Diagnostic Procedures, Treatments, and Outcomes in Stroke
Patients Admitted to Different Types of Hospitals
Kjell Asplund, MD; Maria Sukhova, MSc; Per Wester, MD; Birgitta Stegmayr, PhD;
on behalf of the Riksstroke Collaboration*
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Background and Purpose—In many countries, including Sweden, initiatives have been taken to reduce between-hospital
differences in the quality of stroke services. We have explored to what extent hospital type (university, specialized
nonuniversity, or community hospital) influences hospital performance.
Methods—Riksstroke collects clinical data during hospital stay (national coverage 94%). Follow-up data at 3 months
were collected using administrative registers and a questionnaire completed by surviving patients (response rate 88%).
Structural data were collected from a questionnaire completed by hospital staff (response rate 100%). Multivariate
analyses with adjustment for clustering were used to test differences between types of hospitals.
Results—The proportion of patients admitted directly to a stroke unit was highest in community hospitals and lowest
in university hospitals. Magnetic resonance, carotid imaging, and thrombectomy were more frequently performed in
university hospitals, and the door-to-needle time for thrombolysis was shorter. Secondary prevention with antihypertensive
drugs was used less often, and outpatient follow-up was less frequent in university hospitals. Fewer patients in community
hospitals were dissatisfied with their rehabilitation. After adjusting for possible confounders, poor outcome (dead or
activities of daily living dependency 3 months after stroke) was not significantly different between the 3 types of hospital.
Conclusions—In a setting with national stroke guidelines, stroke units in all hospitals, and measurement of hospital
performance and benchmarking, outcome (after case-mix adjustment) is similar in university, specialized nonuniversity,
and community hospitals. There seems to be fewer barriers to organizing well-functioning stroke services in community
hospitals compared with university hospitals. (Stroke. 2015;46:806-812. DOI: 10.1161/STROKEAHA.114.007212.)
Key Words: Riksstroke ◼ stroke ◼ thrombolytic therapy
H
differences in outcome is differences in case-mix. In some
previous studies, the use of routine administrative registers
has limited the ability to adjust for differences in key prognostic variables, such as stroke severity at onset.
Compared with low-volume hospitals, high-volume hospitals provide, on average, more evidence-based services to
acute stroke patients. These services include diagnostic procedures, acute treatment, such as thrombolysis, aspects of nursing, early rehabilitation, and secondary prevention.10–12 In the
United States, the “Get With The Guidelines Stroke Program,”
hospital certification programs, and recognition programs are
associated with higher conformity with care measures for
acute stroke patients.13
With the exception of the Danish study,10 previous studies
on hospital volume have been performed in settings where
stroke units have not followed a national standard. In Sweden,
all hospitals admitting acute stroke patients have a dedicated
stroke unit (Table I in the online-only Data Supplement).
ospital performance is often assessed at 3 levels: structure, processes, and outcomes,1 with case fatality being
the most commonly available measure of stroke outcome.2
Hospitals with many stroke patients (high-volume hospitals)
have been reported to have a lower 7-day case fatality3,4 or
lower in-hospital stroke case fatality5–7 compared with hospitals with fewer stroke patients (low-volume hospitals). In
the United States, greater spending on hospitals is also associated with lower risk-adjusted inpatient stroke case fatality.8,9
A recent national study from Denmark, however, failed to
demonstrate any relationship between stroke case volume and
30-day or 1-year case fatality after adjusting for differences in
case-mix between hospitals.10
Between-hospital differences in early stroke case fatality are
usually attributed to differences in the quality of acute stroke
care provided (although the scientific evidence for a direct
link between hospital performance and stroke outcome is not
robust2). Another possible explanation for between-hospital
Received September 15, 2014; final revision received December 12, 2014; accepted December 26, 2014.
From the Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University, Sweden.
*See the online-only Data Supplement for details.
The online-only Data Supplement is available with this article at http://stroke.ahajournals.org/lookup/suppl/doi:10.1161/STROKEAHA.
114.007212/-/DC1.
Correspondence to Kjell Asplund, MD, Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University, SE-90185 Umeå,
Sweden. E-mail [email protected]
© 2015 American Heart Association, Inc.
Stroke is available at http://stroke.ahajournals.org
DOI: 10.1161/STROKEAHA.114.007212
806
Asplund et al Stroke Procedures and Outcomes by Hospital Type 807
National stroke guidelines under the auspices of the National
Board of Health and Welfare are available. Riksstroke, a hospital performance register, includes benchmarking of stroke
processes and outcomes in all hospitals.
In the dissemination of new medical technology, the prevailing view is that university hospitals are, in general, early
adopters and community hospitals are, on average, later
adopters. However, the complexity of university hospitals
may negatively affect factors, such as patient satisfaction and
follow-up visits. In this study, we explored to what extent differences in stroke care procedures and outcomes among university, large nonuniversity, and community hospitals exist.
Methods
Downloaded from http://stroke.ahajournals.org/ by guest on June 14, 2017
Patients presenting with acute stroke between January 1, 2012, and
December 31, 2013, and who were recorded in The Swedish Stroke
Register (Riksstroke), were included in the study. The primary aim
of this national register was to monitor and support improvement in
quality of stroke care in Sweden. The register, established in 1994,
covers all hospitals in the country admitting acute stroke patients (72
hospitals in 2012 and 2013). The Riksstroke follow-up procedures
include linkage to the national Cause of Death Register and a questionnaire to surviving patients 3 months after stroke (response rate
87.6% in 2012–2013). Details on the organization, funding, data collection, and reporting and description of variables are available at the
Riksstroke Web site (http://www.riks-stroke.org/index.php?content=
&lang=eng&text=). This study has been approved by the Regional
Ethical Review Board at Umeå University (Dnr 2013/353-31).
Of all patients discharged from Swedish hospitals in 2012 and
2013 with a diagnosis of acute stroke in routine administrative registers, 88.2% were recorded in Riksstroke. Allowing for the estimated
6% false-positive diagnosis of acute stroke in Swedish routine administrative registers,14 the actual coverage of the register is estimated to
be 94%.
Basic characteristics of acute stroke services in Sweden with emphasis on patient allocation to different types of hospital are described
in Table I in the online-only Data Supplement. In the present study,
hospitals were categorized as university hospitals (n=9, mean 562
admissions per year during 2012–2013, range 291–879), specialized nonuniversity hospitals (n=22; mean 507 admissions, range
209–1139), and community hospitals (n=41; mean 204 admissions,
range 64–389). The delineation between specialized nonuniversity
hospitals and community hospitals was determined by their degree
of specialization; community hospitals have only basic inpatient specialities (typically internal medicine, surgery, anesthesiology, x-ray
department, and a laboratory). Large nonuniversity hospitals have
a wider range of specialities and provide more advanced diagnostic
procedures (eg, various magnetic resonance diagnostics) and interventions (eg, carotid surgery).
Stroke patient volume was categorized by quartiles with 18 hospitals in each category; Q1, 64 to 170 admissions; Q2, 201 to 263
admissions; Q3, 291 to 436 admissions; Q4, 439 to 1139 admissions
per year.
In Sweden, acute stroke care is centralized only to a limited extent.
For example, thrombolysis is performed in 69 of the 72 hospitals,
and patients are seldom referred to a tertiary (university) hospital
except for neurosurgery or endovascular procedures. Between 2012
and 2013, 2621 patients (5.3%) were treated in >1 hospital. In the
Riksstroke register, the patient is assigned to the hospital where he/
she spends most of the acute hospital stay.
In April 2013, a 34-item questionnaire addressing structural aspects of stroke care was distributed to the 72 hospitals admitting acute
stroke patients. All hospitals responded. We used this information to
describe stroke unit care in the 3 types of hospitals.
Riksstroke uses definitions agreed upon by the Stroke Unit Trialists’
Collaboration15,16 and the European Stroke Initiative17 to define a dedicated stroke unit. In Riksstroke, the level of consciousness is used as
a proxy for stroke severity. Based on the Reaction Level Scale (RLS
85),18 Riksstroke classifies patients as alert (RLS 1), drowsy (RLS
2–3), or unconscious (RLS 4–8). Recordings of patient-reported
outcomes (mood, self-assessed general health, and satisfaction with
care) have been described in previous publications.19,20
Statistical Analyses
In univariate analyses of hospital type (university hospitals, specialized nonuniversity hospitals, and community hospitals), χ2 tests for 2×3
cross-tables were used for binary variables. Proportions and means are
presented with corresponding 95% confidence intervals within different
hospital type. In 2 multiple logistic regression models (with and without stroke patient volume), independent predictors of the probability of
poor outcome (dead or activities of daily living [ADL] dependency 3
months after stroke) were analyzed. To adjust for the fact that observations on individual patients within one and the same hospital may not
be entirely independent on each other (clustering), we used generalized
estimating equations with an exchangeable correlation structure. It was
used in univariate analyses, as well as in multiple logistic regression
models. Possible presence of multicollinearity in the models was assessed by calculating variance inflation factors. The analyses were performed with the statistical software IBM SPSS Statistics 22.
Role of the Funding Source
The funders of Riksstroke had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. The
corresponding author had full access to all the data in the study and
had final responsibility for the decision to submit for publication.
Results
Hospital and Patient Characteristics
In 2012 to 2013, the Riksstroke register recorded 49 144
admissions for acute stroke from 72 hospitals. Of these, 9 were
university hospitals, 22 were specialized nonuniversity hospitals, and 41 were community hospitals. Table 1 shows some
basic characteristics of the 3 types of hospitals. According to
self-assessments, the great majority of hospitals of all types
fulfilled the basic set of stroke unit criteria. The number of
stroke unit beds per population in the hospital catchment area
was twice as high in community hospitals compared with that
in university hospitals. A dedicated stroke care coordinator
was less common in community hospitals, whereas a routine
for early multidisciplinary rehabilitation was less common in
university hospital stroke units.
Patient characteristics in the 3 types of hospital are shown
in the Table II in the online-only Data Supplement. Patients
admitted to university hospitals were on average 2 years
younger than patients admitted to nonuniversity hospitals.
In university hospitals, a higher proportion were ADL independent before the index stroke, and a lower proportion were
recorded to have hypertension. The proportions of patients
with intracerebral hemorrhage and a lowered level of consciousness (as a proxy for stroke severity) were highest in university hospitals.
Processes
For acute stroke patients admitted to community hospitals,
it was significantly more common that they were admitted
directly to specialized stroke care (stroke unit, intensive care
unit, or transferred to a neurosurgical unit) compared with
patients admitted to university or specialized nonuniversity
hospitals. When instead stroke unit care during more than half
808 Stroke March 2015
Table 1. Characteristics of University, Specialized
Nonuniversity, and Community Hospitals Between 2012 and
2013
Table 2. Stroke Care Procedures Used in Patients Treated
in University, Specialized Nonuniversity, and Community
Hospitals
Hospital Type
University
Hospital Type
Specialized
Nonuniversity
Community
No. of hospitals
9
22
41
No. of patients
10 109
22 295
16 740
No. of stroke unit
beds,* mean
22
21
13
No. of stroke unit
beds per 100 000
in the hospital
catchment area,
mean
8.8
13.5
17.8
University
Specialized
Nonuniversity
Community
P Value
Direct admission 7572 (75.2%;
to specialized
74.4–76.0%)
stroke care*
16 851 (75.9%;
75.3–76.5%)
13 565 (81.4%; 0.032
80.8–82.0%)
Stroke unit care 8771 (86.8%;
more than half of 86.1–87.5%)
hospital stay
20 299 (91.1%;
90.7–91.4%)
15 604 (93.2%; 0.154
92.8–93.6%)
16 453 (98.4%; 0.673
98.2–98.6%)
Imaging
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Annual no. of
admission for
acute stroke, mean
(range)
562 (291–879)
Fulfilling stroke unit
criteria, by selfassessment, %
89 (63–100)
86 (71–100)
93
(84–100)
Stroke care
coordinator, %
89 (63–100)
100 (100–100)
66 (51–81)
Routine use of
patient monitoring
schemes, %
100 (100–100)
100 (100–100)
95 (88–100)
Routine for early
multidisciplinary
rehabilitation in the
unit, %
78 (44–100)
CT scan
9865 (98.5%;
98.2–98.7%)
21 885 (98.2%;
98.1–98.4)
MRI
2127 (21.3%;
20.5–22.1%)
3230 (14.6%;
14.1–15.0%)
2329 (14.0%;
13.4–14.5%)
0.042
10 531 (54.4%;
53.7–55.1%)
7587 (52.3%;
51.5–53.1%)
0.027
507 (209–1139) 204 (64–389)
100 (100–100)
98 (93–100)
Data gathered from the Riksstroke database and questionnaire responses
from the hospitals. Range is given in parentheses.
*Several stroke units reported a flexible number of beds. Minimum numbers
of beds are reported. The mean number of extra beds was 2 to 3 per unit.
of the hospital was tested, the differences between hospital
types were not significant (Table 2).
The proportion of stroke patients examined by computed
tomography scan was high (>98%) in all types of hospital.
In contrast, the proportion examined by magnetic resonance
imaging (MRI) was considerably higher in university hospitals than that in nonuniversity hospitals, whether specialized
or not (Table 2). In addition, the proportion of patients with
ischemic stroke examined by any type of carotid artery imaging was highest in university hospitals.
The proportion of patients with ischemic stroke treated by
thrombolysis was somewhat higher in university hospitals than
that in nonuniversity hospitals (Table 2). Median door-to-needle
time for patients treated with thrombolysis was on average 12
minutes shorter in university hospitals and 8 minutes shorter in
specialized nonuniversity hospitals compared with that in community hospitals. In Sweden, thrombectomy is performed only
in university hospitals, and some patients from other hospitals
are referred to university hospitals for the procedure (Table 2).
Because there are large local variations in the organization
of stroke services, we report the total length of hospital stay (ie,
the time spent in acute care hospitals plus time spent in rehabilitation or geriatric units). Median length of total hospital stay
Carotid artery 5340 (63.3%;
imaging in
62.3–64.4%)
patients with
ischemic stroke
Thrombolysis,
ischemic stroke
18–80 y,
and ADL
independent
before stroke
686 (13.9%;
13.0–14.9%)
1256 (12.2%;
11.6–12.8%)
912 (11.7%;
11.0–12.4%)
0.268
All patients
989 (11.7%;
11.0–12.4%)
1883 (9.7%;
9.3–10.1%)
1296 (8.9%;
8.5–9.4%)
0.084
Median doorto-needle time in
thrombolysis, min
(IQR; Q1–Q3)
46 (29–70)
50 (36–70)
58 (39–80)
0.001*
Thrombectomy,
ischemic stroke
18–80 y, ADL
independent
260 (5.3%;
4.7–5.9%)
124 (1.2%;
1.0–1.4%)
53 (0.7%;
0.5–0.9%)
<0.001
Length of hospital
stay (total†)
Mean, d
16.0 (15.6–16.3) 14.8 (14.6–15.0) 14.4 (14.1–14.6) 0.436
Median, d (IQR; 9.0 (4–20)
Q1–Q3)
Secondary
prevention at
discharge: any
antithrombotic
drug in patients
with ischemic
stroke
7051 (92.5%;
91.9–93.1%)
Oral
1082 (51.9%;
anticoagulants 49.7–54.0%)
in patients with
ischemic stroke
and atrial
fibrillation
9.0 (5–20)
16 368 (93.2%;
92.8–93.6%)
2581 (52.7%;
51.3–54.1%)
9.0 (5–18)
0.136*
12 214 (93.3%; 0.597
92.8–93.7%)
1911 (54.0%;
52.4–55.6%)
0.934
(Continued)
Asplund et al Stroke Procedures and Outcomes by Hospital Type 809
Table 2. Continued
Hospital Type
University
Specialized
Nonuniversity
Statins in
patients with
ischemic
stroke
4963 (65.1%;
64.0–66.2%)
11 814 (67.3%;
66.6–68.0%)
Antihypertensive
agent,
all patients
6438 (73.8%;
72.9–74.7%)
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Outpatient
follow-up by
physician or
stroke nurse
within 3
months,
patientreported
Community
P Value
8812 (67.3%;
66.5–68.1%)
0.555
Table 3. Multivariate Analysis of Patients Treated in
University, Specialized Nonuniversity, and Community
Hospitals With Poor Stroke Outcome (Dead or ADL Dependent
3 Months After Stroke) as the Dependent Variable
95% CI
P Value
OR
Lower
Upper
Community
0.253
0.90
0.75
1.08
Specialized
nonuniversity
0.162
0.88
0.73
1.05
1.10
1.41
0.91
1.02
Hospital type
15 296 (78.1%;
77.5–78.7%)
11 626 (79.3%; 0.041
78.6–79.9%)
University
3113 (78.5%;
77.2–79.7%)
7922 (83.5%;
82.7–84.2%)
6133 (84.2%;
83.4–85.1%)
0.233
P values tested in a GEE model, taking clustering of hospitals into account.
ADL indicates activities of daily living; CT, computed tomography; IQR,
interquartile range; and MRI, magnetic resonance imaging.
*Median of continuous variable, not possible to test in the GEE model, logistic
regression model used, ie, clustering of hospitals has not been taken into account.
†Length of stay in acute hospital plus inpatient rehabilitation or inpatient
geriatric services.
was identical in the 3 types of hospital, whereas mean length
of stay was 1.6 days longer in university hospitals than that
in community hospitals. There were no clinically meaningful
differences between the 3 types of hospitals with respect to
prescription of secondary prevention drugs at discharge from
hospital, except for antihypertensive drugs that were prescribed significantly more often in patients discharged from
nonuniversity than those from university hospitals (Table 2).
The proportion with an outpatient follow-up visit to a physician or a stroke nurse was lower in university hospitals than
that in the 2 other hospital types (Table 2; nonoverlapping 95%
confidence intervals but nonsignificant P value).
Death and ADL Dependency
A somewhat larger proportion of surviving patients had poor
outcome (death from ADL dependency) at 3 months after
stroke if they had initially been admitted to a university hospital rather than a nonuniversity hospital, but after adjustment
for clustering the differences were not statistically significant
(Table IV in the online-only Data Supplement).
In a multivariate statistical model that included case-mix
variables and hospital type and was adjusted for clustering,
poor outcome (death or ADL dependency 3 months after
stroke) was similar in the 3 types of hospital (Table 3).Other
factors associated with increased risk of poor outcome in the
multivariate model were high age, being ADL dependent
before the index stroke, living alone, and a history of stroke,
diabetes mellitus, and atrial fibrillation (Table 3). The risk
of poor outcome was strongly associated with a diagnosis
of intracerebral hemorrhage and lowered consciousness at
admission.
Ref.
Transferred to
another hospital
Yes
<0.001
No
1.24
Ref.
Sex
Men
0.180
0.96
Ref.
Women
Age group, y
<50
<0.001
0.07
0.06
0.09
50–59
<0.001
0.12
0.10
0.13
60–69
<0.001
0.15
0.14
0.17
70–79
<0.001
0.25
0.22
0.27
80–89
<0.001
0.49
0.45
0.54
0.07
0.09
1.00
1.11
1.38
1.57
0.92
1.02
1.35
1.51
1.30
1.48
0.95
1.11
≥90
Ref.
ADL independent
before index stroke
Yes
<0.001
No
0.08
Ref.
Living alone
Yes
0.034
1.06
Ref.
No
Previous stroke
Yes
<0.001
No
1.47
Ref.
Hypertension
Yes
0.257
No
0.97
Ref.
Diabetes mellitus
Yes
<0.001
No
1.43
Ref.
Atrial fibrillation
Yes
<0.001
No
1.39
Ref.
Smoking
Yes
No
0.527
1.03
Ref.
(Continued)
810 Stroke March 2015
Table 3. Continued
P Value
OR
Lower
Upper
inflation factor was 2.18 for both hospital type and stroke
patient volume, indicating some degree of multicollinearity.
For all other variables, the variance inflation factor was ≤1.36
(absence of multicollinearity).
Intracerebral
hemorrhage
<0.001
2.06
1.91
2.23
Other Out.comes
Undetermined
0.569
1.15
0.70
1.89
95% CI
Stroke subtype
Ischemic
Ref.
Level of
consciousness on
admission
RLS 4–8
(unconscious)
<0.001
21.63
17.77
26.33
RLS 2–3
(drowsy)
<0.001
6.70
5.90
7.59
RLS 1 (alert)
Ref.
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OR (95% CI), adjusted for clustering by generalized estimating equations
(GEE). ADL indicates activities of daily living; CI, confidence intervals; OR, odds
ratio; and RLS, Reaction Level Scale.
In an additional multivariate model, hospitals were subdivided by stroke patient volume into quartiles (Table III
in the online-only Data Supplement). After adjustment for
clustering, there were no significant differences in poor outcome between high volume (439–1139 admissions per year;
reference), medium-high volume (291–436 admissions per
year; odds ratio, 0.87; 95% confidence interval, 0.74–1.03),
medium-low (201–263 admissions per year; odds ratio, 0.89;
95% confidence interval, 0.74–1.06), and low-volume hospitals (64–170 admissions per year; odds ratio, 0.97; 95%
confidence interval, 0.79–1.18). In this model, the variance
Table 4. Satisfaction With Care, Mood, General Health,
and Smoking Cessation in Patients Treated in University,
Specialized Nonuniversity, and Community Hospitals
Hospital Type
University
Specialized
Nonuniversity
Community
P Value
Dissatisfied
with in-hospital
stroke care
296 (5.0%;
4.5–5.6%)
689 (4.9%;
4.5–5.2%)
444 (4.2%;
3.8–4.5%)
0.386
Dissatisfied
with
rehabilitation
after discharge
from hospital
404 (11.5%;
10.5–12.6%)
983 (10.7%;
10.1–11.4%)
537 (7.5%;
6.9–8.1%)
0.001
Low mood,
no (%)
3660 (59.7%;
58.5–61.0%)
9015 (61.8%;
61.0–62.6%)
6446 (58.0%;
57.0–58.9%)
0.045
Low selfassessed
general health
1413 (23.8%;
22.7–24.8%)
3447 (23.9%;
23.2–24.6%)
2198 (19.9%;
19.2–20.7%)
0.007
Smoking
cessation
385 (42.7%;
39.5–46.0%)
938 (45.2%;
43.0–47.3%)
675 (42.2%;
41.7–46.7%)
0.526
Percentages with 95% confidence intervals adjusted for clustering by
generalized estimating equations.
The great majority of patients in all types of hospitals
reported that they were satisfied with the care they had
received in hospital and the rehabilitation they had received
after discharge. The proportion of patients who were dissatisfied with the acute in-hospital care was similar in the
3 types of hospitals, whereas dissatisfaction with rehabilitation after discharge from hospital was significantly more
common in patients treated in university and specialized
university hospitals than in those treated in community hospitals (Table 4). A lower proportion of community hospital
patients reported their general health as poor 3 months after
stroke, whereas similar proportions reported some degree of
low mood in the 3 types of hospital. The rates of smoking
cessation 3 months after stroke did not differ substantially
by type of hospital.
Discussion
Our results show important differences in stroke services and
management among university, nonuniversity, and community
hospitals, and these differences are not always in the favor
of university hospitals. Whereas nonintensive stroke units are
established in all acute hospitals in Sweden, patient access to
stroke units is better in community hospitals than that in university hospitals. However, patients treated in university hospitals are more often investigated using MRI, are more often
having their carotid arteries examined, have shorter door-toneedle times for thrombolysis, and are more often treated by
thrombectomy. After adjusting for differences in case-mix,
hospital type is not associated with the risk of poor outcome
(dead or ADL dependency 3 months after stroke). Further
adjustment for stroke patient volume did not affect the main
results.
A strength of this study is that it is nationwide with up-todate information and that all hospitals in the country admitting
acute stroke patients are covered. As acute care hospitals in
Sweden have reasonably well-defined catchment areas and are
all publicly financed, there is minimal risk of active patient
selection by ability to pay. The coverage of all acute stroke
patients admitted to hospital is high (see Methods). Extensive
validations of the data submitted to Riksstroke have not indicated any systematic differences in data quality between
different types of hospitals (Riksstroke, unpublished). The
case-mix, including prevalence of risk factors, is similar to
what has been reported in other large-scale studies, for example, the US Get With The Guidelines project21 and the UK
Oxfordshire Community project,22 except that atrial fibrillation is a more prominent risk factor in the Swedish population.
Most previous studies have only reported on case fatality as
outcome. Our study, however, also included functional outcome. The Riksstroke database has permitted more complete
case-mix adjustments than in studies based on routine administrative data only.
Asplund et al Stroke Procedures and Outcomes by Hospital Type 811
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A limitation of the present study is that data on stroke care
structure (Table I in the online-only Data Supplement) were
self-reported by the hospitals and not validated. A further
limitation is that there may be some residual confounding
although major factors known to be prognostic were included
in the statistical models of outcome. Socioeconomic data,
except being married/cohabitant versus single, were not collected. It should also be noted that most Swedish community
hospitals have higher stroke patient volumes than reported
from other countries (eg, ref. 3–5).
To some extent, a different patient mix in university hospitals may explain the differences in procedures by type of
hospital. The lower mean age and more pronounced stroke
severity at onset may have contributed to a higher proportion of patients undergoing MRI scanning and carotid artery
imaging and receiving thrombolysis. The longer mean (but not
median) stay in university hospitals could possibly indicate
higher proportions of patients with severe stroke. An alternative interpretation is that it reflects less-than-optimal interactions between hospitals and community services in large cities
with university hospitals. Despite adjustment for the most
common prognostic factors in the regression models, some
residual unmeasured confounding cannot be excluded.
Remarkably, there is a 6% unit difference in favor of community compared with university hospitals in patients’ access
to direct stroke unit admission. It seems that community
hospitals give higher priority to stroke patients than university hospitals do, at least in terms of number of stroke unit
beds per population in the hospital catchment area. The large
proportion of patients in university and specialized university hospitals not admitted directly to specialized stroke care
(stroke unit, intensive care unit, or transferred to a neurosurgical unit) indicates organizational deficits in large hospitals.
Patient dissatisfaction with rehabilitation is also more common in university and specialized nonuniversity hospitals than
that in community hospitals, and patients treated in university
hospitals are less often followed up after discharge. These
observations indicate that there are more barriers when organizing well-functioning stroke services in complex university
hospital settings. It also seems that stroke care suffers because
of the strong internal competition for resources in university
hospitals.
The moderate differences in stroke care procedures and
outcomes between different types of hospitals should be seen
in the context of how the quality improvement in stroke care
has developed in Sweden during the past 2 decades. The first
version of national guidelines for stroke care was issued by
a governmental agency in 1990s, and these guidelines have
been regularly updated. A national system for benchmarking
of hospital performance (Riksstroke) has been in operation
since the mid-1990s, with all hospitals admitting acute stroke
patients participating since 1998.23 A large set of performance
indicators is publicly available.
One of the aims of the national guidelines and the benchmarking of hospital performance has been to reduce regional
and between-hospital differences in stroke care quality. A previous study that used Riksstroke data has shown a considerable delay in adopting new technologies, such as thrombolysis
in community hospitals.11 The present data show that differences still exist, but they are modest. Major differences now
exist for MRI scanning and thrombectomy. Only a minor
fraction of patients first admitted to a community hospital are
referred to a larger hospital for these procedures.
After adjusting for case-mix and clustering, the risk of poor
outcome was similar in the 3 types of hospital. The similarities
in outcome after case-mix adjustment suggest that the various
differences in quality of stroke management counterbalance
each other. It seems reasonable that this counterbalance is,
in part, the result of the emphasis on national guidelines and
measurements of hospital performance with publicly available
benchmarking.
We observed, however, that, independent of hospital type
and case-mix and after adjustment for clustering, the outcome
was similar in high-volume and low-volume hospitals. This
finding agrees with findings from a nationwide Danish study10
but not with most other studies on stroke patient volume.3–9 It
seems that, in some contexts, it is possible to uphold the same
quality of stroke care in small as in large hospitals.
Summary and Conclusions
Patients admitted to university hospitals, compared with
community hospitals, are less often admitted directly to specialized stroke services and are more often dissatisfied with
rehabilitation after discharge from hospital. Patients in university hospitals have better access to diagnostic procedures, and
the in-hospital delay to thrombolysis is shorter. After adjusting
for differences in case-mix, stroke patient outcome is similar
in university and community hospitals. The Swedish setting
with national stroke guidelines, stroke units in all hospitals,
measurement of hospital performance, and publicly available benchmarking may have helped eliminate differences in
outcome between types of hospitals. There seems to be fewer
barriers to organizing well-functioning stroke services in community hospitals compared with those in university hospitals.
Sources of Funding
Riksstroke is funded by the Ministry of Health and the Swedish
Association of Local Authorities and Regions.
Disclosures
None.
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Diagnostic Procedures, Treatments, and Outcomes in Stroke Patients Admitted to
Different Types of Hospitals
Kjell Asplund, Maria Sukhova, Per Wester and Birgitta Stegmayr
on behalf of the Riksstroke Collaboration
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Stroke. 2015;46:806-812; originally published online February 5, 2015;
doi: 10.1161/STROKEAHA.114.007212
Stroke is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231
Copyright © 2015 American Heart Association, Inc. All rights reserved.
Print ISSN: 0039-2499. Online ISSN: 1524-4628
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Data Supplement (unedited) at:
http://stroke.ahajournals.org/content/suppl/2015/02/05/STROKEAHA.114.007212.DC1
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SUPPLEMENTAL MATERIAL
Diagnostic procedures, treatments and outcomes in stroke patients admitted to
different types of hospitals
Kjell Asplund, Maria Sukhova, Per Wester, Birgitta Stegmayr for the Riks-Stroke
Collaboration*
Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University,
Umeå, Sweden
Supplemental tables
Supplemental Table I. Description of acute stroke services in Sweden with emphasis on allocation of patients to
different types of hospital.
Item
Ownership and financing of
hospitals admitting acute
stroke patients
Patient fees
General rule of allocation of
stroke patients
Stroke units
Thrombolysis
Thrombectomy
Neurosurgery
Follow-up after hospital stay
Description
71 hospitals publicly owned, 1 hospital privately owned but stroke care is
publicly financed.
Patients pay a small nominal fee for hospital stay (approximately 13 USD per
day a maximum of 160 USD over a 30-day period); the fee is the same for all
types of hospital.
Each hospital serves a defined population (geographical catchment area); acute
stroke patients are transported to or seeking this hospital.
Dedicated stroke units are established in all 72 hospitals admitting acute stroke
patients. The great majority are fulfilling the stroke unit criteria defined by the
Stroke Unit Trialists’ Collaboration15,16 and the European Stroke Initiative17
(see Table 1).
Stroke thrombolysis is performed in 69 of the 72 hospitals. Patients from 1
large non-university hospital and 2 community hospitals are transferred to
university hospitals for thrombolysis; after the procedure, they are usually
transferred back to their home hospital. In the present study, patients are
allocated to the hospital where they spent most of their hospital stay.
Performed in 6 of the 9 university hospitals. In 2013, 94 of 232
thrombectomies were performed in patients from another hospital’s catchment
area. After the intervention, patients are usually transferred back to their home
hospital. In the present study, patients are allocated to the hospital where they
spend most of their hospital stay.
Selected stroke patients are transferred to one of the 6 neurosurgical facilities
in Sweden for hemicraniectomy or hematoma evacuation. In 2013, 42 patients
were transferred to neurosurgical clinics. In the present study, these patients
are allocated to the hospital they were first admitted to.
Procedures for follow-up vary by patient groups and hospitals. Nationwide,
the first follow-up visit is in a hospital out-patient clinic in 34 % and in a
primary health care center in 34 % (Riksstroke annual report 2013).
1 Supplemental Table II. Characteristics of patients treated in university, large non-university, and
community hospitals between 2012 and 2013. Number of patients and percentages with 95% CIs, adjusted
for clustering by generalized estimating equations (GEE).
Hospital type
Age, mean (95% CI)
Sex, male
Living alone
ADL independent before index stroke
University
Specialized nonuniversity
Community
P value
73.9 (73.6-74.1)
76.0 (75.8-76.2)
76.2 (76.0-76.4)
0.010
5336 (52.8%;
11327 (50.8%;
8737 (52.2%;
51.8 - 53.8)
50.2-51.5)
51.4-53.0)
4803 (48.0 %)
11466 (51.8 %)
8309 (49.8 %)
47.0-48.9)
51.1-52.4)
49.0-50.5)
8890 (90.0%;
19015 (87.8%;
14221 (86.4%;
89.4-90.5%)
87.4-88.2%)
85.9-87.0%)
2282 (22.9%;
5465 (24.6%;
3971 (23.8%;
22.1-23.7%)
24.1-25.2%)
23.2-24.5%)
5855 (58.7%;
13567 (61.4%;
10856 (65.1%;
57.8-59.7%)
60.8-62.0%)
64.3-65.8)
1986 (19.9%;
4661 (21.0%;
3655 (21.9%;
19.1-20.7%)
20.5-21.5%)
21.2-22.5%)
2802 (28.1%;
6491 (29.3%;
4826 (28.9%;
27.2-28.9%)
28.7-29.9)%
28.2-29.6%)
1305 (14.4%;
2885 (14.1%;
2013 (12.7%;
13.7-15.1%)
13.6-14.6%)
12.2-13.2%)
8530 (84.4%;
19412 (87.1%;
14538 (86.8%;
83.7-85.1%)
86.6-87.5%)
86.3-87.4)
1495 (14.8%;
2567 (11.5%;
1987 (11.9%;
14.1-15.5%)
11.1-11.9%)
11.4-12.4%)
0.092
0.070
0.017
Medical history
previous stroke
hypertension
diabetes
atrial fibrillation
smoking
0.039
0.005
0.090
0.690
0.176
Stroke subtype
ischemic
Intracerebral haemorrhage
undetermined
Lowered level of consciousness on admission (RLS
>=2)
84 (0.8%;
316 (1.4%;
215 (1.3%;
0.65-1.0%)
1.3-1.6%)
1.1-1.5%)
2071 (20.9%;
3511 (16.0%;
2825 (17.1%;
20.1-21.7%)
15.5-16.5%)
16.5-17.6%)
0.104
0.018
0.072
0.083
2 Supplemental Table III. Multivariate analysis, including also stroke patient volume, of patients
treated in university, specialized non-university, and community hospitals with poor stroke
outcome (dead or ADL dependent three months after stroke) as the dependent variable. Odds
ratios (95% CI), adjusted for clustering by generalized estimating equations (GEE).
Hospital type
Community
Specialized non-university
University
Stroke patient volume
Low (Q1)
Medium-low (Q2)
Medium- high (Q3)
High (Q4)
Transfer from another hospital
Yes
No
Sex
Men
Women
Age group
< 50
50-59
60-69
70-79
80-89
>= 90
ADL independent before index
stroke
Yes
No
Living alone
Yes
No
Previous stroke
Yes
No
Hypertension
Yes
No
Diabetes
Yes
No
Atrial fibrillation
Yes
No
95 % CI
Lower
Upper
P value
OR
0.58
0.23
0.94
0.90
Ref.
0.74
0.75
1.18
1.07
0.73
0.20
0.10
0.97
0.89
0.87
Ref.
0.79
0.74
0.74
1.18
1.06
1.03
0,001
1,24
Ref.
1,09
1,40
0.18
0.96
Ref.
0.91
1.02
<0.001
<0.001
<0.001
<0.001
<0.001
0.07
0.12
0.15
0.25
0.49
Ref.
0.06
0.10
0.14
0.23
0.45
0.09
0.13
0.17
0.27
0.54
<0.001
0.08
Ref.
0.07
0.09
0.04
1.06
Ref.
1.00
1.11
<0.001
1.47
Ref.
1.38
1.57
0.25
0.97
Ref.
0.92
1.02
<0.001
1,42
Ref.
1,34
1,51
<0.001
1,39
Ref.
1,30
1,47
3 Smoking
Yes
No
Stroke subtype
I61
I64
I63
Level of consciousness on admission
RLS 4-8
RLS 2-3
RLS 1
0.52
1.03
Ref.
0.95
1.11
<0.001
0.59
2.05
1.15
Ref.
1.90
0.70
2.22
1.88
<0.001
<0.001
21.72
6.69
Ref.
17.76
5.89
26.58
7.60
Supplemental Table IV. Univariate analyses of case fatality and poor outcome in patients treated in
university, specialised non-university, and community hospitals in 2012-2013. Numbers and percentages
with 95 % confidence intervals. P values adjusted for clustering by generalized estimating equations (GEE).
Hospital type
P value
University
Specialized nonuniversity
Community
815 (8.7%;
8.12-9.26%)
1600 (7.7%;
7.33-8.05%)
1224 (7.7%;
7.30-8.13%)
0.662
1876 (21.9%;
21.01-22.77%)
3791 (19.4%;
(18.82-19.93%)
2899 (19.4%;
18.81-20.08%)
0.208
Poor outcome 3 months after stroke (dead or 1545 (24.1%;
23.03-25.12%)
ADL dependent)
3260 (22.1%;
2522 (22.6%;
21.41-22.75%)
21.80-23.10%)
Case fatality
7 days
3 months
0.105
4 Appendix. The Riksstroke Collaboration.
Members of the Board
Bo Norrving, Lund University (chair), Peter Appelros, Örebro University Hospital, Daniela Bjarne, STROKERiksförbundet (patient representative), Wania Engberg, NÄL Hospital, Trollhättan, Mia von Euler, Karolinska
Institute, Stockholm, Birgitta Stegmayr, Umeå University Hospital, Andreas Terént, , Uppsala University
Hospital, Sari Wallin, Riksstroke office, Umeå, Mariann Ytterberg (patient representative), Västerås
Working group
Birgitta Stegmayr (superintendent), Sari Wallin (national coordinator), Åsa Johansson (research nurse), Fredrik
Jonsson (statistician), Maria Hals Berglund (statistician), Maria Sukhova (statistician), Per Ivarsson (project
administrator), Eva-Lotta Glader (research consultant), Marie Eriksson (statistical consultant).
Participants
Akademiska/Uppsala
Hultman Anki, Lisa Jonsson
Karolinska Solna
Anita Hansson Tyrén
Alingsås
Brita Eklund, Annika Emilsson, Maria
Ekholm, Anna Lindh, Ida Abrahamsson
Arvika
Anna Lena Wall
Kiruna
Anita Stockel‐Falk, Monica Sahlin, Marit
Edén
Kristianstad
Lena Eriksson, Cia Caplander, Anna Hansson
Avesta
Åsa-Lena Koivisto, Else-Marie Larsson,
Bitte Pettersson, Taina Ylitalo
Bollnäs
Maj Fröjd, Lena Parhans
Kullbergska/Katrineholm
Britt‐Marie Andersson, Christina Petersson
Sunderbyn
Ann‐Louise Lundgren, Ulla Jarlbring
Kungälv
Maria Berglund, Eva Eriksson
Sundsvall
Barbro Högvall, Ewa Edin
Borås
Hillevi Grändeby, Marianne Hjalmarsson,
Elisabeth Arvidsson, Camilla HarénNilsson, Sibylla Carlsson
Capio S:t Göran/ Stockholm
Pirjo Perduv, Bo Höjeberg, Eva Rosso,
Gabriella Strandberg
Danderyd/Stockholm
Berit Eriksson, Ann-Charlotte Laska
Köping
Ann Hedlund, Lotta Ruin, Therese
Kanthergård, Jan Saaf
SUS Lund
Karina Hansson, Gunilla Nilsson,
Hélène Pessah-Rasmussen
Landskrona
Eva-Lotta Persson, Birgitta Jeppsson,
Jessica Johansson
Lidköping
Ingrid Roland, Anita Söderholm,
Kerstin Bjälkefur, Sofia Wahll
Lindesberg
Anette Eriksson, Vigdis Welander
SUS Malmö
Penny Baaz, Hélène Pessah‐Rasmussen,
Elisabeth Poromaa
Södersjukhuset (SÖS)/Stockholm
Cecilia Schantz-Eyre, Emma WeckströmWadling
Södertälje
Inger Davidsson
Falun
Helen Eriksson, Carin Hedlund,
Monica Eriksson, Joakim Hambraeus,
Ann-Jeanette Melin
Gällivare
Karin Johansson, Barbro Juuso
Linköping
Caroline Nilsen, Ann-Christine Josefsson,
Gunnie Green
Torsby
Anna‐Lena Halvardsson, Åsa Valfridsson,
Corina de Wijs
Ljungby
Elisabeth Nyman, Maria Linnerö
Gävle
Christina Andersson, Maria Smedberg
Lycksele
Cecilia Ölmebäck
Trelleborg
Ingela Fröjdh, Agneta Kristenssen, Ramona
Vuoristo
Umeå
Åsa Olofsson, Maria Fransson
Halmstad
Monica Karlsson, Kerstin Larsson,
Jessica Noren, Christine Billfors
Helsingborg
Marie Mikkelsen, Annica Fristedt
Mora
Marianne Bertilsson, Inger Boije
Varberg
Ing‐Marie Thyr, Lisa Nilsson
Hudiksvall
Maj Britt Johansson
Motala
Anette Grahn, Anette Gunninge,
Britt‐Louise Lövgren, Ulf Rosenqvist
Mälarsjukhuset/Eskilstuna
Yvonne Kentää, Camilla Jansson
Visby
Eva Smedberg, Anna Westberg-Bysell,
Åsa Lindblad, Åsa Lövgren, Susanna Grönborg
Värnamo
Marie Andersson, Mats Altesjö
Hässleholm
Erika Ekholm, Anna Zenthio, Magnus
Esbjörnsson
Mölndal
Eva-Britt Giebner, Helen Zachrisson,
Linda Alsholm
Västervik
Maud Lindqvist, Britt-Marie Martinsson
Enköping
Ann-Kristin Kinander
SkaS Skövde
Eric Bertholds, Ann‐Catrine Elgåsen,
Björn Cederin, Eva Åkerhage
Skellefteå
Helena Olofsson, Ann-Charlotte Johnsson
Sollefteå
Solveig Velander, Inger Jonsson
5 Höglandssjukhuset/Eksjö-Nässjö
Elisabet Olsson, Katarina Andersson
Norrköping/ Vrinnevi
Marguerite Berglund, Anna Göransson
Kalix
Hannele Hjelm, Maria Förare
Norrtälje
Patricia Hilland, Katarina Sjöström
Kalmar
Kerstin Karlsson, Anette Danielsson,
Lotten Berggren
Karlshamn
Anders Pettersson, Carina Larsson, Lisa
Strand
Karlskoga
Inger Rosengren, Eva Grohp
Nyköping
Annika Kastenfalk
Karlskrona
Boel Bingström Karlsson, Inger Berggren,
Katarina Widebrant
Karlstad
Anna-Lena Perman, Lena Larsson
Karolinska Huddinge
Marie Axelsson
NÄL/Norra Älvsborgs Länssjukhus
Anette Rosengren, Annika Jägevall, Lena
Dittmer
Oskarshamn
Anita Svensson, Ann-Kristin Persson,
Mariette Gustavsson
Piteå
Ulla Söderberg, Ulla Ganestig
Ryhov/Jönköping
Lena Sörman, Berit Krantz
Sahlgrenska/Göteborg
Christina Gullbratt, Lena Wernhamn
Västerås
Sara Östring, Eira Johansson, Lena Eriksson,
Linda Jakobsson, Meeli Tarish, Elisabeth
Norman, Catharina Holmberg
Växjö
Ulla Pettersson, Linda Nilsson, Anette Borland
Ystad
Åsa Lindström, Gunilla Persson, Bengt Jonazon,
Gull-Marie Wahlberg
Ängelholm
Dorit Christensen, Inger Hallenborg
Örebro
Marie Lokander
Örnsköldsvik
Marie Andersson , Ulrika Westin, Maire
Johansson
Östersund
Kristina Ingvarsson, Åsa Persson
Östra sjukhuset/Göteborg
Hengameh Kazemi, Linda Nilsson, Satu
Kousmanen
6