Predicting state Medicaid home and community based waiver participants and expenditures, 1992-1997.
OBJECTIVE
The study examined trends and predictors of state Medicaid home and community based waiver participants and expenditures from 1992 to 1997 to identify factors of interest to policy makers and clinicians.


METHODS
HCFA Form 372 data were collected from state officials for each waiver for each year. Two separate regression analyses were conducted to examine the effects of sociodemographic, economic, political, policy, and health services on state waiver participants and expenditures.


RESULTS
State waiver participants were positively associated with those aged 85 and over, personal income, residential care beds, and inpatient users and negatively with home health regulation and nursing home beds. State waiver expenditures were positively associated with democratic governors, personal income, home health reimbursement methods, Medicaid eligibility, home health agencies, and Medicare home health users.


CONCLUSIONS
The factors policy makers might consider changing include increasing the number of residential care beds and home health agencies, removing certificate of need for home health care, using Medicare home health reimbursement methods for Medicaid, and raising the Medicaid eligibility criteria. In some states with low nursing home occupancy rates, reducing the supply of nursing home beds may also be considered. All of these approaches would be controversial and should be based on additional cost-effectiveness analysis.
Harrington
C
C
Department of Social and Behavioral Sciences, University of California, San Francisco 94143-0612, USA. chas@itsa.ucsf.edu
Carrillo
H
H
Wellin
V
V
Miller
N
N
LeBlanc
A
A
D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D014487:Centers for Medicare and Medicaid Services, U.S.; D003153:Community Health Services / Q000191:economics* / Q000706:statistics & numerical data; D003362:Cost-Benefit Analysis; D004608:Eligibility Determination; D005161:Facility Regulation and Control / Q000331:legislation & jurisprudence; D005260:Female; D005544:Forecasting; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006302:Health Services Research; D006699:Home Care Services / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008484:Medicaid / Q000191:economics / Q000706:statistics & numerical data*; D017059:Models, Econometric; D020380:Needs Assessment; D012044:Regression Analysis; D012051:Reimbursement Mechanisms / Q000458:organization & administration; D012959:Socioeconomic Factors; D014481:United States