Higher Quality of Care for
Hospitalized Older Adults is
Associated with
Improved Survival
One Year After Discharge
Vineet Arora MD, MA, Melissa Fish BA, Anirban Basu PhD,
Jared Olson MD, Colleen Plein BA, Kalpana Suresh MS,
Greg Sachs MD, David O Meltzer MD, PhD
Academy Health Annual Research Meeting
June 29, 2009
Quality of care for hospitalized older adults

Increasing use of quality
measures for hospital care



Public reporting and pay-forperformance
Ideally, adherence to quality
measures is associated with
improved patient outcomes
Need to test and develop meaningful quality measures
for hospitalized older patients




Increasing numbers of hospitalized older patients
Greater severity of illness and more comorbidities
Different goals and preferences of health care
“Hazards of hospitalization” (i.e. delirium, pressure ulcers)
ACOVE:
Assessing Care of Vulnerable Elders

Series of if/then
statements
specifically developed
for vulnerable elders
(Wenger, 2001)

Associated with
decreased mortality
for community
dwelling elders (Higashi,
2005)

Adapted for hospitalized
older patients (Arora, 2006)

Association with patient
outcomes still unknown
Aim of study

To assess the relationship between quality
of care for hospitalized vulnerable elders
(using ACOVE quality measures) and
post-discharge mortality
Methods: patient selection

Patients age 65 and older
recruited from University of
Chicago Hospitalist Project from
May 2004 through June 2007

Excluded

Length of stay <1 day

(Meltzer, 2002)

Identified as vulnerable elders
 VES-13: 13-item Vulnerable
Elders Survey (Saliba, 2001)



Score of 3 or higher =
“vulnerable” (at greater risk
for functional decline or
death)
Died in hospital or
discharged to hospice or
comfort care

age, self-rated health,
functional ability

Hard to consider the impact
of quality of care during a
short stay
Death may not have been an
unexpected outcome
Transferred from an ICU

Greater severity of disease
Methods: Quality of Care

Chart abstraction based on select ACOVE quality
measures (Arora, 2006)

6 measures for all patients


Effort to improve mobility, discharge planning, assessment of
cognitive status, functional ability, nutritional status, and pain
10 other measures assessed only when relevant

If a patient has dementia, pressure ulcers, etc.
Methods: Mortality data

Social Security Death
Index


Publicly available
website
Used matching
algorithm based on first
and last name, date of
birth, zip code, and last
four digits of Social
Security number (Calle,
1993)

Recorded dates of
death

Able to calculate time to
death from discharge
date
http://ssdi.rootsweb.ancestry.com/
Methods: data analysis

Composite quality score (Higashi, 2006)
quality indicators met
quality score =
× 100%
quality indicators triggered

Adherence to universally applicable individual QIs

Effort to improve mobility, discharge planning,
assessment of cognitive status, functional ability,
nutritional status, and pain
Methods: data analysis

Cox proportional hazards models to test association
between quality score and mortality adjusting for:


Demographics (age, sex, race, marital status)
Markers of patient illness

Likely to have an independent effect on mortality








VES-13 score
DNR/DNI status
Charlson comorbidity score
# of quality measures triggered
length of stay
# baseline ADL limitations
clustered by attending physician
Repeated models to test association between adherence
to individual QIs and mortality
Results: patient population

Between May 2004 and June 2007
 3633 (69%) older inpatients consented
 2040 (56%) identified as vulnerable
 1861 (91%) eligible for chart review


did not die in hospital, not discharged to
hospice, not transferred from ICU
1856 (99.7%) charts reviewed
Study population (n = 1856)
Characteristic
Age in years
Mean*
79.8 ± 8.3
Female, n (%)
1281 (69%)
African-American, n (%)
1355 (73%)
Single, n (%)
1311 (71%)
Impaired cognitive status, n (%)
106 (6%)
VES-13 score
5.8 ± 2.1
Length of hospital stay in days
5.9 ± 9.0
# of ADL limitations at admission
2.7 ± 2.7
Charlson comorbidity score
1.9 ± 1.6
DNR/DNI order present, n (%)
177 (10%)
Quality of care score
59.3 ± 19.2
Died within 30 days, n (%)
114 (6.1%)
Died within 1 year, n (%)
495 (26.7%)
*Except where noted
Study population (n = 1856)
Characteristic
Age in years
Mean*
79.8 ± 8.3
Female, n (%)
1281 (69%)
African-American, n (%)
1355 (73%)
Single, n (%)
1311 (71%)
Impaired cognitive status, n (%)
106 (6%)
VES-13 score
5.8 ± 2.1
Length of hospital stay in days
5.9 ± 9.0
# of ADL limitations at admission
2.7 ± 2.7
Charlson comorbidity score
1.9 ± 1.6
DNR/DNI order present, n (%)
177 (10%)
Quality of care score
59.3 ± 19.2
Died within 30 days, n (%)
114 (6.1%)
Died within 1 year, n (%)
495 (26.7%)
*Except where noted
Cox proportional hazards regression
Hazards ratio = 0.82 (95% CI = 0.68-1.00)
p value < 0.05
Relationship between disease severity
covariates and mortality
Covariate
Cox hazards ratio
(95% CI)
p value
VES-13 score
1.09 (1.04-1.15)
<0.001
DNR/DNI status
1.89 (1.41-2.54)
<0.001
Number of QIs triggered
1.06 (1.00-1.12)
0.036
Charlson comorbidity score
1.10 (1.04-1.17)
0.002
Length of stay
1.40 (1.25-1.58)
<0.001
Number of ADL limitations
1.07 (1.03-1.12)
0.001

As predicted, sicker patients are more likely to die
Individual measures and
mortality
Quality indicator
Hazards ratio
(95% CI)
p value
Cognitive status screening
0.66 (0.39-1.10)
0.11
Functional ability screening
0.90 (0.70-1.16)
0.53
Mobility improvement plan
0.81 (0.65-1.01)
0.07
Discharge planning
0.89 (0.65-1.20)
0.43
Nutritional status screening
0.61 (0.40-0.93)
0.02
Pain assessment
0.93 (0.78-1.11)
0.42
*Derived from Cox proportional hazards regression model testing the relationship between predictor variables
& post-discharge patient mortality, adjusted for race, gender, age, marital status, VES-13 score, DNR/DNI
status, Charlson comorbidity score, number of quality indicators triggered, length of hospital stay, and number
of baseline ADL limitations
Limitations




Cannot assume causality
Could be unmeasured confounders driving
mortality
One institution
Mortality may not be the most relevant
outcome for elderly patients

Completing research examining functional
decline
Conclusions

Hospitalized older persons who receive
higher quality of care (as measured by
ACOVE quality indicators) are less likely to
die one year after discharge
Consistent with prior research on communitydwelling elders
 Association especially strong for the
assessment of nutritional status


Mechanism is unclear
Implications

Possible mechanisms for these findings:




Better quality of care improves post-discharge
survival
Inpatients that will live longer receive higher quality
of care
Adherence to certain process of care measures is a
proxy for an unmeasured variable influencing
survival
Future research needed to confirm possible
mechanisms for these findings

In particular, examining the effect of nutrition
interventions for hospitalized VE’s
Questions?
varora@uchicago.edu

Hospitalist Study
Support Staff





Korry Schwanz
Hui Tang
Ben Vekhter
Ainoa Mayo
Meryl Prochaska

Supported by:





Juned Siddique DrPH,
Northwestern University

Hartford Foundation Health
Outcomes Research
Scholars Award
1T35AG028785-01A1 NIA
Short Term Aging-related
Research Program
1U18HS016967-01 AHRQ
CERT
1 RO1 GM075292-01
NIGMS Effectiveness of
TEACH Research
Donald W Reynolds
Foundation: CHAMP
EXTRA SLIDES
Quality of Care Delivered &
Post-Discharge Mortality
Number of
Time period post- patients who died
(%)
discharge
*Quality
Odds ratio (95%
confidence
interval)†
p value
30 days
114 (6.1)
0.88 (0.76-1.02)
0.08
60 days
191 (10.3)
0.90 (0.81-1.00)
0.05
90 days
246 (13.3)
0.94 (0.86-1.04)
0.22
1 year
495 (26.7)
0.93 (0.87-1.00)
0.04
of care calculated as percent of quality indicators triggered that were actually met, here divided by 10
†Derived from multivariate logistic regression analysis, adjusting for race, gender, age, marital status, VES-13
score, DNR/DNI status, Charlson comorbidity score, number of quality indicators triggered, length of hospital
stay, and number of baseline ADL limitations
Methods: disease severity

Measures of disease severity







Age
VES-13 score
Number of ADL limitations
}
Assessed in initial
study recruitment
interview
DNR/DNI status
Length of hospital stay
Number of quality measures for
which a patient is eligible
Charlson comorbidity score
}
Assessed in
chart abstraction