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Eliot Fishman and Suzanne Tamang Medicare Advantage Quality Measurement & Performance Assessment Conference April 8

Eliot Fishman and Suzanne Tamang Medicare Advantage Quality Measurement & Performance Assessment Conference April 8-9, 2008. Using the Health Outcomes Survey to Inform Quality Measurement for Medicare Advantage.

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Eliot Fishman and Suzanne Tamang Medicare Advantage Quality Measurement & Performance Assessment Conference April 8

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  1. Eliot Fishman and Suzanne Tamang Medicare Advantage Quality Measurement & Performance Assessment Conference April 8-9, 2008

  2. Using the Health Outcomes Survey to Inform Quality Measurement for Medicare Advantage

  3. Overview of how Medicare Advantage plans can use Health Outcomes Survey (HOS) data to analyze the impacts of programs. Based on one plan's experience with analysis of the impacts of a Chronic Care Benefit on nursing home use: How to look at both aggregated and individual-level data; How to use HOS data regarding chronic illness and psychosocial risk factors; How HOS data can contribute to a broader quality analysis strategy incorporating HEDIS, CAHPS, claims data, and other data sources. Objectives 1

  4. Enrollment of about 18,000 (up from 9,000 in 2002) Operated from 1980s until 2007 as a Social HMO. Social HMO Benefit package included up to $7800 in chronic care benefits, including personal care services, which are the lion’s share of CCB service utilization and expenditure. Personal Care Benefit—An important policy subject Now one of the nation’s first Special Needs Plans to focus on nursing home-eligible individuals in the community. About Elderplan 2

  5. How does risk-adjusted nursing home utilization compare between Elderplan and other MA plans? While NH utilization was similar in Elderplan overall, utilization among frail enrollees and long-term nursing home utilization are lower than would be expected. Is there evidence that the plan members’ home care benefit utilization directly offset nursing home utilization? Dividing Elderplan’s 2004 frail membership into cohorts based on usage of personal care workers, nursing home utilization went down substantially as personal care utilization increased. This is despite the much higher frailty of the higher home-care-utilizing cohorts. Our Questions in 2005-2006, And What We Found 3

  6. Elderplan has Extremely Low Nursing Home Residence Rates Compared to General Medicare Population • Average point-in-time level of nursing home residence (100 days or more) approximately 1/6 the New York State average (.7% vs. 4.6%).This is despite Elderplan’s higher than average age and frailty based on comparison of HOS to MCBS. • Question: How would this result hold up in comparison to other MA plans? 4

  7. A longitudinal, self-administered survey of Medicare Advantage enrollees Beneficiaries are randomly sampled from each plan and surveyed every spring Two years later, these same respondents are surveyed again Purpose to identify health care status, health-related quality of life of Medicare Advantage enrollees. Wave IV – 2001-2003 Health Outcomes Survey 5

  8. We found this by searching online databases for work on Nursing Home Utilization and Medicare Managed Care. Sample HOS self-respondents Wave III (1999-2001) Linked HOS with MDS, OSCAR, EDB Method—Cox Cox Proportional Hazards Regression Model was used to predict the risk of entering a nursing home Various models were tested to determine the final variables Independent Variables - Predisposing, Enabling, Need-Based Dependent Variable - Nursing Home Admission The Harris Model of HOS-based predictors of NH Utilization 6

  9. Harris used only those who filled out HOS Survey themselves for her analysis. In order to mirror her analysis, we needed to isolate nursing home utilization by responder type—that is, self-responders, proxy responders, and non-responders. Issues in using the HOS — Part I 7

  10. Out of 490 who submitted a baseline HOS survey, CMS did not include 95 records in the standard “Performance Measurement Report” for confidentiality reasons (subsequently disenrolled: 62, incomplete survey: 33) Unlike Harris, using HOS sample as all MA plans receive it from CMS, we could not account for outcomes among those lost to follow-up. Issues in using the HOS — Part I 8

  11. Furthermore, the standard CMS HOS report does not include all of the individual HOS measures, particularly those relating to psycho-social independent variables. (e.g. individual functional status, marital status variables) Without these measures, we would have to use HOS sample measures for some independent variables and plan-wide measures for others. Issues in using the HOS — Part I 9

  12. To resolve the issues described above, we requested the complete data set from the HOS study group, including “non-responders” (n=1000). The acquisition process involved: Submission and approval of a Data Use Agreement (DUA) by CMS Preparation and delivery of the data by HSAG Integrating HOS data with internal EP data for our analysis involved: Identifying the relevant HOS fields and codes detailed by HOS Electronic Data Users Guide (provided by HSAG). Importing HOS and EP claims data into a relational DB application. Using unique identifiers, to join HOS survey data with internal plan data. This allowed us to track Nursing Home Utilization. Also gave us the option of analyzing HOS non-responders. Acquiring a Complete HOS Data File 10

  13. Harris drew on National MDS Sample for Nursing Home utilization. We draw on Elderplan claims for post-acute and payment codes for long-term NH. Therefore, disenrollment is a censoring event for us and not for Harris. We have superficially adjusted for disenrollment. Harris does not distinguish between short-term and long-term NH stays. Because Elderplan’s long-term stays are seemingly low relative to short-term stays, this is a key area of analysis. Harris assumed that about 50% of stays in her sample become long-term stays (> 100 days), reflecting widespread national trends over decades. (e.g. J. Kasper “Who Stays and Who Goes”, Kaiser Family Foundation, 2005) However, with the growth of post-acute rehab in nursing homes, more recent estimates indicate that only 40% of nursing home admissions “convert” to custodial nursing home stays. Complicating Factors of Applying This Model 11

  14. The Harris Model of HOS-based predictors of NH Utilization

  15. Elderplan’s Baseline HOS vs. MA Average

  16. Nursing Home Utilization Outcomes 14

  17. Results of HOS Analysis—All Nursing Home Stays • Elderplan had similar or slightly lower nursing home admission rates than would have been predicted looking at whole plan membership and available (continuously enrolled) individual HOS responders. • However, long-term nursing stays were lower than would be expected based on national MA trends. 15

  18. Long-Term Nursing Home Days: Within Nursing Home Certifiable (NHC) population, a 2004 total of 140 Chronic (Status Code 01) Nursing Home Stays of Greater than 100 Days. 56 out of 140 (40%) long-term stays among Personal Care Users, while PCW users only 23% of NHCs. But Frailty Index is much higher among PCW users (.39 vs. .15). Next step: Looking at NH Use and Personal Care Utilization 16

  19. Within NHC Population, Average Frailty Score (from the HSF Frailty Index) for PCW Utilizers is .39. Average Frailty for non-PCW utilizers is .15 (2004) Same for HCCs: PCW Utilizers: 1.61 Non-PCW Utilizers: 1.28 PCW costs also go up with frailty score. The Frailty score has a 30% correlation with PCW costs among PCW users. There is a small (8%) correlation with HCC. PCW Benefit is Going to Frailest Members 17

  20. Effect is above $2400 in PCW Benefits: that is, more than one visit per week. Long-term NH Stays identified by Status Code 01 (Chronic Institutional) for 100 Days or more. Both NH Days and NH Stays go down dramatically with PCW. As PCW Hours go up in 2004, Long-Term Nursing Home Stays Go Down 18

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  22. High Levels of PCW Utilization Also Correlated With Lower Hospitalizations(Non-Medicaid PCW Users, Hospitalizations per member per year , 2004) 20

  23. Elderplan’s annual QI initiatives are driven by a combination of HEDIS, CAHPS, HOS, internal surveys and medical record review. Plans have a variety of data sources available to them for QI purposes. Based on CMS requirements, Elderplan selects clinical or nonclinical initiatives: In 2006, the Plan selected CAHPS Access and Availability indicators as one of its performance measures with the goal of increasing member satisfaction. In 2007, EP selected the HEDIS Controlling High Blood Pressure measure as one of its performance measures. HTN is the #1 Dx in EP membership. New guidelines emphasize lower thresholds for controlled HTN. Elderplan Quality Improvement Initiatives 21

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