Factors Associated With 28-Day Hospital Readmission
After Stroke in Australia
Monique F. Kilkenny, MPH; Mark Longworth, BNA; Michael Pollack, M Clin Epi;
Christopher Levi, MBBS; Dominique A. Cadilhac, PhD; on behalf of New South Wales Stroke
Services Coordinating Committee and the Agency for Clinical Innovation
Downloaded from http://stroke.ahajournals.org/ by guest on June 15, 2017
Background and Purpose—Understanding the factors that contribute to early readmission after discharge following stroke
is limited. We aimed to describe the factors associated with 28-day readmission after hospitalization for stroke.
Methods—Factors associated with readmission were classified from the medical record standardized audits of 50 to 100
consecutively admitted patients with stroke from 35 Australian hospitals during multiple time periods (2000–2010).
Factors were compared between patients readmitted and not readmitted after stroke hospitalization (n=43) grouped
using 5 categories: patient characteristics (n=16; eg, age), clinical processes of care (n=13; eg, admitted into a stroke
unit), social circumstances (n=3; eg, living home alone prior), health system (n=6; eg, location of hospital), and health
outcome (n=5; eg, length of stay). Multilevel logistic regression modeling was used to examine the association with these
independent factors selected if statistical significance P<0.15 or if considered clinically important and readmission status.
Results—Among 3328 patients, 6.5% were readmitted within 28 days (mean age, 75; 48% female; 92% ischemic). After
bivariate analyses 14/43 factors from 4/5 categories were associated with readmission after hospitalization for stroke.
Two factors from patient and health outcome categories remained independently associated with readmission after
multivariable analyses. These were dependent premorbid functional status (adjusted odds ratio, 1.87; 95% confidence
interval, 1.25–2.81) and having a severe adverse event during the initial hospitalization for stroke (adjusted odds ratio,
2.81; 95% confidence interval, 1.55–5.12).
Conclusions—This is the first study to comprehensively evaluate factors associated with 28-day readmission after stroke.
The factors associated with 28-day readmission are diverse and include potentially modifiable and nonmodifiable
factors. (Stroke. 2013;44:2260-2268.)
Key Words: Australia ◼ complications ◼ length of stay ◼ hospital readmission ◼ stroke
S
troke is an important condition for understanding the
likely factors that contribute to avoidable readmissions.
This is because stroke is a leading cause of hospitalizations,
deaths, and disease burden. In Australia, among older people
aged ≥75 years stroke is the leading cause of hospitalization.1
Hospitalizations for patients with stroke are expensive.2
Information on the reasons why hospital readmissions
occur within 1 month after discharge following an admission
for stroke is limited. Readmission can be an important outcome of the quality of hospital care for patients with stroke.3,4
Readmissions within 1 month of discharge may reflect unresolved problems at discharge,5 the quality of immediate post–
hospital care, a more chronically ill population, or because of
a combination of these factors.6 A study in the United States
provided evidence that patients with acute stroke who were
readmitted within 30 days had a worse chance of survival and
incurred greater healthcare costs than patients who were not
readmitted.7 Preventing avoidable readmissions may reduce
costs to the healthcare system.8
Several studies have been undertaken to examine the frequency of readmissions within 1 month of discharge after
stroke, mainly from the United States, Australia, Denmark,
and Taiwan (Table 1).3–5,8–15 Common data sources used to
calculate hospital readmissions rates include Medicare data,
registry data, patient interviews, or medical records. Evidence
from these studies show that the frequency of hospital readmissions may vary from 6.5% to ≈24.3%.3–5,8–15
The potential factors that may be associated with being
readmitted after an initial hospitalization for stroke can be
grouped into 5 broad categories: patient characteristics, social
Received December 17, 2012; accepted May 6, 2013.
From the Department of Medicine, Translational Public Health Unit, Stroke and Ageing Research, Southern Clinical School, Monash University, Clayton,
Victoria, Australia (M.F.K., D.A.C.); Stroke Division, The Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia (M.F.K.,
D.A.C.); Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia (M.F.K., D.A.C.); Agency for Clinical Innovation, Stroke
Services New South Wales, Greater Metropolitan Clinical Taskforce, NSW Health, Sydney, NSW, Australia (M.L.); Department of Neurology, Hunter
Agency for Clinical Innovation, Stroke Service, Hunter New England Area Health, New Lambton Heights, NSW, Australia (M.P., C.L.); and Centre for
Brain and Mental Health Research, University of Newcastle and Hunter Medical Research Institute, New Lambton, NSW, Australia (M.P., C.L.).
Correspondence to Dominique A. Cadilhac, PhD, Department of Medicine, Translational Public Health Unit, Stroke and Ageing Research, Southern
Clinical School, Monash University, Level 1/43-51 Kanooka Grove, Clayton, Victoria, Australia. E-mail [email protected]
© 2013 American Heart Association, Inc.
Stroke is available at http://stroke.ahajournals.org
DOI: 10.1161/STROKEAHA.111.000531
2260
Kilkenny et al Factors Associated With Readmission After Stroke 2261
Table 1. Summary of Literature of the Factors Found to be Associated With Early* Readmission After Stroke
Country, Author,
Year
Australia,
Roe,14 1996
Estimated
No. of
No. of
Factors
Data Source Patients Frequency Investigated
Medical
records
USA, Camberg,5 Medicare data
1997
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USA, Smith,8
2005
Taiwan, Chuang,4
2005
USA, Smith,15
2006
Patient
Characteristics
Clinical
Processes of
Care
Outcome
Social Circumstances
Health System
264
6.5
7 factors
…
…
Influenced by
treating unit
(P=0.02, log-linear
analysis)
…
…
2261
16.6
15 factors
>3 prior
hospitalizations for
patients (no data
presented)
…
Proximity of home to
the hospital (no data
presented)
…
Longer length
of stay (no data
presented)
32% patients
discharge
Veteran Affairs
nursing home vs
16% discharged
home (RR,
1.1; 95% CI,
0.7–1.6)
12.9
29 factors
…
…
Medicare HMO
(15%) vs FFS (13%;
HR, 1.29; 95% CI,
1.09–1.52)
…
…
…
Need for wound
nursing care
(OR, 3.3; 95%
CI, 1.3–7.9);
need for other
invasive nursing
care (OR, 2.6;
95% CI, 1.0–
6.6) adopted a
care plan (OR,
3.4; 95% CI,
1.8–6.5)
…
Medicare data 44 099
Patient
interviews
489
24.3
20 factors
Medicare data
9003
14.0
27 factors
…
…
Patients seen
by neurologist
borderline lower risk
(HR, 0.91; 95% CI,
0.82–1.01)
Patients seen by
neurologists had
12% lower risk of
rehospitalization for
infections (HR, 0.88;
95% CI, 0.78–0.99)
and aspiration
pneumonitis but
17% higher risk for
rehospitalization
for heart disease
(HR, 1.17; 95% CI,
1.02–1.34)
…
…
14.5
15 factors
…
…
Joint Commission
certified hospitals
(13.8%) vs
noncertified
hospitals (14.6%);
adjusted (HR, 0.97;
95% CI, 0.95–0.99)
…
…
USA, Lichtman,13 Medicare data 3 66 551
2009
Activities of daily Carer arrangements
living limitations after discharge: family
(OR, 8.6; 95% care (OR, 4.5; 95% CI,
CI, 2.4–30.6);
1.7–11.7); full-time
first-time stroke helper (OR, 10.1; 95%
(OR, 2.4; 95% CI,
CI, 3.8–25.9)
1.4–4.1)
(Continued)
2262 Stroke August 2013
Table 1. Continued
Country, Author,
Year
USA,
Bhattacharya,3
2011
USA, Howrey,10
2011
Estimated
No. of
No. of
Factors
Data Source Patients Frequency Investigated
Medical
records
265
11.5
Social Circumstances
Health System
Clinical
Processes of
Care
22 factors History of coronary
artery disease
(45.5% vs 14.7%;
P<0.001)
…
…
…
Discharge
rehabilitation or
nursing home
vs home or
rehabilitation
(23.8% vs
8.2%; P<0.01)
NIHSS≥10
(50.0% vs
25.4%; P<0.02)
Patient
Characteristics
Outcome
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Medicare data 10 884
…
28 factors
…
…
Readmission
rates were higher
for patients in
hospitalist care
vs nonhospitalist
(HR, 1.30; 95% CI,
1.11–1.52)
…
…
Registry data 14 545
Denmark,
Langagergaard,11
2011
9.1
26 factors
…
Unemployed (HR, 1.17;
95% CI, 1.00–1.37)
or pensioner patients
(HR, 1.33; 95% CI,
1.13–1.57)
…
…
…
Taiwan, Li,12
2011
National Health 1194
Insurance
9.9
22 factors
…
…
…
Antiplatelets
(HR, 0.06) or
anticoagulants
(HR, 0.15)
prescribed
within 1-m
index admission
discharge
reduced
readmission
rates at 1 m
…
USA, Fonarow,9
2012
Medicare data 91 134
14.1
25 factors
…
…
Academic hospitals
in West had slightly
better readmission
rate 13.3 vs
South or Midwest
hospitals 14.5% and
Northeast 14.3%
…
…
*Twenty-eight– or 30-day readmission. CI indicates confidence interval; FFS, fee-for-service; HMO, Health Maintenance Organizations; HR, hazard rate; NIHSS,
National Institute of Health Stroke Scale; OR, Odds ratio; and RR, Relative risk.
circumstances, health system, clinical care or process, and
health outcome (Figure 1). A recent systematic review and
other subsequent studies investigating factors associated
with readmission after stroke have focused on <30 factors,
which fall mainly within patient or health system categories
(Table 1).3,9–12 Investigators have generally used Medicare data
and have assessed <3 clinical care or process variables, such
as discharge medication, admitted into a stroke unit, and readmission after stroke.
Since 2004, the New South Wales Stroke Audit Program
has been used to monitor patient characteristics, social circumstances, health system, adherence to clinical processes of
care, and outcomes before and after stroke unit implementation within hospitals.16,17 The detailed data available from this
large study provided a unique opportunity to explore many
factors and their potential association with early readmission
after an initial hospitalization for stroke.
The aim of this study was to describe the factors associated with readmission after a hospitalization for stroke and
determine whether there are any modifiable factors. Our primary hypothesis was that quality of care factors, in addition
to patient and system factors, can explain differences between
patients with stroke who were readmitted within 28 days and
those who were not readmitted.
Methods
Data were obtained on patients with acute stroke who were admitted to New South Wales hospitals between 2000 and 2010 at various
Kilkenny et al Factors Associated With Readmission After Stroke 2263
PATIENT
HEALTH
OUTCOME
e.g. length of stay,
discharged home,
any severe
complication
CHARACTERISTICS
e.g. age, gender,
history of risk
factors, stroke
severity, stroke
type
SOCIAL
CIRCUMSTANCES
e.g. live alone,
marital status
READMISSION
FACTORS
CLINICAL
PROCESSES OF
CARE e.g. stroke
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unit care,
assessed by allied
health, brain
imaging
Figure 1. Categories of factors that may be associated with readmission for patients with stroke.
HEALTH SYSTEM
e.g. location of
hospital, treating
doctor
time periods. Methods of data collection and patient eligibility for
this study have been previously published.16,17 In brief, consecutive
medical record audits were conducted by trained data abstractors
working at the hospitals using a validated data collection tool. Patient
eligibility criteria were as follows: confirmed diagnosis of a first-ever
or recurrent stroke admission to hospital for acute management and
readmission status known (that is cases with unknown or missing information for this question were excluded). On the rare occasion a
medical record was not available, then those patients were substituted
for the next consecutive patient until the desired sample size was
reached for that hospital. All audit data were independently processed
and analyzed by externally based research staff.
Readmitted patients were defined as those readmitted to the same
hospital within 28 days of discharge for an initial hospitalization for
stroke. After careful review of the readmission records, auditors documented in free text, the primary cause for the readmission, referred to
here as the readmission diagnosis. The readmission diagnoses for this
study were then sorted into consistent disease categories by a medically trained research officer. Separate questions determined whether
the readmission was related to the previous admission for stroke, the
length of stay, and whether the patient was discharged from hospital
for that admission
Data Analysis
The variables selected for our analyses were based on findings from
our literature review (Table 1) and our earlier research using this data
set.16,17 Our literature review (Table 1) involved identifying previous
studies investigating early readmission after stroke. Each of the articles was reviewed to estimate the number of factors investigated.
Only key findings were highlighted under each of 5 identified broad
categories.
The initial bivariate analyses included 43 factors (listed in Table 2)
that we grouped according to the 5 categories (Figure 1) as outlined
below:
1. Patient characteristic factors: n=16, including variables used to
account for stroke severity on the basis of a validated prognostic model developed for predicting stroke outcome.18 These
included arm weakness, impaired speech, inability to walk on
admission, and incontinence in the first 72 hours. Dependence
on admission and before stroke was defined according to the
modified Rankin Scale (2–5).
2. Social circumstances factors: n=3.
3. Health system factors: n=6.
4. Clinical processes of care factors: n=13 with brain imaging defined as receiving a computed tomography or MRI scan.
5.Health outcomes: n=5 the modified Rankin Scale was used
to define level of dependence on discharge with being dependent classified as modified Rankin Scale 3 to 519 equivalent to
moderate to severe disability. Severe complications during the
initial hospitalization were defined as events determined to be
incapacitating, life-threatening, and prolonging the hospital
admission and patient acuity (eg, falls, urinary tract infection,
aspiration pneumonia, other chest infection, decubitus ulcer,
deep vein thrombosis, stroke progression, second stroke, and
myocardial infarct).
χ-square tests were used for categorical variables and the Wilcoxon
Mann–Whitney rank-sum test for continuous variables for bivariate
analyses.
Random effects multilevel, logistic regression models were used
with level defined as hospital. Readmission status was defined as the
dependent variable. A parsimonious approach to model development
was used where independent variables with clinical importance or
statistical significance (P<0.15) from bivariate analyses were used.
Standard techniques were implemented to check for collinearity and
the fit of various models were compared using Bayesian Information
Criteria. Level of dependence on admission and discharge was collinear with 90% of patients dependent on admission and discharge.
Therefore, in the final model we included only the dependent on admission variable. Stata (version 10.1; StataCorp, College Station, TX,
2010) statistical software was used for all analyses and P values of
<0.05 were considered significant. Adjusted odds ratio (OR) and 95%
confidence intervals (CIs) were calculated.
Results
Of the 4139 patients with acute stroke included in this study, the
median age was 74 years (Q1–Q3, 67–83); 50% were women;
92% had an ischemic stroke; 66% had first-ever stroke; and
90% had been discharged from hospital. Readmission status was unknown or missing for 11% of discharged patients.
There was no difference in patient characteristics, such as age,
or being dependent before admission for those where readmission status was known compared with patients whose readmission status was unknown. Patients with stroke were admitted
from 35 Australian hospitals during multiple time periods
2264 Stroke August 2013
Table 2. Patient Characteristics, Social Circumstances, Health System, Clinical Processes of Care and Health Outcome Factors for
Hospital Readmission Within 28 Days
Factor
Not Readmitted
n (%) n=3113
Readmitted
n (%) n=215
P Value
Patient characteristics
Median age (Q1–Q3)*
76 (66–83)
77 (67–84)
0.15
Sex women*
1532 (50)
101 (47)
0.51
Australian*
2302 (76)
170 (80)
0.19
Dependent before admission (modified Rankin Scale, 2–5)*
797 (27)
80 (39)
<0.001
Atrial fibrillation†
654 (23)
52 (28)
0.19
Hypercholesterolemia†
934 (34)
67 (36)
0.61
1957 (67)
136 (68)
0.81
Diabetes mellitus†
654 (23)
55 (28)
0.09
Ischemic heart disease†
789 (28)
68 (34)
0.042
Previous stroke or TIA†
980 (34)
74 (36)
0.43
Hypertension†
Patient stroke sub-type classification*
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Ischemic stroke
2851 (94)
191 (92)
0.19
Total anterior circulation infarct
415 (14)
28 (13)
…
Partial anterior circulation infarct
1178 (39)
84 (40)
…
Lacune infarct
878 (29)
45 (22)
…
Posterior circulation infarct
380 (13)
34 (16)
…
Hemorrhagic stroke
181 (6)
17 (8)
…
1973 (66)
130 (65)
0.68
Weak arm (SSS score: 0, 2, 4, or 5)*
2190 (72)
137 (68)
0.14
Unable to walk on admission (SSS gait score: 1, 2, 4, or 5)‡
1144 (58)
63 (65)
0.07
Incontinent <72-h admission*
1096 (37)
92 (45)
0.013
1582 (55)
104 (53)
0.66
800 (27)
55 (27)
0.99
21 (1)
1 (<1)
0.71
Stroke severity variables
Impaired speech (SSS speech score: 0, 3, 6)*
Social circumstances
Married or with partner before admission†
Lived alone (before admission)
Discharge delay because family unprepared
Health system
Rural hospital
1424 (48)
116 (55)
0.037
Median onset time to arrival (Q1–Q3)*
7 (2–22)
4 (2–15)
0.16
Median arrival to admission (Q1–Q3)
8 (5–12)
8 (5–11)
0.29
Stroke unit establishment/implementation
1477 (47)
102 (47)
0.99
Neurologist, principal treating doctor
1049 (35)
61 (29)
0.11
479 (16)
28 (13)
0.33
CT scan or MRI (<24 h)
2807 (91)
179 (84)
0.001
Documentation of swallowing (<24 h)§
1348 (68)
88 (68)
0.88
Assessed by physiotherapist (<48 h)*
1725 (55)
124 (58)
0.48
Assessed by speech pathologist (<48 h)*
1858 (60)
132 (62)
0.62
Assessed by occupational therapist (<48 h)*
1052 (34)
76 (35)
0.60
Frequent neurological observations (<24 h)
2076 (68)
148 (71)
0.35
Any care in a stroke unit during admission
1239 (40)
87 (41)
0.85
92 (57)
4 (50)
0.70
403 (13)
25 (12)
0.57
Discharge delay
Clinical processes of care
Admitted to intensive care unit
Family meeting within 7 d*
Clinical pathway or management plan*
1120 (36)
76 (36)
0.75
Aspirin given (<24 h), if ischemic stroke
1803 (64)
112 (59)
0.15
(Continued)
Kilkenny et al Factors Associated With Readmission After Stroke 2265
Table 2. Continued
Not Readmitted
n (%) n=3113
Factor
Self-management care plan on discharge*
Appropriate discharge strategy*
Readmitted
n (%) n=215
P Value
420 (14)
28 (14)
0.92
1550 (51)
95 (46)
0.09
1446 (48)*
93 (47)†
0.88
45 (1)
3 (1)
0.52
1921 (63)
149 (72)
0.007
136 (4)
18 (8)
0.007
Health outcomes
Discharged home
Palliative care
Dependent at discharge (modified Rankin Scale, 3–5)*
Any severe complication
Median length of stay in days (Q1–Q3)
8 (5–15)
9 (4–18)
0.41
CT indicates computed tomography; Q1, 25th percentile; Q3, 75th percentile; SSS, Scandinavian Stroke Scale; and TIA, transient ischemic attack.
*<5% missing data.
†5% to 10% missing data.
‡11% to 15% missing data.
§If admitted with impaired speech.
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(2000–2010). Quality of care received improved for patients
admitted to stroke units (5%–69%; P<0.001) and receiving
computed tomography or MRI scan within 24 hours (84%–
96%; P<0.001) during this decade. Outcomes improved during this period with an increase in patients discharged home
(54%–69%; P=0.03).
Readmissions to Hospital Within 28 Days of
Discharge
Of the 3328 discharged patients with known readmission status 6.5% (95% CI, 3.2–9.7) were admitted to the same hospital
within 28 days. The reasons for readmissions are summarized
in Figure 2, with the majority being for a stroke or cardiovascular disease. The median length of stay for the readmission
was 6 days (Q1–Q3, 2–12). Among the readmitted patients
with discharge status recorded, 10% died during the readmission. The frequency of readmissions remained constant during
the time period ranging from 4% to 19% (P=0.68).
Findings From the Descriptive Analyses of Factors
Table 2 shows that many of the patient characteristics and
social circumstances of readmitted patients were similar to
those who were not readmitted. However, readmitted patients
were more likely to have a documented history of ischemic
heart disease, be incontinent in the first 72 hours of admission
and be dependent before admission for the initial hospitalization compared with patients not readmitted.
Differences in the health system, clinical care, and health
outcome factors for patients with stroke who were readmitted and not readmitted to hospital are provided in Table 2.
Management on a stroke unit did not differ for readmitted
patients compared with those not readmitted, even during the
poststroke unit implementation period. However, we found
that readmitted patients were less likely to receive brain imaging within 24 hours of the initial admission when compared
with patients who were not readmitted, but overall a similar
proportion had brain imaging during their admission. On further examination, we noted that patients who did not receive
brain imaging within 24 hours were more likely to have been
admitted to a rural hospital (11%) compared with an urban
hospital (6%; P<0.001). However, there was no statistically
significant difference among patients in rural or urban hospitals receiving brain imaging during their stroke admission, but
more rural patients had their scans done at different locations
Stroke
Cardiovascular disease
Others†
Cardinal manifestation
Surgical procedures
Respiratory disease
Falls and fracture
Figure 2. Primary reason for readmission. †For
example, sepsis or palliative care.
Renal disease
Gastrointestinal disease
Neurological and mental disorders
Endocrinological & metabolism disorders
Cancer
Ulcer and wound
0
5
10
15
Percent
20
25
2266 Stroke August 2013
*
Any severe complication
Myocardial infarction
*
*
Recurrent stroke
Stroke progression
Deep vein thrombosis
Decubitus ulcer
Figure 3. Adverse events or complications by readmission status. *Only a single primary reason for the
readmission was recorded for each patient.
Other chest infection
Aspiration pneumonia
Urinary tract infection
Fall
0
2
Readmitted
4
6
Per cent
8
10
12
Not readmitted
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than the hospital where they were admitted for stroke (50%
rural versus 10% urban), and this may have caused time
delays. There were no differences among patients who
received timely scans and whether they arrived after-hours to
the hospital compared with those that did not receive a scan
within 24 hours.
Patients who were readmitted were more likely to have
been dependent at discharge and experience ≥1 or more severe
complications during their initial hospitalization for stroke
compared with patients not readmitted (Figure 3). Patients
with severe complications had longer lengths of stay (median,
13 days) compared with patients without severe complications
(median 8 days, P<0.001). Patients with severe complications
were also more likely to be dependent at time of admission
(OR, 1.6; 95% CI, 1.2–1.9) or discharge (OR, 9.3; 95% CI,
5.0–17.2).
Findings From Multivariable Analyses
The factors that remained significantly associated with patients
being readmitted within 28 days included being dependent
before the initial admission and experiencing a severe complication during the admission (Table 3). Our measures of stroke
severity were not independent predictors of readmission in our
adjusted model.
When we restricted our analyses to patients with no history
of prior stroke, being dependent before the initial admission
(OR, 2.1; 95% CI, 1.3–3.5) and experiencing a severe complication during the admission (OR, 3.3; 95% CI, 1.6–6.7)
retained significance when all the potential factors associated
with readmission were included in the model.
Discussion
This is the first study to have comprehensively assessed a
large and broad range of factors that may be associated with
readmissions and to determine whether there were any differences in the quality of care received by patients on the basis of
readmission status. The results provided evidence that patients
who were being readmitted were generally receiving the same
quality of care during the initial hospitalization as patients
who were not readmitted. Our summary of the literature noted
only 1 study by Chuang et al4 that found associations with
clinical processes of care, such as need for wound care nursing
or other invasive nursing care and adopting a care plan with
early readmission after stroke. In our study, we found only 1
potential difference, which had borderline significance in the
quality of care factors that differed for readmitted patients.
Readmitted patients tended to receive fewer brain scans within
24 hours of admission compared with patients who were not
readmitted. This result could not be explained by differences
in time of arrival to hospital. However, patients admitted to
rural hospitals in our sample were less likely to receive timely
imaging because these services are often not collocated. Early
brain imaging is required to confirm type of stroke, commence
time-dependent therapies effective within the first 24 hours
and to exclude stroke mimics.20
Table 3. Factors Associated Hospital Readmission Within 28
Days*
Factors
Odds Ratio
95% CI
P Value
Age at stroke
0.93
0.57–1.53
0.78
Men
1.04
0.73–1.51
0.79
Dependent before admission (modified
Rankin Scale, 2–5)
1.87
1.25–2.81
0.002
Diabetes mellitus
1.02
0.67–1.56
0.93
Ischemic heart disease
1.36
0.92–2.02
0.12
Weak arm
0.70
0.46–1.07
0.10
Impaired speech
0.72
0.49–1.06
0.10
Unable to walk on admission
0.82
0.54–1.26
0.38
Incontinent <72-h admission
1.19
0.77–1.83
0.43
No CT scan or MRI <24 h
1.78
1.00–3.14
0.047
No appropriate discharge strategy
1.09
0.72–1.66
0.68
Managed by neurologist
1.12
0.68–1.82
0.66
Treated in a rural hospital
1.21
0.73–2.00
0.46
Any severe complication†
2.81
1.55–5.12
0.001
Model statistics: BIC 1084, AIC 993; CI indicates confidence interval; CT,
computed tomography.
*Adjusted for all factors listed in table; level was hospital.
†Any severe complication includes falls, urinary tract infection, aspiration
pneumonia, other chest infection, decubitus ulcer, deep vein thrombosis; stroke
progression, second stroke, and myocardial infarct.
Kilkenny et al Factors Associated With Readmission After Stroke 2267
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In our study, we investigated nonmodifiable factors, such as
patients being dependent (having a moderate to severe disability) before their initial stroke admission. We found patients
had a nearly 2-fold greater chance of being readmitted if they
were dependent. It is interesting that the stroke severity variables we used did not seem to be an independent predictor
of readmission. Hospitals treating patients with stroke should
flag dependent patients as at risk of readmission. The level of
dependence at discharge for stroke was also associated with
readmission within 28 days. This indicates that these patients
who are frailer or have more severe strokes because of greater
comorbidity have a greater chance of readmission. Any other
interventions aimed at preventing 28-day readmissions should
place more attention on those with a moderate to severe disability. Hospitals should consider whether these patients might
benefit from staying in hospital longer or ensure adequate
transitions to other healthcare services after discharge from
an acute hospital setting to prevent unplanned readmission.21
We also investigated potentially modifiable factors, such as
patients with stroke experiencing a severe complication during admission. We found that patients had a ≈3-fold greater
chance of being readmitted if they had experienced a severe
complication. Our study showed that the likelihood of a severe
complication or adverse event increases if you are dependent
before stroke or have a severe disability after stroke. Hospitals
treating patients with stroke should flag dependent patients
before admission as at risk of severe complications and readmissions. Greater vigilance and monitoring may be warranted
so that preventable serious adverse events, such as urinary
tract infections or falls, are avoided. Targeted intervention
programs need to be developed to increase efforts at prevention of complications during admission, especially for patients
who were dependent at admission.
Short-term readmissions to hospitals are a worldwide problem. In the United States, Medicare is following readmission
data closely. In other disease states, such as chronic heart failure, readmissions have been tied to reduced reimbursements
to hospitals.22 One recommendation from our study is that
hospitals treating patients with stroke should flag patients who
experienced a severe complication during admission. These
patients should be targeted for early outpatient follow-up after
discharge, as there is recent evidence that these arrangements
can potentially reduce readmissions.23
In Australia, data on factors related to readmissions for
patients admitted with stroke are limited. The strength of our
study is that we were able to use a large data set from a diverse
range of hospitals within New South Wales, Australia. Other
studies have used administrative data sets and were unable to
include a large range of variables covered within the 5 categories we have identified. A limitation of our study was that we
were only able to ascertain factors related to readmissions to
the same hospital. Therefore, our readmission numbers may
be an underestimate if patients within a geographical region
went to a different hospital. In our sample, only 5% of patients
had been transferred to the participating hospital from a different hospital for their initial stroke admission. It may be
possible that some of these people did not return to the participating hospital for a readmission. Furthermore, we did not
exclude planned readmissions because this information was
not collected. On review of our data, there were potentially 8
readmissions that might be considered a planned readmission
(1 for carotid endarterectomy, 1 for permanent pace-maker,
and 6 for percutaneous gastrostomy tube insertion). In contrast, the studies using linked administrative Medicare data
were able to look at factors associated with readmissions to
any hospital and whether the readmissions were planned or
unplanned. However, it has been shown that 81% of readmission within 30 days are admitted to the same hospital
after a major disease event.24 Future studies are underway in
Australia linking Registry data with administrative hospital
data to explore further the factors associated with readmissions for patients with stroke to all hospitals.
Conclusions
This is the first time a large number of factors have been
explored to assess potential modifiable and nonmodifiable
factors associated with readmission. Our study showed that
severe complications, which are potentially modifiable, were
independently associated with a risk of readmission. Given
the growing cost burden of stroke on healthcare systems, this
study provides important information for clinicians, health
administrators, and policy makers to identify patients at risk of
readmission. Use of the categories outlined in this study will
facilitate future comparative and comprehensive approaches
for investigating this topic.
Acknowledgments
We acknowledge New South Wales (NSW) Health State-wide services development branch for funding the NSW stroke audit program. We also acknowledge L. Cutler and the NSW Rural Institute
of Clinical Services and Training for their support of the rural audit
initiative. We also acknowledge the hospital staff, stroke care coordinators, and area directors across Stroke Services NSW Network
for supporting this work. The authors thank research assistants for
their contribution to data processing from the Florey Institute of
Neuroscience and Mental Health and L.C. Quang for her contribution to database management. A/Prof L. Churilov for advice on the
multivariable modeling. We thank Dr B. Amatya for recoding all the
readmission diagnoses into discrete categories.
Disclosures
None.
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Factors Associated With 28-Day Hospital Readmission After Stroke in Australia
Monique F. Kilkenny, Mark Longworth, Michael Pollack, Christopher Levi and Dominique A.
Cadilhac
on behalf of New South Wales Stroke Services Coordinating Committee and the Agency for
Clinical Innovation
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Stroke. 2013;44:2260-2268; originally published online June 25, 2013;
doi: 10.1161/STROKEAHA.111.000531
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