Is Higher Continuity Associated
with Lower Risk of Preventable
Hospitalization?
David Nyweide, Ph.D.
Office of Research, Development, and Information at
the Centers for Medicare & Medicaid Services (CMS)
AcademyHealth Annual Research Meeting
June 27, 2010
This presentation does not necessarily reflect the official position of CMS or the
U.S. Department of Health and Human Services.
Preventable hospitalizations:
Hospitalizations attributable to disease
complications that are likely avoidable
with better ambulatory care
management.
–
–
–
–
–
–
–
–
–
–
–
Congestive heart failure (CHF)
Chronic obstructive pulmonary disease (COPD)
Diabetes
b
Hypertension
Asthma
Perforated appendix
Dehydration
Bacterial pneumonia
Urinary tract infection
Angina without procedure
Diabetic lower extremity amputation
Rates per 100,000 Adult Population
R
Preventable Hospitalization and the Elderly
2 500
2,500
2,000
1,500
1,000
500
0
18–44
45–64
65+
AHRQ, 2004
Medicare Utilization by Number of Chronic Illnesses
Number of Physicians or Visits
40
30
20
10
0
0
1
2
3
4
5+
Number of Chronic Illnesses
Average Unique Physicians
Average Physician Visits
Berenson and Horvath, 2002
Care Patterns and
Preventable Hospitalization
Care p
patterns mayy be continuous or fragmented
g
Higher continuity of care has been shown to be
associated with lower rates of hospitalization and
rehospitalization for pediatric, Medicaid, and veterans
populations (Wasson et al. 1984; Mainous and Gill
1998 Christakis
1998;
Ch i t ki ett al.
l 1999,
1999 2001)
Care patterns indicative of higher continuity may be
related to lower risk of preventable hospitalization for
Medicare patients
Continuity of care:
Degree to which a patient’s care pattern is
concentrated among physicians over time
time.
I d off C
Index
Continuity
i i off Care
C
(COC score))
– Total visits
– Total physicians
– Total visits with each physician
k

i=1
2
ni
-N
COC =
N(N - 1)
Bice and Boxerman, 1977
COC Score
COC score ranges from 0 (low) to 1 (high)
Patients with 1
1, 2,
2 or 3 visits produce spuriously
high or low scores
– ~15%
15% allll Medicare
M di
patients
ti t have
h
<4
4 visits
i it
– ~10% of chronically ill Medicare patients have <4
visits
COC score
A
B
C
Patient
0.321
(42 + 32 + 12) - 8
= 0.321
8(8 - 1)
COC score
A
B
C
Patient
D
0.250
(42 + 22 + 12 + 12) - 8
= 0.250
8(8 - 1)
COC score
A
B
C
Patient
D
0.214
(42 + 12 + 12 + 12 + 12) - 8
E
= 0.214
8(8 - 1)
Methods
Data sources
–
–
–
–
2007-2008
2007-2008
2007-2008
2007-2008
p
part
B 20% sample
p
outpatient 20% sample (RHC/FQHC)
MedPAR file (part A)
beneficiary summary file
UPIN-NPI crosswalk
– NPIs limited to physicians in Part B file
– NPIs at RHCs/FQHCs in outpatient file considered
unique
i
provider
id
AHRQ preventable hospitalization technical
specifications
Methods
Eligible if older than 65 and continuously
enrolled in fee
fee-for-service
for service Medicare with at
least 4 ambulatory evaluation and
management visits before any preventable
hospitalization
Flagged with chronic condition if claims and
coverage met or ever date and coverage met
in 2007
Methods
All beneficiaries (n = ~3,900,000)
– Any preventable hospitalization
Beneficiaries with
CHF (n = ~880,000),
~880 000)
COPD (n = ~730,000), or
diabetes (n
( = ~1,150,000)
1 150 000)
– First preventable hospitalization for particular
chronic illness
– Controlled for any other prior preventable
hospitalization
p
Analyses
Time-dependent Cox proportional hazards
regression
– COC score recalculated monthly
Patients
2007
Start
observation
period
2008
End
observation
period
Patients
COC score measurements
Start study
period
End study
period
Analyses
Time-dependent Cox proportional hazards regression
– COC score recalculated monthly
C
Covariates
i t
–
–
–
–
–
–
–
Age
Sex
Race
Dual-eligible status at any time
Illness burden ((HCC score))
Prior preventable hospitalization (CHF, COPD, diabetes)
HRR fixed effects to control for supply-side and market
characteristics
SAS-PHREG and TPHREG procedures
Analyses Summary
Main independent variable:
COC score
sco e data-derived
data de i ed terciles
te ciles of lo
low, medi
medium,
m high
continuity (lowest dropped)
Dependent variable:
Preventable hospitalization
Hypothesis: Patients with higher continuity
have lower risk of preventable hospitalization.
Medium Tercile
Risk of Preventable Hospitalization
High Tercile
All Beneficiaries
Beneficiaries with
CHF
Beneficiaries with
COPD
Beneficiaries with
Diabetes
0
Unadjusted results
0.5
Better
1.0
1.5
Worse
Medium Tercile
Risk of Preventable Hospitalization
High Tercile
All Beneficiaries
Beneficiaries with
CHF
Beneficiaries with
COPD
Beneficiaries with
Diabetes
0
Unadjusted results
0.5
Better
1.0
1.5
Worse
Medium Tercile
Risk of Preventable Hospitalization
High Tercile
All Beneficiaries
Beneficiaries with
CHF
Beneficiaries with
COPD
Beneficiaries with
Diabetes
0
Unadjusted results
0.5
Better
1.0
1.5
Worse
Medium Tercile
Risk of Preventable Hospitalization
High Tercile
All Beneficiaries
Beneficiaries with
CHF
Beneficiaries with
COPD
Beneficiaries with
Diabetes
0
Unadjusted results
0.5
Better
1.0
1.5
Worse
Medium Tercile
Risk of Preventable Hospitalization
High Tercile
All Beneficiaries
Beneficiaries with
CHF
Beneficiaries with
COPD
Beneficiaries with
Diabetes
0
Adjusted for patient and
regional characteristics
0.5
Better
1.0
1.5
Worse
Medicare Cost Savings
What would be the annual cost savings of
averted hospitalizations if patients in the
lowest continuity tercile had higher
continuity?
– Hazard ratios used to adjust hospitalization rate
before calculating differences in costs
– Medicare payment per discharge from short-stay
hospitals,
p
, 2008 ($9,390)
($ ,
)
Annual Medicare Cost Savings
Limitations
Not causality
Patients with <4 visits may have high continuity
without office visits
C i i for
Continuity
f chronically
h i ll ill may be
b better
b
measured among more than 1 “provider”
Cannot infer anything physicians or patients
may or may not being doing to affect
continuity
Implications
A patient’s ambulatory care patterns may affect
hospital utilization
Highest levels of continuity appear to have
l
largest
t benefit
b
fit
Improving continuity of Medicare patients could
save the program millions of dollars annually
Thank You