Hongdao Meng, Ph.D., Stony Brook University Brenda Wamsley, Ph.D., West Virginia State University
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Transcript of Hongdao Meng, Ph.D., Stony Brook University Brenda Wamsley, Ph.D., West Virginia State University
Impact of a Voucher Program on Consumer Choices of
Personal Assistance Providers: Urban-Rural Differences
Impact of a Voucher Program on Consumer Choices of
Personal Assistance Providers: Urban-Rural Differences
Hongdao Meng, Ph.D., Stony Brook University
Brenda Wamsley, Ph.D., West Virginia State University
Acknowledgments Acknowledgments
• Funding agency: Centers for Medicare and Medicaid Services (# 95-C-90467/2-01)
• Monroe County Long Term Care Program, Inc., Rochester, NY.
• Center for Aging and Healthcare in WV, Inc., Parkersburg, WV.
BackgroundBackground
• Personal Assistance Services (PAS) help people with long-term care needs to live independently in their homes.
• PAS is delivered via:– “Agency-directed” model (ADM)– “Consumer-directed” model (CDM)
BackgroundBackground
• Benefits of CDM:– Flexibility– Autonomy– Potential cost-savings– Expanded care worker pool
• Concerns of CDM:– Cognitive impairment– Hiring of family members– Quality assurance
ObjectivesObjectives
• To examine the impact of a voucher program on consumer choices of PAS providers (ADM or CDM).
• To assess urban-rural differences in these choices.
Study DesignStudy Design
• Randomized controlled trial:– Control group: regular Medicare– Nurse group: health promotion nurse home
visit– Voucher group: $200 monthly PAS benefits– Combination group: Nurse + Voucher
SampleSample
• 1605 participants who meet the inclusion criteria of this study:– Community-dwelling (NY, WV, OH) – Medicare Parts A and B enrollee, and– 2+ ADLs or 3+ IADLs, and– Had prior health services use (ER, hospital,
NH, or home care)
DataData
• Baseline assessment data – Socio-demographics– Health and functional status– Prior health services use
• PAS utilization data over two years– Personal care aide – Home health aide – Respite care
Analytical StrategiesAnalytical Strategies
• Descriptive statistics
• Multivariate logistic regression adjusting for the following co-variates:– Age, gender, education, income, MediGap,
Medicaid, caregiver status– ADLs, IADLs, Cognitive Performance Scale– Prior health services use
Baseline Descriptive ResultsBaseline Descriptive Results
• Mean age 77– 27% age 85+
• 69% female• 96% White• 33% income < $10k• 73% had caregiver • 38% lived alone• 11% had Medicaid• 3% had LTC
insurance
• Mean # of ADLs 2.3• Mean # of IADLs 3.5• Mean # of chronic
conditions: 4.4• Prior service use:
– Hospital 63%– ER 23%– Nursing home
10%– Home care 52%
PAS Use Over Two YearsPAS Use Over Two Years
% with any use
19%
21%
21%
38%ADM onlyCDM onlyBothNeither
PAS Use, Control GroupPAS Use, Control Group
% with any use
16%
22%
18%
44% ADM only
CDM only
BothNeither
PAS Use, Voucher GroupPAS Use, Voucher Group
% with any use
21%
21%
24%
33%
ADM only
CDM only
BothNeither
Odds Ratio for PAS Use, by Provider Type
Odds Ratio for PAS Use, by Provider Type
1.74
1.28
0
0.5
1
1.5
2
ADM CDM
Adjusted for covariates
Odds Ratio for PAS Use, by Provider Type and Urban-Rural
Odds Ratio for PAS Use, by Provider Type and Urban-Rural
**: p < 0.01, adjusted for covariates
Summary of Key FindingsSummary of Key Findings
• Overall, the voucher program increased the probabilities of using both types of PAS providers.
• In urban areas, the voucher effect is primarily on the use of agency-employed workers.
• In rural areas, the voucher effect is primarily on the use of privately-hired workers.
LimitationsLimitations
• Generalizability
• Definition of rural
Policy ImplicationPolicy Implication
• A voucher program for PAS promotes its use moderately.
• Consumer behavior under the voucher program differs substantially between urban and rural participants.
• The availability of agency and private workers may
explain part of the observed differences.
• These differences should be taken into account in promoting the use of consumer-directed models.