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Examining Long-Term Care Episodes and Care History for Medicare Beneficiaries:
A Longitudinal Analysis of Elderly Individuals with
Congestive Heart Failure
Stephanie Maxwell & Timothy Waidmann
APHA Annual MeetingBoston, MA
November 6, 2006
Background
• Congestive heart failure (CHF) is the leading medical condition among the elderly.
• Significant policy concern regarding CHF hospitalization rates
• CHF is a common target of disease management programs.
• Few large-scale studies have explored the CHF patients’ use of long-term care (LTC) services and Medicare services combined
Overview of Study Design
• Longitudinal (36-month) analyses
• National cohort of elderly who were first hospitalized for CHF in 1999.
• Identify patterns over three years of Medicare service use and spending, enrollment in Medicaid, and nursing home entry.
• Estimate hazard models of risks of re-hospitalization, nursing home admission and death, controlling for health status.
Data Sources (mainly 1999-2002 files)
• 100% Medicare claims files (all service types)
• 100% Medicare enrollment files
• 100% MDS patient assessment records
• Area Resource File and Interstudy HMO Files
Defining the Cohort in the Claims Data
Final cohort = 296,462 elderly
•Cohort consists of elderly hospitalized, in 1999, for their first hospitalization for CHF.
•The principal diagnosis field of acute hospital records was searched for a set of diagnosis codes indicating CHF as the primary reason for hospitalization.
•Scanned a 5-year “look-back” period of hospital claims (1994-1998 claims) to screen out individuals whose first CHF admission occurred before 1999.
•To assure a comparable “look-back period”, we included only those age-eligible for Medicare in January 1994 in the cohort.
Statistical Methods
• Bivariate analyses -- of outcomes stratified by patient and area characteristics
• Survival models -- to estimate the effects of covariates on the instantaneous risk of an outcome, through measuring the elapsed time before an outcome is observed.
• Two-part use and spending models – estimated models for the first six months following CHF hospitalization and also for the three years following CHF hospitalization.
Outcomes Measures of Hazard Models
• Survival
• Subsequent CHF hospitalization
• Subsequent non-CHF hospitalization
• Medicaid enrollment
• Nursing home entry
Outcomes Measures of Two-Part Use and Spending Models
• CHF hospitalizations
• Other hospitalizations
• SNF stays
• Home health use
• Hospital outpatient use
• Physician services use
Person-Level Independent Variables
• Demographics (age group, race, sex)
• Charlson comorbidity score
• Length of stay of the index CHF hospitalization
• Nursing home use prior to index CHF hospitalization
Utilization and spending variables between the index CHF hospitalization and outcome:
• Quarterly physician spending
• Quarterly hospital outpatient spending
• Quarterly acute hospital spending (except in models of death and non-CHF hospitalizations)
• CHF hospitalizations (except when used as an outcome)
• Oher hospitalizations (except when use as an outcome)
• SNF stays
• Medicare home health use
• Nursing home use (except when used as an outcome)
County-Level Independent Variables
• Urban influence
• HMO penetration
• Median county income
• Supply rates per 1000 elderly:– All physicians – Cardiologists – Short-term hospital beds – Long-term hospital beds – SNF beds – Nursing home beds
• Presence of a facility in the county:
– Short-term hospital – Nursing home – Rural health clinic – Federally qualified health clinic
• Population mortality rates for 10 selected medical conditions
Summary of Findings
Over 3 years following index hospitalization for CHF:
• 36% had additional CHF hospitalizations
• 68% had hospitalizations for other conditions
• 42% had SNF stays
• 15% entered a nursing home (non-Medicare)
• 7% enrolled in Medicaid
• 56% died
• 11% had NH use prior to their index CHF hospitalization
• Average 3-year spending = $35,000– Non-CHF hospitalizations was largest source of spending
Findings – Death
SNF use is the dominant risk
• Age -- 5 additional years 13% to 30% higher risk
• Charlson -- additional comorbidity 10% higher risk
• Index LOS -- additional day 2% higher risk
• SNF use 200% higher risk
• Physician spending per quarter ($thousands) 15 to 40%
higher risk
• NF use 15% to 47% higher risk
Mortality risk, by state
0.8
0.85
0.9
0.95
1
1.05
1.1
1.15
1.2
1.25
OR
EG
ON
OK
LA
HO
MA
WA
SH
ING
TO
N
UTA
H
MIS
SIS
SIP
PI
GE
OR
GIA
AR
KA
NS
AS
NE
W M
EX
ICO
NE
VA
DA
LO
UIS
IAN
A
DE
LA
WA
RE
NO
RT
H C
AR
OL
INA
MIC
HIG
AN
AR
IZO
NA
TE
XA
S
WY
OM
ING
AL
AB
AM
A
IDA
HO
HA
WA
II
SO
UT
H C
AR
OL
INA
VIR
GIN
IA
IND
IAN
A
WE
ST
VIR
GIN
IA
CO
LO
RA
DO
MO
NTA
NA
AL
AS
KA
TE
NN
ES
SE
E
NE
BR
AS
KA
OH
IO
VE
RM
ON
T
NE
W H
AM
PS
HIR
E
MIS
SO
UR
I
CA
LIF
OR
NIA
FL
OR
IDA
KA
NS
AS
KE
NT
UC
KY
WIS
CO
NS
IN
IOW
A
RH
OD
E IS
LA
ND
NE
W Y
OR
K
ILL
INO
IS
MA
RY
LA
ND
PE
NN
SY
LVA
NIA
DIS
TR
ICT
OF
CO
LU
MB
IA
MIN
NE
SO
TA
MA
INE
NE
W J
ER
SE
Y
MA
SS
AC
HU
SE
TT
S
CO
NN
EC
TIC
UT
SO
UT
H D
AK
OTA
NO
RT
H D
AK
OTA
Haz
ard
rat
io (
rela
tive
to
Ala
bam
a)
Findings – CHF Hospitalizations
Approximately 15% increased risk associated with:
• 5-year age increase• Additional comorbidity • Race: Black• Physician spending per quarter ($thousands)• Home health use
Whites have higher death risks and blacks have higher rehospitalization risks. This is consistent with each other in suggesting that whites are more severely ill once hospitalized.
CHF hospitalization risk, by state
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
AL
AS
KA
MIS
SIS
SIP
PI
DIS
TR
ICT
OF
CO
LU
MB
IA
WE
ST
VIR
GIN
IA
AR
KA
NS
AS
KE
NT
UC
KY
AL
AB
AM
A
SO
UT
H C
AR
OL
INA
IND
IAN
A
LO
UIS
IAN
A
NE
W H
AM
PS
HIR
E
GE
OR
GIA
OH
IO
HA
WA
II
MA
RY
LA
ND
OK
LA
HO
MA
MIS
SO
UR
I
TE
NN
ES
SE
E
PE
NN
SY
LVA
NIA
VIR
GIN
IA
ILL
INO
IS
NO
RT
H C
AR
OL
INA
MIN
NE
SO
TA
DE
LA
WA
RE
RH
OD
E IS
LA
ND
MIC
HIG
AN
TE
XA
S
MA
SS
AC
HU
SE
TT
S
NE
W J
ER
SE
Y
WIS
CO
NS
IN
MA
INE
KA
NS
AS
NE
W Y
OR
K
WY
OM
ING
MO
NTA
NA
SO
UT
H D
AK
OTA
AR
IZO
NA
FL
OR
IDA
CO
NN
EC
TIC
UT
NE
BR
AS
KA
WA
SH
ING
TO
N
CA
LIF
OR
NIA
IOW
A
IDA
HO
NE
VA
DA
UTA
H
NO
RT
H D
AK
OTA
OR
EG
ON
NE
W M
EX
ICO
VE
RM
ON
T
CO
LO
RA
DO
Findings – Other Hospitalizations
Compared to CHF hospitalization, key differences
are regarding race and home health use
• Blacks 10% to 20% higher risk for CHF hospitalizations • But blacks 5% to 10% lower risk for other hospitalizations
• Home health use 15% higher risk for CHF hospitalizations• But home health use 20% lower risk for other hospitalizations
Non-CHF hospitalization risk, by state
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
1.05
1.1
MIS
SIS
SIP
PI
WE
ST
VIR
GIN
IA
LO
UIS
IAN
A
AR
KA
NS
AS
AL
AB
AM
A
MA
INE
SO
UT
H C
AR
OL
INA
OK
LA
HO
MA
MO
NTA
NA
NO
RT
H C
AR
OL
INA
KE
NT
UC
KY
TE
NN
ES
SE
E
SO
UT
H D
AK
OTA
MA
SS
AC
HU
SE
TT
S
MIS
SO
UR
I
IDA
HO
MIC
HIG
AN
IOW
A
UTA
H
KA
NS
AS
GE
OR
GIA
VIR
GIN
IA
IND
IAN
A
MA
RY
LA
ND
TE
XA
S
CO
NN
EC
TIC
UT
OH
IO
PE
NN
SY
LVA
NIA
ILL
INO
IS
NE
VA
DA
WA
SH
ING
TO
N
VE
RM
ON
T
CO
LO
RA
DO
WY
OM
ING
MIN
NE
SO
TA
DIS
TR
ICT
OF
CO
LU
MB
IA
FL
OR
IDA
WIS
CO
NS
IN
AR
IZO
NA
NE
W M
EX
ICO
DE
LA
WA
RE
NE
W H
AM
PS
HIR
E
NE
BR
AS
KA
RH
OD
E IS
LA
ND
NE
W Y
OR
K
OR
EG
ON
NO
RT
H D
AK
OTA
HA
WA
II
NE
W J
ER
SE
Y
CA
LIF
OR
NIA
AL
AS
KA
Findings – Nursing Home Entry
SNF use and prior NH use are dominant risks
• SNF use several hundred percent higher risk
• Prior NH use 100% higher risk
• Additional CHF hospitalizations 20% higher risk
• Other hospitalizations 5% to 20% higher risk
Nursing home entry risk, by state
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
RH
OD
E IS
LA
ND
CO
LO
RA
DO
WY
OM
ING
IOW
A
NE
W Y
OR
K
NO
RT
H D
AK
OTA
MIN
NE
SO
TA
DE
LA
WA
RE
LO
UIS
IAN
A
OK
LA
HO
MA
WA
SH
ING
TO
N
GE
OR
GIA
KE
NT
UC
KY
MO
NTA
NA
NE
W M
EX
ICO
TE
XA
S
NO
RT
H C
AR
OL
INA
NE
VA
DA
OR
EG
ON
NE
BR
AS
KA
MA
SS
AC
HU
SE
TT
S
MIC
HIG
AN
CA
LIF
OR
NIA
WIS
CO
NS
IN
OH
IO
MIS
SO
UR
I
KA
NS
AS
PE
NN
SY
LVA
NIA
DIS
TR
ICT
OF
CO
LU
MB
IA
AR
KA
NS
AS
CO
NN
EC
TIC
UT
NE
W J
ER
SE
Y
AL
AB
AM
A
TE
NN
ES
SE
E
NE
W H
AM
PS
HIR
E
MIS
SIS
SIP
PI
SO
UT
H C
AR
OL
INA
IDA
HO
IND
IAN
A
MA
INE
VIR
GIN
IA
VE
RM
ON
T
AR
IZO
NA
ILL
INO
IS
MA
RY
LA
ND
WE
ST
VIR
GIN
IA
HA
WA
II
FL
OR
IDA
UTA
H
AL
AS
KA
SO
UT
H D
AK
OTA
Findings – Medicaid Enrollment
SNF use and NH use are the dominant risks
(200% to 300% higher risk)
Three factors each increasing risk by ~ 6% to 24%:
• Prior NH use
• Hospitalizations
• Home health use
Race: black 40% to 100% higher risk
Medicaid enrollment risk, by state
0.2
0.4
0.6
0.8
1
1.2
1.4
OR
EG
ON
WA
SH
ING
TO
N
HA
WA
II
IDA
HO
IND
IAN
A
CO
LO
RA
DO
NO
RT
H C
AR
OL
INA
GE
OR
GIA
VIR
GIN
IA
WY
OM
ING
AR
KA
NS
AS
OH
IO
DE
LA
WA
RE
MIS
SIS
SIP
PI
AL
AB
AM
A
MA
RY
LA
ND
SO
UT
H C
AR
OL
INA
NE
W M
EX
ICO
IOW
A
UTA
H
CA
LIF
OR
NIA
AL
AS
KA
AR
IZO
NA
NE
VA
DA
SO
UT
H D
AK
OTA
DIS
TR
ICT
OF
CO
LU
MB
IA
FL
OR
IDA
NE
W J
ER
SE
Y
KA
NS
AS
KE
NT
UC
KY
VE
RM
ON
T
MIC
HIG
AN
CO
NN
EC
TIC
UT
TE
NN
ES
SE
E
MIN
NE
SO
TA
WE
ST
VIR
GIN
IA
TE
XA
S
MO
NTA
NA
LO
UIS
IAN
A
MA
SS
AC
HU
SE
TT
S
OK
LA
HO
MA
ILL
INO
IS
PE
NN
SY
LVA
NIA
MIS
SO
UR
I
NE
BR
AS
KA
WIS
CO
NS
IN
MA
INE
RH
OD
E IS
LA
ND
NO
RT
H D
AK
OTA
NE
W H
AM
PS
HIR
E
NE
W Y
OR
K
Haz
ard
rat
io (
rela
tive
to
Ala
bam
a)
Methodological Contributions to the CHF Literature
• Large-scale, national study of CHF population with a long follow-up (36 months).
• Survival analysis jointly accounts for utilization and mortality risk. This is important when studying elderly or high-mortality conditions. Logistic regression may give misleading impressions.
• Controlled for health status using comorbidity index and prior nursing home use.
• Controlled for area variation using state and 6-level urban influence variable. In terms of urban influence, risks hinged on large metro county residence. An urban/rural flag would incorrectly attribute practice patterns typical in large center cities to the surrounding metro areas and to smaller cities.
Conclusions
• Higher CHF rehospitalization among African Americans. Target for disease management programs?
• Bivariate findings suggest decreasing intensity of care with age. Multivariate models do not.
• Importance of more than CHF hospitalization in cohort.
• Geographic variation in utilization and health.
Main Study Limitation: Missing Data on Social Support,
Income, Functional Status
• This study had mixed findings regarding the effect (sign) of home health use on outcomes. Our findings on home health use in relation to SNF use may point to influential characteristics not available in our data: social support, individual income, and ADL information on community residents.
• The importance of these factors in understanding LTC use is well-established in the literature.
• This study’s findings suggest that these factors may be important in understanding medical use as well, when examining a chronic and ultimately debilitating disease like CHF.
Principal Investigators:
Stephanie Maxwell, PhD and Timothy Waidmann, PhD
[email protected] [email protected]
202-261-5825 202-261-5718
Health Policy CenterThe Urban Institute2100 M Street, NW
Washington, DC 20037fax: 202-223-1149
Funder: Centers for Medicare and Medicaid Services
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