minnesota ltss service access study: findings from years 1 and 2

© Truven Health Analytics Inc. All Rights Reserved. 1

Jessica Kasten and Rebecca WoodwardAugust 14th- 15th 2014

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


Minnesota is National Leader in Publicly-funded LTSS

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

Older Adults People with Disabilities

0%

20%

40%

60%

80%

100%

2000 2012

Ranked 3rd on Medicaid per-person spending specific to HCBS (2012)

1


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.


Study Period Timeline for Provider Rate Change Effects


3

1

2

Three Phases of Study

Close collaboration w

ith DH

S

Background and Selection of

Access Measures

Exploratory analysis of trends and encounter

data

Multivariate analysis

© Truven Health Analytics Inc. All Rights Reserved. 6© Truven Health Analytics Inc. All Rights Reserved. 6

Phase 1

Background on Service Access and Selection of Measures


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

o Interviewed MN MCO key informants

Proposed several measure domains to explore in the quantitative analysis:

1. Comparison of services used to services authorized, with a significant discrepancy indicating an access constraint

2. Service utilization

3. 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.


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


Phase 2

Exploratory Analysis of Trends and Encounter Data


Service Use Trends

Selected services based on multiple criteria (e.g. policy interest, adequate data, offered by multiple programs, etc.)

oPersonal Care Assistance (PCA)

oPrivate Duty Nursing (PDN)

oSkilled Nurse Visit (SNV)

oHomemaker

oConsumer 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


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

oAddressed by trimming the outliers to reasonable amounts based on DHS billing guidelines


Phase 3

Multivariate Analysis


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

o 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?


Multivariate Outcome Variables

Multivariate Model

Access Measure as Dependent Variable

Access Measure Description

Service Authorized Amount vs. Used

Measure 1 (FFS Only) % difference between authorized and used amounts of LTSS Service X, with access constraint defined as a discrepancy of >15%

Utilization Measure 2 Out of those eligible, use or non-use of LTSS Service X within a given yearly quarter

Measure 3 Out of service users, amount (units) of LTSS Service X used within a given yearly quarter

Provider Availability

Measures 4a and 4b Number of enrolled LTSS providers per county (4a) and participating LTSS providers per county (4b)

Measures 5 Ratio of unique recipients to unique participating LTSS providers


Explanatory Variables

Zip code characteristics (e.g. RUCA)

Provider rate changes Recipient

characteristics that vary over

time (e.g. age)

Recipient characteristics

that do not vary over time

(e.g. gender, race)


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


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


Measure 3 Results: Amount of Service Used


Measure 4a Results: Enrolled Provider Counts


Measure 4b Results: Participating Provider Counts


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


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


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


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


COMMENTS AND QUESTIONS


More than Data. Answers.

Jessica [email protected] 547-4379

Rebecca [email protected] 254-5353

mailto:[email protected]

mailto:[email protected]

minnesota ltss service access study: findings from years 1 and 2

Documents

health care

measurement of access

enrollees access

development of access

provider rate changes

quantitative analysis

multiple criteria

multiple programs