THE EFFECT OF MEDICAID RATE
ON POTENTIALLY PREVENTABLE
HOSPITALIZATIONS
FROM NURSING HOME*
Orna Intrator
with
V. Mor, N. Wu, D. Grabowski†,
D. Gifford and Z. Feng
Brown University and † UAB
* Funded by NIA RO1 AG20557
Objective



Medicaid payment rates are reflected in the
availability of the clinical and managerial
infrastructure necessary to manage nursing
home residents’ medical conditions.
Over 60% of all nursing home residents are
Medicaid recipients
Differences in reimbursement rates and other
Medicaid reimbursement policies likely to
contribute to observed inter-state differences
in hospitalization rates.
CONCEPTUAL MODEL
STATE
Policies
MARKET
Context
NURSING
HOME
Context
Hospitalization
RESIDENT
Characteristic
s
Direct and indirect effects
Hypotheses: direct effects

Nursing home residents in states with
Higher Medicaid rates experience fewer
potentially preventable hospitalizations.
 Bedhold policies will be more likely to be
hospitalized
 With casemix reimbursement will be more
likely to be hospitalized because a
hospitalization would result in change in
per-diem rate

Hypotheses: Indirect effects

Higher Medicaid rates 

More NP/PAs
•  Less hospitalizations

More RNs in nursing home nursing force
•  Less hospitalizations

More investment in physicians
•  Less hospitalizations
Data and Cohort
• Minimum Data Set (MDS) to identify long-stay
residents or urban free standing nursing homes in 48
contiguous states in 2000 (N=575,188 in 9124
facilities)
• Facility data from Centers for Medicare and Medicaid
Services’ Online Survey Certification and Reporting
(OSCAR) system.
• Medicare claims of all hospitalizations within 5
months of baseline MDS that were initiated from
baseline nursing home (N=101,105)
 Area Resource File for information on counties as NH
markets
Survey of
State Medicaid Policies*
48 continguous states contacted
 Information on:

Method of calculation
 Casemix method and updating schedule
 Average per-diem payment rate and
ancillary payments
 Bedhold rate and durations
 CON and moratorium

*Forthcoming article in Health Affairs Web Exclusive
June 18, 2004
State Policy Measures

Average per diem rate:





Total payments divided by total bed days
Free standing and hospital based
Annually, 1999-2002
Used 2000 data in this study
Bedhold policies*



Proportion of NH rate paid
Maximum number days in period
Minimum occupancy requirements
*Poster at 6pm tonight
State Policy Measures

Casemix reimbursement:




Type of system (RUG based, other)
How frequently updated (annually, quarterly)
Based on resident, facility, or both
Four category variable:
•
•
•
•
No casemix (N=17)
Not resident specific only updated annually (N=9)
Facility specific quarterly or semi-annually (N=14)
Most responsive: Resident specific quarterly or semiannually or both and quarterly (N=8)
Outcome Definition

Hierarchical outcome:
Any potentially preventable hospitalization
(using ambulatory care sensitive diagnoses)
 Any other hospitalization
 Death
 Remaining in the facility.

Distribution of outcome:
Any potentially preventable …………… 7.4%
Other Hosp ……………………………..……. 12.6%
Died ……………………………………….……….. 9.2%
Model and Estimation
Multinomial response (4 categories)
 Multilevel:

Resident
 Facility
 County
 State


Estimation using MLWiN for binomial
response: Outcome vs. remain in NH
Results:
Direct Medicaid Policy Effects
Potentially
Preventable
AOR
LCI
Any bedhold
1.41
(Medicaid Rate - $100)/$20
0.94
Casemix Annual
0.99
Caemix Semi-Annual
1.05
Casemix Frequenty
1.36
UCI
1.15
0.86
0.78
0.85
1.07
P<.05
P<.1
1.74
1.03
1.26
1.30
1.73
Other
Hospitalizations
OR
LCI
UCI
1.26
1.09
1.47
0.92
0.87
0.99
1.05
0.88
1.24
1.08
0.92
1.25
1.22
1.02
1.46
Results:
Indirect Medicaid Policy Effects
Potentially
Preventable
AOR LCI
Any NP/PAs
0.93
>4.55 Nurse hr/resident day 0.92
>3.2 Nurse hr/resident day
1.02
>1/2 Physician FTE
0.96
Other
Hospitalizations
UCI OR
LCI
UCI
0.89 0.97 0.98 0.95
0.86 0.99 1.00 0.95
0.98 1.05 0.98 0.95
0.92 0.99 1.00 0.98
P<.05
P<.1
Death
Within 5 months
OR
LCI UCI
1.01 1.03 1.01
1.05 1.01 0.96
1.00 1.00 0.97
1.03 0.99 0.96
1.06
1.06
1.02
1.01
Policy Implications
• Highlights competing motivation of Medicaid and
Medicare:
• Higher Medicaid rates  lower Medicare
expenditures from less hospitalizations
 higher Medicare expenditures from increased
LOS
• Higher bedhold rates  higher Medicare
expenditures
• More bedhold days  better quality of life
• What is “optimal” policy
• For Medicare? For Medicaid? For Residents?