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Minnesota LTSS Service Access Study: Findings from Years 1 and 2

Minnesota LTSS Service Access Study: Findings from Years 1 and 2. Jessica Kasten and Rebecca Woodward August 14 th - 15 th 2014. Minnesota is National Leader in Publicly-funded LTSS. 1.

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Minnesota LTSS Service Access Study: Findings from Years 1 and 2

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  1. Minnesota LTSS Service Access Study: Findings from Years 1 and 2 Jessica Kasten and Rebecca Woodward August 14th- 15th 2014

  2. Minnesota is National Leader in Publicly-funded LTSS 1 Ranked 1st in AARP Scorecard in overall performance across multiple dimensions, both in the 2011 and 2014 editions Increased shares of people receiving LTSS in the community Ranked 3rd on Medicaid per-person spending specific to HCBS (2012)

  3. Purpose of Study • Authorized by 2011 Legislature • If there were impacts of rate changes, how much? • What other factors were relevant to access? • How do findings support development of access measures for a DHS Dashboard? • The main purpose was to ascertain the extent to which provider rate changes affected recipients’ ability to access LTSS.

  4. Study Period Timeline for Provider Rate Change Effects

  5. Close collaboration with DHS Three Phases of Study Background and Selection of Access Measures 1 Exploratory analysis of trends and encounter data 2 3 Multivariate analysis

  6. Phase 1 Background on Service Access and Selection of Measures

  7. Background on Service Access and Selection of Measures, 2012 • Literature Review related to measurement of access in health care and LTSS • Review of how access to LTSS is assured in managed care • Interviewed MN MCO key informants • Proposed several measure domains to explore in the quantitative analysis: • Comparison of services used to services authorized, with a significant discrepancy indicating an access constraint • Service utilization • Provider availability • Measures described in discussion of multivariate analysis • Truven Health gathered and synthesized background materials to inform the selection of LTSS service access metrics.

  8. MCOs’ Perspectives on Access • Semi-structured telephone interviews (December 2012 - February 2013) using protocol approved by DHS • MCOs use numerous methods to assure access to LTSS • MCOs use several sources to assess their enrollees’ access to LTSS • MCOs generally did not think the rate changes affected access • Some did not think providers could sustain further cuts • Some thought the increase in PCA requirements adversely affected provider availability

  9. Phase 2 Exploratory Analysis of Trends and Encounter Data

  10. Service Use Trends • Selected services based on multiple criteria (e.g. policy interest, adequate data, offered by multiple programs, etc.) • Personal Care Assistance (PCA) • Private Duty Nursing (PDN) • Skilled Nurse Visit (SNV) • Homemaker • Consumer Directed Community Supports (CDCS) • Examined number of recipients using the service and amount of service used over the study period • Examined by delivery system (FFS and managed care) • Average number of people using the service increased both in FFS and managed care for PCA, homemaker, and CDCS • Trends not consistent between FFS and managed care for PDN or SNV

  11. Encounter Data Review • Reviewed encounter claims for the 5 services included in the trends analysis • Reviewed most relevant claims fields with particular focus on units of service • Most important finding for multivariate analysis was the significant number of outliers in units of service for some services in some years • Addressed by trimming the outliers to reasonable amounts based on DHS billing guidelines

  12. Phase 3 Multivariate Analysis

  13. Multivariate Analysis Overview • Statistical study of 2 or more variables of interest at the same time • Include factors such as geographic area, age of recipient, level of likely LTSS need, etc. • Main focus was rate effects (FYs 2008-12) • Explored same set of services from Phase 2, except for CDCS • CDCS presented methodological challenges • Included large number of State data sources • Added Rural Urban Commuting Area (RUCA) classification of geographic areas • What has been the impact of rate changes, relative to other potential correlates, on access to LTSS in Minnesota?

  14. Multivariate Outcome Variables

  15. Explanatory Variables Recipient characteristics that vary over time (e.g. age) Provider rate changes Recipient characteristics that do not vary over time (e.g. gender, race) Zip code characteristics (e.g. RUCA)

  16. Measure 1 Results: Discrepancy Between Authorized and Used Amounts of Service

  17. Measure 2 Results: Use vs. Non-Use of Service

  18. Measure 3 Results: Amount of Service Used

  19. Measure 4a Results: Enrolled Provider Counts

  20. Measure 4b Results: Participating Provider Counts

  21. Measure 5 Results: Ratio of Unique Recipients to Unique Participating Providers

  22. Multivariate Summary • Designed and analyzed access measures tailored to available data and DHS’ interests • Novel approach with few, if any, precedents • Most of the measures showed some rate change effects with Measure 3 (amounts of service used) showing the largest effects • Provider availability measures showed the least rate change effects • PCA appears to be the service, of the four examined, most greatly affected by the rate changes • Other factors such as age, level of LTSS need, and geographic area had much larger influence than the rate changes on access in Measures 1 and 2, but comparable or smaller-sized effects in Measure 3 • Enrollment in managed care often has a larger effect on access measures as compared to the effects of other factors

  23. Study Limitations • Main focus and charge were to determine whether there were rate change effects • Not able to explore whether other statistical approaches might explain the access measures better (i.e. better “fit” to data) • With no available control group, an observational study like this shows associations, not causation • Difficult to control for policy or programmatic changes (e.g. PCA reform) • Likely other factors we have neither identified nor controlled for • Presence of an informal caregiver • Level of LTSS need for people without assessments

  24. Next Steps • Development of technical appendix • Consider which measures best lend themselves to Dashboard metrics and what the most useful “drill-down” variables should be • Age group • Geographic location (RUCA, county, other) • Program (waiver, home care) • Develop Dashboard and test measures

  25. COMMENTS AND QUESTIONS

  26. Jessica Kasten Jessica.kasten@truvenhealth.com 301 547-4379 Rebecca Woodward Rebecca.woodward@truvenhealth.com 978 254-5353 More than Data. Answers.

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