Both are used to identify individuals with gaps in care and identify individuals for care management programs Do differences exist in the number of individuals identified with chronic conditions based on the method used? –What are the implications for quality of care measures? Used to evaluate physician performance Used to evaluate efficacy of care management programs

5 Health Status Indicators (HSI) HSI ® logic uses specific combinations of inpatient, outpatient, and pharmacy services to identify chronic conditions similar to HEDIS criteria Event-based –e.g., inpatient admission Time-interval based –e.g., 2 office visits in 6 months –Disease-specific criteria include one or more of the following: ICD-9 diagnosis codes for principal or secondary diagnoses CPT/HCPCS codes for procedures NDC codes for pharmacy claims

6 HSI Methodology Creates a member-level flag that indicates the presence of a chronic condition Time-insensitive once it is created –Member carries this flag over time e.g., ‘once a diabetic, always a diabetic’ Chronic conditions include: –Asthma, CAD, CHF, COPD and Diabetes

7 Example: CHF Individual will meet the criteria for receiving an HSI ® for CHF if either of the following conditions is met: –Condition 1 – An encounter in an ambulatory or non-acute inpatient setting with a diagnosis of CHF, rheumatic heart disease or hypertensive heart and renal disease with CHF (principal or secondary diagnosis of , ….., ….) –Condition 2 – An encounter in an acute inpatient or ER setting with a diagnosis of CHF, rheumatic heart disease or hypertensive heart and renal disease with CHF (a principal or secondary diagnosis of , ….., ….) HSI ® is based on specific combinations of service and diagnosis codes and uses rolling 4 years of claims data

8 Episode Treatment Group (ETG ® ) Methodology ETGs ® bundle medical and pharmacy services into clinically meaningful, statistically reliable units Each diagnosis code is considered primary for one and only one ETG ® Each ETG ® has a defined clean period –Discrete episodes for diseases/conditions are created –Time-sensitive No member-level history is retained beyond the creation of the episode e.g., ‘once a diabetic, not necessarily always a diabetic’

9 Phase 1: Study Design Population Studied: Participants were members of the commercially insured population administered by a large single-state health plan in the southeastern U.S. Study Period: 2005 For 5 chronic conditions individuals with an HSI ® flag for 36 consecutive months (based on continuous enrollment) were identified 01/ /2005 ETG ® data for these members were pulled for each chronic condition for year 2005 –All types of episodes were included

10 Phase 1: Results Commercial Line of Business: Jan – Dec 2005

11 Phase 1: Results Overall the majority of members with an HSI ® for a chronic disease (55%) did not have an ETG ® for that disease during the given study period The number of members with an ETG ® for the same condition ranged from only 26% (CHF) to 61% (Diabetes)

12 Phase 1: Conclusions HSI ® methodology is more liberal in identifying members with chronic conditions –Overall only a minority of members with HSI ® have ETG ® Reliance on ETG ® methodology for identifying chronic conditions will underestimate prevalence ETG ® methodology is more time-sensitive ETG ® methodology has no ‘memory’ Two methodologies capture different information

13 Phase 2: Rationale Large differences were observed in the number of individuals identified with chronic conditions based on the methodology used –Inconsistency across conditions What implications does this have for evaluation metrics? Quality metrics used to evaluate physician performance Quality metrics used to evaluate the efficacy of care management programs

14 Phase 2: Study Design HEDIS-based quality measures were evaluated for year 2006 for individuals identified with chronic conditions in 2005 Quality scores for members identified by HSI ® vs. ETG ® methodology were compared for Diabetes and CHF Diabetes –Albumin test –Cholesterol test –HbA1c test –Eye exam CHF –Ace inhibitors –Beta blockers –Cholesterol Test –No IP admission

15 Phase 2: Results Differences in quality scores were observed based on the method used to identify individuals –Lack of consistency across diseases Overall quality scores were lower for members with an HSI ® for Diabetes than members who had an ETG ® for Diabetes For members with CHF no overall difference in quality scores was observed Condition DiabetesCHF With HSIWith ETGWith HSIWith ETG Mean Quality Score 58%63%46% N30,64733,54619,9074,670 t testt = 24.32, p<.0001n.s.

16 Conclusions and Recommendations Episode Grouper method captures fewer individuals with chronic diseases –Underestimates prevalence of chronic diseases in a given population Identification methodology can have an impact on quality scores Quality scores are used in a variety of important initiatives –Potentially impact pay for performance/transparency initiatives –Evaluations of the efficacy of care management programs Understanding and careful consideration of methodology chosen to target individuals for intervention programs is a must! Be consistent in methodology used across programs