Cost Savings Associated with VA
Hospital-based
p
Palliative Care
Joan D. Penrod, PhD
James J. Peters VA
Mount Sinai School of Medicine
This work was funded by VA Health Services Research
and
dD
Development
l
tS
Service.
i
Co investigators
Co-investigators
Partha
P
th Deb,
D b PhD
Cornelia Dellenbaugh, MPH
James F. Burgess, Jr., PhD
y Zhu, PhD
Carolyn
Cindy L. Christiansen, PhD
Carol Luhrs, MD
Therese B. Cortez, NP
Elayne Livote
Livote, MPH
MPH, MS
R. Sean Morrison, MD
Background
Care off hospitalized
C
h
it li d patients
ti t with
ith advanced
d
d
disease is characterized by:
• High prevalence of pain and symptom distress
• High
g use of burdensome, non-beneficial care,
including ICU
• Inadequate communication among patients,
families, & medical team
Background
Palliative Care: Definition
• Interdisciplinary
• Assess and treat p
pain and other symptoms
y p
• Identify and discuss goals of care
Background
P lli ti C
Palliative
Care: D
Definition
fi iti
• Provide practical and psychosocial support
• Coordinate care across specialists and
settings
• Provided simultaneously with all other
appropriate medical treatment
Background
• 53% of all U.S. hospitals with 50 or more
beds have palliative care programs.
• Consultative team is most common model.
• VA issued directives and funding to establish
and expand PC consultation teams in acute
care and long-term care.
Background
Is palliative care effective?
• Systematic review in 2008 of results from 22 RCTs
found:
– Greater family satisfaction with care
– Improved
I
d quality
lit off life
lif
• Recent
R
t RCT off a nurse-led
l d PC iintervention
t
ti ffound:
d
– Higher scores for patient quality of life and mood
– No differences in symptom intensity scores
scores, days in the hospital
hospital,
ICU or emergency department visits
Background
What is the effect of PC on care costs?
• RCT of PC consultation for 448 patients from an integrated health
plan at 3 hospitals in 3 cities found:
– Lower costs overall
– Fewer ICU admissions on hospital readmission
• Observational study of 21,000 patients from 8 hospitals with wellestablished PC programs found:
– Savings of $279 in direct costs per day compared to usual care patients
Background
We hypothesized:
– Lower hospital
p
costs for patients
p
with PC
consult compared to similar patients
g usual care
receiving
Background
PC teams
t
elicit
li it goals
l off care that
th t reflect
fl t patient
ti t
and family preferences
– Less use of cardiopulmonary resuscitation (CPR)
– Fewer transfers to ICU for intubation, intravenous
p esso s
pressors
– Fewer invasive procedures
p
– More comfort care measures
Methods
Ob
Observational,
i
l retrospective
i design
d i
Study Population
• All adult patients admitted with advanced
disease to 5 VA hospitals
• October 1, 2004 to September 30, 2006
Methods
Ad
Advanced
d disease
di
–
–
–
–
–
–
–
–
Metastatic solid tumor
Central nervous system (CNS) malignancies
Metastatic melanoma
Locally advanced head and neck cancer
Locally advanced pancreatic cancer
HIV/AIDS with secondary diagnoses
C
Congestive
i h
heart ffailure
il
(CHF)
Chronic obstructive pulmonary disease (COPD)
Methods
Data Sources
• Patient characteristics and clinical
information from VHA Medical SAS
Inpatient Dataset
• Inpatient care costs from VA Decision
Support System National Data Extracts
Methods
Variables
• Key independent variable
– Binary indicator of whether the patient
received a palliative care consultation
during the hospital stay
Methods
Oth Independent
Other
I d
d t Variables:
V i bl
•
•
•
•
•
•
•
•
•
Condition/Diagnosis
Age (under 75 years, 75-84, 85 and older)
Married
Bl k white,
Black,
hit other
th
Comorbidity index
Death
Enrollment priority group
Ln(LOS)
Site
Methods
Selection problem
• Non-random
Non random assignment of patients to
treatment
• Unobserved and unmeasured patient and/or
physician factors influence both treatment and
costs
• Instrumental variable estimation to address
selection
l ti
Methods
Assumptions for IV
• Physician preference for PC varies
• Patients referred to PC by some
physicians would not be referred by other
p y
physicians
• Patient preference for medical
intervention varies
Methods
Assumptions for IV
• Because attending physicians
assigned
i
d tto patients
ti t quasi-randomly
i
d l
((2 – 4 week rotation),
) p
physician
y
characteristics are orthogonal to
patient characteristics such as
unobserved health status
Methods
Statistical Analyses
• Generalized Linear Models (GLM) (gamma
distribution with log link) to estimate the
unadjusted effect of PC consultation on costs
• Probit model to estimate the unadjusted
effect of PC consultation on the probabilityy of
an ICU stay
Methods
Adjusted
Adj
t d effects
ff t were estimated
ti t d in
i models
d l th
thatt
extend the basic framework in two ways:
• Observed characteristics introduced models
• Both models estimated with nonlinear
instr mental variables
instrumental
ariables (NLIV)
– Using simulated likelihood methods for the GLMgamma models
– Bivariate probit for ICU admissions
R
Results
l
Palliative Care
( N = 606)
Usual Care
(N = 2715)
Percent
Percent
Less than 65
28 1
28.1
33 2
33.2
65-74
21.6
24.9
75-84
33.8
31.8
85 and older
16.5
10.1
White
63 0
63.0
65 5
65.5
Black
31.0
29.2
Other
6.0
5.3
Married
34.7
33.1
0.44
1–6
90 5
90.5
90 0
90.0
0 49
0.49
7, 8
9.5
10.0
92.2
40.5
Patient Characteristics
(N= 3321)
Age, years
P Value
<0 0001
<0.0001
Race
0 50
0.50
VA enrollment priority groups
g study
yp
period
Died during
<0.0001
Palliative Care
( N = 606)
Usual Care
(N = 2715)
61.6%
15.8%
<0.0001
Chronic Obstructive Pulmonary
Disease
36.3
54.5
<0.0001
Congestive Heart Failure (CHF)
27.6
50.6
<0.0001
HIV/AIDS
31
3.1
13
1.3
0 0012
0.0012
Comorbidities, mean (SD)
2.5 (1.5)
2.5 (1.4)
0.69
Number of Hospitalizations
Hospitalizations, mean
(SD)
2 18 (1
2.18
(1.6)
6)
1 94 (1
1.94
(1.5)
5)
0 0004
0.0004
Hospitalizations (N= 6595)
Palliative Care
(N = 824)
Percent
Usual Care
(N = 5771)
Percent
Proportion with an ICU stay
32.9
37.3
0.013
Hospital Length of Stay, days, mean
(SD)
20.6 (23.3)
11.5 (15.9)
<0.0001
ICU Length of Stay, days, mean (SD)
9.7 (15.3)
5.0 (9.4)
<0.0001
Advanced Diseases:
Advanced cancer
Differences in hospital costs
for p
palliative versus usual care
Effects of Palliative Care on Costs and ICU Use
-6
60
-40
$
-20
$
-5
500 -400 -300 -20
00 -100
0
Pharmacy Cost
0
Total Direct Cost
Unadjusted
Adjusted
I-beams indicate 95% confidence intervals
Unadjusted
Adjusted
Effects of Palliative Care on Costs and ICU Use
Laboratory Cost
-60
0
-200
0
-150
-40
$
$
-100
-2
20
-50
0
0
Nursing Cost
Unadjusted
Adjusted
I-beams indicate 95% confidence intervals
Unadjusted
Adjusted
Effects of Palliative Care on Costs and ICU Use
ICU Stay
-.5
5
--20
-10
0
$
0
10
perrcentage p
points
-.4 -.3 -.2
2 -.1
0
20
Radiology Cost
Unadjusted
Adjusted
I-beams indicate 95% confidence intervals
Unadjusted
Adjusted
Discussion
• PC is
i associated
i t d with
ith llower h
hospital
it l costs
t
compared to usual care for patients with
advanced diseases
• VA findings are consistent with the recent multimulti
site RCT and the large observational study in
non-government hospitals.
• PC teams work with patients/families to establish
treatment goals and arrange care consistent
with goals.
Discussion
• Shift to lower intensity treatments
• Fewer laboratory and radiological tests
• Decreased use of the ICU
Implications
• Medically complex patients like the ones in
the study
y account for a g
growing
gp
proportion
p
of admissions and bed days
– Lower costs for PC patients could make a
big difference in hospital financial
performance
Limitations
• Data are not from an RCT: potential
selection bias
• Severity
S
it off illness
ill
• May not generalize to newly established
PC tteams and/or
d/ lless organized
i d PC
programs
Conclusions
• PC improves symptom control and family
satisfaction with hospital care while also
reducing costs compared to usual care
care.
• Expansion of palliative care programs is
indicated
Background
• Sources for potential selection bias
– Severity of illness
– Patient/family
P ti t/f il preferences
f
– Doctor attitude
• Non-referrers think patient/family too unrealistic about
prognosis
• Non-referrers do not “need” a consultant
• Referrers feel comfortable with end-of-life care issues