For peer review only
FACTORS FACILITATING A NATIONAL QUALITY REGISTRY
TO AID CLINICAL QUALITY IMPROVEMENT.
Journal: BMJ Open
Manuscript ID bmjopen-2016-011562
Article Type: Research
Date Submitted by the Author: 26-Feb-2016
Complete List of Authors: Eldh, Ann ; Uppsala Universitet, Department of Public Health and Caring Sciences ; Hogskolan Dalarna Wallin, Lars; Hogskolan Dalarna; Karolinska Institutet, Department of Neurobiology, Care Sciences and Society Fredriksson, Mio; Uppsala Universitet, Department of Public Health and Caring Sciences Vengberg, Sofie; Uppsala Universitet, Department of Public Health and Caring Sciences
Winblad, Ulrika; Uppsala Universitet, Department of Public Health and Caring Sciences Halford, Christina; Uppsala Universitet, Department of Public Health and Caring Sciences Dahlström, Tobias; Uppsala Universitet, Department of Public Health and Caring Sciences
<b>Primary Subject Heading</b>:
Health services research
Secondary Subject Heading: Neurology
Keywords:
Stroke < NEUROLOGY, HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Organisational development < HEALTH SERVICES
ADMINISTRATION & MANAGEMENT, Quality in health care < HEALTH SERVICES ADMINISTRATION & MANAGEMENT
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FACTORS FACILITATING A NATIONAL QUALITY REGISTRY TO AID CLINICAL
QUALITY IMPROVEMENT.
Authors
Ann Catrine Eldh*, PhD, Associate Professor1, 2
Lars Wallin, Professor2, 3
Mio Fredriksson, PhD1
Sofie Vengberg, MSc1
Ulrika Winblad, PhD, Associate Professor1
Christina Halford, MD, PhD1
Tobias Dahlström, PhD1
Affiliations
1 Department of Public Health and Caring Sciences, Uppsala University, UPPSALA, Sweden
2 School of Health and Social Science, Dalarna University, Falun, Sweden
3 Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska
Institutet, Stockholm, Sweden
Corresponding author
Ann Catrine Eldh, School of Health and Social Science, Dalarna University, SE791 88 Falun,
Sweden. Telephone +46 (0)23 77 86 97. E-mail [email protected]
Keywords
Evidence-based practice, Facilitation, Quality improvement, Quality registry, Stroke
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Number of references
31
Abstract
Objectives
While national quality registries (NQRs) are suggested to provide opportunities for systematic
follow-up and learning opportunities, and thus clinical improvements, features in registries
and contexts triggering such processes are not fully known. This study focuses one of the
world’s largest stroke registries, the Swedish NQR Riksstroke, investigating what aspects of
the registry and healthcare organisations facilitate or hinder the use of registry data in clinical
quality improvement.
Methods
Following particular qualitative studies, we performed a quantitative survey in an exploratory
sequential design. The survey, including 50 items on context, processes and the registry, was
sent to managers, physicians and nurses engaged in Riksstroke in all 72 Swedish stroke units.
Altogether 242 individuals were presented with the survey; 163 responded, representing 97%
of all units. Data were analyzed descriptively and through multiple linear regression.
Results
A majority (88%) considered Riksstroke data to facilitate detection of stroke care
improvement needs and acknowledged that their data motivated quality improvements (78%).
The use of Riksstroke for quality improvement initiatives was associated (R2 = 0.76) with
“Colleagues’ call for local results” (p=0.00), “Management Request of Registry data”
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(p=0.00), and it was said to be “Simple to explain the results to colleagues” (p=0.02). Using
stepwise regression, “Colleagues’ call for local results” was identified as the most influential
factor. Yet, while 73% reported that managers request registry data, only 39% reported that
their colleagues call for the unit’s Riksstroke results.
Conclusions
While a NQR like Riksstroke demonstrates improvement needs and motivates stakeholders to
make progress, local stroke care staff and managers need to engage to keep momentum going
in terms of applying registry data when planning, performing and evaluating quality
initiatives.
Strengths and limitations of this study
• A survey providing novel insight as to what facilitate clinical quality improvements with
regards to quality registries.
• Represents a study with good response rate, using a validated survey, from across almost
all units’ stakeholders in one of the largest registries on stroke worldwide.
• While national quality registries are more common in countries like Australia, Sweden
and UK, the findings may be applicable to users of other medical registries.
• Representing a well-established NQR, findings from Riksstroke may not illustrate barriers
in emerging registries and/or their use in clinical practice.
Introduction
Systematic collection and analysis of performance data is a commended approach for
monitoring quality of care and identifying areas of improvement.1 Many countries have thus
introduced medical registries to improve healthcare quality.2-4 Sweden has an extensive track
record of national quality registries (NQRs).5 Providing for individual-based data entries on
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particular diagnoses, treatment interventions, and outcomes, NQRs offer opportunities to
monitor and thus improve healthcare quality.6
The NQR on stroke, Riksstroke, represents a renowned diagnosis-based registry. It was
established in 1994, and since 1998, all hospitals providing stroke care partake in the registry,
including 25,000–26,000 unique care episodes each year.7 Riksstroke comprises the acute
care following a stroke and follow-up at three and twelve months after discharge for each
individual, including medical aspects as well as the multiprofessional stroke care process. It
currently contains over 450,000 stroke events, making it one of the world’s largest stroke
registries.7
While Riksstroke is said to provide opportunities for systematic follow-up and learning
opportunities,8 9 neither this nor other NQRs have proven to be the expected drivers of local
quality improvement. The local focus is often on entering complete data, while local analysis
and initiation of improvements by the data is less common.10 Thus, the most recent national
subsidisation of NQRs is accompanied by the prospect that NQRs will aid facilitation of
continuous quality improvement, cultivating effectiveness and balancing differences in
quality of care between health providers.11 However, the complete picture as to how and when
NQRs contribute to or initiate such processes is pending.
Previously, using Riksstroke as a case in a series of qualitative studies, we found barriers and
facilitators for quality improvement within the registry itself and in the interplay between
inner and outer stroke care contexts.12-14 Beyond particular stroke process projects, the use of
Riksstroke was ambiguous and highly dependent on devoted professionals in stroke units and
among stakeholders at the politico-administrative level. While these studies provided a
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profound understanding, including a sample of stroke care in Sweden, a common knowledge
of how a NQR like Riksstroke promotes quality improvement is needed. This study
investigates what aspects of Riksstroke and healthcare organisations facilitate or hinder the
use of registry data in clinical quality improvement.
Methods
Survey development
This quantitative study is the second phase of an exploratory sequential design.15 Previous
qualitative findings exposed several factors for further investigation: the organisation’s
context; the individuals involved in local NQR work; the stroke healthcare process; data
registration; data analysis; and experiences applying the NQR for initiating change.12 13 From
these studies and a literature review, we produced a national survey. The survey was in
Swedish, but an overview of the content and structure is presented in English (see
Supplementary file I). The complete survey can be obtained from the research team.
In spring 2014, the preliminary survey was tested for content validity and response process
validity in three phases.16 Initially, the research team examined the content validity in a
workshop. Secondly, another six healthcare researchers external to the team examined the
survey’s structure, content, layout and responses in individual think-aloud interviews.17 The
input prompted minor changes to the wording of questions and response options. Thirdly, the
survey was tested in its target population, including five NQR users from across Sweden, all
in charge of the local work in their units using three similar NQRs. They were appointed for
individual telephone interviews; at the start of each interview, respondents received the survey
by e-mail, in accordance with the planned distribution for the main study. They were
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prompted to respond to the survey and to think aloud on its structure, content and layout. The
test resulted in minor changes regarding wording and a reordering of certain items.
The final survey was designed in a web survey program (LimeSurvey, version 1.90+) and
comprised 50 questions organised in 7 sections: (A) Background information about the
respondent; (B) Quality of care; (C) Data quality; (D) Organisational conditions; (E) The
respondent’s use of registry data; (F) The stroke unit’s use of registry data, and (G) Perceived
value of the registry. We mainly used a Likert scale approach for the responses, with five
alternatives ranging from “Strongly Disagree” to “Strongly Agree”. However, section B partly
applied a five-alternative Likert scale ranging from “Very Poor” to ”Very Strong”, and
section E partly applied a four-alternative frequency scale ranging from “Never” to “Often”.
Each section included an opportunity to provide additional remarks in free text, and the
survey program allowed for each section to appear consecutively.
Sampling and procedure
At each stroke unit, the survey was sent to: a) the head of the clinic, b) the physician(s) in
charge of Riksstroke (or, if there were none, the physician in charge of the stroke unit), and c)
the registered nurse(s), licensed practical nurse(s), and/or medical secretary (if any) in charge
of registering local Riksstroke data. To identify respondents, the national Riksstroke registry
administration shared their inventory of all 72 hospital units providing stroke care in Sweden,
and the name and address of the contact person at each stroke unit. From this information, we
identified potential recipients and obtained names and email addresses, including at least 2
and at most 5 individuals per stroke unit (mean 3.5).
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The survey was distributed via email in September 2014. After two, three and four weeks,
respectively, corresponding reminders were sent to those who had not yet replied. A final
reminder was sent after week five that included an opportunity to provide reasons for not
partaking. Prior to the study, approval from the regional ethical board in [blinded for review],
Sweden, was obtained (2013/181). Individual consent to participate was achieved by the
voluntary completion and submission of the survey.
Independent and dependent variables
We identified sets of dependent and independent variables (indexes) by processing theoretical
knowledge and clinical experience, including our previous qualitative studies12 13, and the
literature review; all indexes are outlined in Supplementary file II. Essentially, an index was
created as a dependent variable that depicted the healthcare unit’s use of registry data as
reported by the respondents (Cronbach’s Alpha=0.89). The following indexes, serving as
independent variables, were constructed to capture: Support from Outer Setting; Management
Request for Registry Data; Management Involvement in Registry-based Quality
Improvement; Data Quality and Usefulness, and Resources. In addition, a number of single
questions (items 8, 24, 28, 29, 30, 31, and 46) were included as independent variables
comprising: the unit’s local results; support from the local department and the registry;
simplicity of retrieving outdata and explaining the results to colleagues and managers;
motivation, and colleagues’ interest in Riksstroke data.
Validation of indexes
A factor analysis was conducted using SPSS v23 to validate that our indexes contained
relevantly grouped individual items. The factors were first extracted using direct oblimin
rotation. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.75, indicating that a
factor analysis was appropriate for the material, while Bartlett’s Test of Sphericity had a
significance of .000, indicating that the data were appropriate for factor analysis. The highest
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correlation between our factors was 0.35, validating the use of the direct oblimin rotation. The
scree plot suggested using four factors, but performing the exploratory factor analysis to
validate our five indexes, we chose to extract five factors. The factor analysis generally
validated our scales as seen in Table 1. The extracted factors had a high degree of
correspondence with those constructed on theoretical bases a priori. As a final test, we
calculated the Cronbach alpha (using SPSS, version 23) on our indexes, identifying a range
from 0.73 for “Data Quality and Usefulness”, to 0.91 for “Management Request of Registry
Data”. Details are found in Table 1 and Supplementary file II.
Table 1. Factor loadings
Pattern Matrix Loadings (only loadings above 0.5 are shown)
Index Item 1 2 3 4 5
Data Quality
and
Usefulness
(Cronbach’s
Alpha= 0.88)
9. Data from the registry are
of high quality
10. Data from the registry
capture the essential aspects
of quality of care 0.85
11. Data from the registry
are a useful tool for
identifying improvement
areas 0.66
12. Data from the registry
enable reliable internal
comparisons over time
0.52
13. Data from the registry
0.74
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enable reliable external
comparisons with other
organisations registering in
Riksstroke
Resources
(Cronbach’s
Alpha= 0.73)
7. I believe the care of our
stroke patients has sufficient
resources to maintain a high
quality
14. We have sufficient
resources (for example,
allocated time and
competence) to enter
complete mandatory data in
the registry -0.82
15. We have sufficient
resources (for example,
allocated time and
competence) to analyse
outdata from the registry -0.79
16. We have sufficient
resources (for example,
allocated time and
competence) to perform
improvement work based on
registry data -0.59
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Support
from Outer
Setting
(Cronbach’s
Alpha=0.79)
25. I get the support I ask
for from support functions at
the hospital 0.79
26. I get the support I ask
for from the county council
(equivalent to region) 0.74
27. I get the support I ask
for from a regional registry
centre
0.72
Management
Request for
Registry
Data
(Cronbach’s
Alpha=0.91)
17. My manager (the
manager I report to) calls for
data from the registry 0.66
47. Our results in Riksstroke
are called for by the
department managers 0.83
48. Our results in Riksstroke
are called for by the
hospital’s board of directors 0.99
49. Our results in Riksstroke
are called for by the county
council board (equivalent to
region) 0.94
Management
Involvement
in Registry-
18. My manager (the
manager I report to)
supports improvement work
-0.52
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based
Quality
Improvement
(Cronbach’s
Alpha=0.80)
initiated by others based on
registry data
19. My manager (the
manager I report to) initiates
improvement work based on
registry data -0.61
Included as
single items
24. I get the support I ask
for from my own
department 0.54
30. It is simple to explain
our department’s results to
colleagues and managers
0.59
46. Our results in Riksstroke
are called for by the
department’s members of
staff
8. I consider our results in
Riksstroke to be…
28. I get the support I ask
for from Riksstroke
29. It is simple to retrieve
registry data
0.51
31. I am motivated to
improve the stroke care we
provide as a result of our 0.65
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results in the registry
Statistical analyses
A descriptive analysis of individual respondents’ demographics and responses was conducted
using SPSS v23, dichotomising the items with a cut-off at Agree. A descriptive analysis of the
independent variables used in the regression analysis was also conducted. Using STATA
version 13, a multiple linear regression analysis was performed. The chosen unit of analysis
was “stroke unit” (not individual respondent) to avoid stroke units with more respondents
having a larger impact on the results. The regression analysis was conducted with the
following specification
�� = � + ������ + ��� + ��, � = 1, … ,73, � = 1,… ,5� = 1,… ,7
with X being the five indexes used as independent variables, Z being the 7 individual items
used as independent variables, and y being the use of quality registers as depicted by our
constructed index. The sk-test and Shapiro-Wilk test verified normal distribution of the
residuals. To test for heteroscedasticity, the Breusch-Pagan test was used, which could not
reject constant variance. We used the forward selection criteria to determine the order of
inclusion in the stepwise regression and then the nestreg command to determine the change in
R2.
Results
Response rate and demographics
The survey was sent to 242 individuals, 163 of which responded (67%), representing 70 of the
72 Swedish hospitals with stroke units (97%). Most respondents were registered nurses,
followed by physicians and managers, and completed more than one task with Riksstroke, for
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example data registration and data analysis (see Table 2). A vast majority had been engaged
with the local Riksstroke three years or longer, indicating potential for experience with full
annual cycles of reporting, feedback and analyses. Those who did not respond (but specified
why) were mainly managers who reported not working with Riksstroke enough to respond to
the survey.
Table 2. Demographics of respondents
Type of demographics Replies Number (%)
n=163
Sex Women
Men
119 (72.6)
43 (26.4)
Profession* Physician
Secretary
Registered nurse
Licensed practical nurse
Manager
Other
47 (28.8)
7 (4.3)
69 (42.3)
13 (8)
35 (21.5)
17 (10.4)
Role in the local work with Riksstroke Local responsibility for
the registry
Entering data in the
registry
Collecting data for the
registry
Manager
Other
52 (31.9)
71 (43.6)
65 (39.9)
48 (29.5)
21 (12.8)
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Number of years in this role Less than one year
1-2 years
3-5 years
6 years or more
23 (14)
30 (18)
39 (24)
71 (44)
* Multiple answers are possible.
Descriptive results
Most respondents felt Riksstroke provided data for identifying areas in need of improvement
(88%) and reported using Riksstroke data to do so (76%). Slightly fewer, 63%, reported
performing local analyses of their data in Riksstroke, but only 42% reported having enough
resources, for instance time and skills, in the stroke unit to analyse their data. Even with this
potential lack of resources, 61% of respondents reported that they retrieve outdata, and 68%
that they participate in data analysis. A slight majority (59%) reported that their manager
supports quality improvement based on their unit’s data and still more (73%) that their
managers request data from the registry. While 63% considered it simple to explain data to
fellow staff and managers and 79% presented registry data to others, only 39% reported that
their colleagues call for Riksstroke results from their unit. All details are represented in Table
3.
Table 3. Descriptive results – details
Items, including their respective openings when
appropriate
Number (percent) agreeing
(n=163)*
I believe the care of our
stroke patients…
is of high quality 153 (94)
has sufficient resources to
maintain a high quality
70 (44)
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I consider our results in Riksstroke to be…** 124 (77)
Data from the registry… are of high quality 134 (83)
capture the essential aspects
of quality of care
136 (84)
are a useful tool for
identifying improvement
areas
142 (88)
enable reliable internal
comparisons over time
145 (89)
enable reliable external
comparisons with other
organisations registering in
Riksstroke
126 (77)
We have sufficient resources
(for example, allocated time
and competence) to…
enter complete mandatory
data in the registry
88 (54)
analyse outdata from the
registry
69 (42)
perform improvement work
based on registry data
64 (40)
My manager (the manager I
report to)…
calls for data from the
registry
102 (63)
supports improvement work
initiated by others based on
registry data
94 (59)
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initiates improvement work
based on registry data
67 (42)
I get the support I ask for
from…
my own department 102 (65)
support functions at the
hospital
39 (27)
the county council
(equivalent to region)
22 (15)
a regional registry centre 24 (17)
Riksstroke (the registry
organisation)
110 (71)
It is simple to… retrieve registry data 93 (59)
explain our department’s
results to colleagues and
managers
99 (63)
I am motivated to improve the stroke care we provide as a
result of our results in the registry
99 (78)
I… retrieve registry data 99 (61)
partake in analysis of registry
data
109 (68)
report registry results to
others
126 (79)
suggest improvements to our
stroke care by means of our
results in the registry
127 (79)
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participate in improvements
in our organisation by means
of our results in the registry
120 (70)
manage improvements in our
organisation by means of our
results in the registry
91 (58)
In my department, we… enter complete mandatory
data in the registry for all
eligible patients
150 (93)
use the registry indicators in
our activity plan
105 (66)
perform own analyses of our
data in the registry
99 63
use registry data to identify
issues where there is a need
to change
121 (76)
carry out the improvements
which we have deemed
necessary based on our
results in the registry
109 (70)
regularly present our results
in the registry to members of
staff
93 (60)
use registry data to compare
our results to similar
94 (59)
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organisations
use registry data when
introducing new clinical
methods and procedures
61 (39)
Our results in Riksstroke are
called for by...
the department’s members of
staff
62 (39)
department managers 118 (73)
the hospital board of directors 101 (64)
the county council board
(equivalent to region)
81 (54)
I believe that what we gain from partaking in the registry
justifies the resources spent on working with it
104 (65)
* Missing responses, range 0-22 (mean 4.7). No imputations made.
**Item response alternatives ranging from ‘very poor’ to ‘very strong’.
Multiple regression results
Using the index of the healthcare unit’s use of registry data as a dependent variable, three
independent variables were found to be significant: one index “Management Request of
Registry Data” (p=0.00), and two single items: “It is simple to explain our department’s
results to colleagues and managers” (p=0.00) and “Our results are called for by staff
members” (p=0.00). These three variables accounted for the variance (R2) at 0.75. Neither
data quality nor resources were found to be significant for the unit’s use of Riksstroke for
quality improvement (see Table 4). Using stepwise regression, we could see “Our results are
called for by Members of Staff” had the highest impact on explained variance, followed by
the index “Management Consideration of Data “(see Table 5).
Table 4. Regression results, multiple regression
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Independent variables Coefficient P
Support from Outer Setting -.098 0.572
Management Request for Registry Data .447 0.000
Management Involvement in Registry-based Quality Improvement .009 0.976
Resources .160 0.272
Data Quality and Usefulness -.031 0.880
I consider our results in Riksstroke to be… .250 0.747
I get the support I ask for from my own department -.016 0.974
I get the support I ask for from the registry organisation .490 0.315
It is simple to retrieve registry data -.333 0.502
It is simple to explain our department’s results to colleagues and
managers 1.411 0.022
I am motivated to improve the stroke care we provide as a result of
our results in the registry -.610 0.323
Our results in Riksstroke are called for by members or staff 2.642 0.000
Constant 5.776 0.110
N 70
R2 0.759
Table 5. Regression results, stepwise regression
Inserted variable Block R2
Change
R2
Our results in Riksstroke are called for by members or staff (item
46) 1 0.59
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Management Request for Registry Data 2 0.71 0.12
It is simple to explain our department’s results to colleagues and
managers (item 30) 3 0.74 0.03
Discussion
While quality registries are suggested as a vehicle for improving quality of care, the complete
picture of how and when registries inform or drive these processes has not been fully
appraised. Riksstroke is often employed in research18 and thus contributes to better care for
stroke patients in Sweden and beyond. However, as with many healthcare innovations, it is
not fully known if, how, where and when it is applied in clinical practice.19 In previous
qualitative studies, we found that health professionals and decision-makers depicted
contextual factors at the stroke unit, hospital and regional levels to affect the use or lack of
use of Riksstroke to improve stroke care.12 13 Additional features were found in this study to
further illustrate the application of Riksstroke in local quality initiatives. Primarily, the role of
managers and co-workers will be considered, along with the limited support this study
provides for the notion that resources and data quality shape quality improvement.
Besides research, local quality improvements are needed to advance stroke care. Access to
local data is crucial for quality improvement.20 Our findings emphasise that recipients need to
understand performance in conjunction with quality to capture improvement needs21: while a
NQR like Riksstroke can provide stroke units with opportunities to access their local
longitudinal data on aggregated levels and benchmark their care to national standards and/or
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other stroke units,22 feedback is best managed in groups of peers, with repeated
communication on the outdata to feed improvement initiatives.23 While Sweden and other
countries like Australia and the UK have invested in NQRs like Riksstroke,24 25 most efforts
focus on securing data quality.12 13 For future progress, quality improvement initiatives must
focus on enhancing specific knowledge and skills, an assignment beyond stroke care
expertise.26
A careful look at the results reveals a complex picture: while neither data quality nor
resources were significantly correlated with the use of NQR data in local quality
improvement, more professionals involved in Riksstroke reported their own use of data than
use of data by the stroke unit to improve quality. The limited engagement from colleagues and
the obvious influence of the use of data on local quality improvement suggests the image of a
lone stroke expert deciphering local data, while the stroke team members are unaware of the
opportunities for quality improvement at their fingertips. Local Riksstroke stakeholders
aggregate and present data to peers and managers and find this rather simple. However, this
does not seem to increase engagement from peers. Our previous study showed that staff
members engaged in Riksstroke at the stroke unit level are aware of the need to identify
unique selling points to involve their colleagues.12 But more collaborative efforts and an
understanding of quality improvement are necessary if the data is to help improve stroke care
and not just provide feedback. Managers are often considered key to support clinical quality
improvement,12 13 27 which our findings also support. But our results show that peer support is
just as important, if not more so, to keep up the momentum to improve stroke care based on a
NQR like Riksstroke. This factor had the strongest association with the unit’s use of
Riksstroke outdata for quality improvement. The need for team collaboration and support
among co-workers is congruent with findings of quality improvement in general,28 suggesting
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that successful quality improvement is a joint effort, and support from others is a motivating
factor for facilitating improvement.29 The importance of interplay between the adoption of
innovations30 by individuals and organisations further emphasizes the motivating impact of
others being engaged in the same issues as oneself. Improvements are social processes, and
relationships and communication are thus significant for quality improvement. Leaders are
important in quality improvement,31 but locally appointed staff working with the registry
apparently need staff members to engage to improve stroke care.
Methodological considerations
Sweden has a universal, comprehensive and tax-based healthcare system similar to those of
larger nations like Australia, the UK and Canada. As a result, experiences with NQRs in
Sweden may be relevant to registry initiatives in other countries. Riksstroke is a well-known
and acclaimed registry, giving this study the potential to pinpoint factors that facilitate quality
improvements to stroke care and other similar registries.
While the factor analysis did not fully confirm our index of dependent variables, the match
between the indexes constructed a priori and the factors identified in the factor analysis
worked out relatively well. To facilitate the interpretation of the regression analysis, we chose
to keep our indexes instead of using the factor scores. However, the index that was found to
be significant in the regression had a 100% match with the suggested factor in the factor
analysis. Given our cross-sectional sample, the results cannot distinguish between cause and
effect. While we have not tested for causation, it is reasonable to believe that it is not
unidirectional, but rather that there are feedback loops.
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Conclusions
Previous studies have shown that besides being a rich source for research, a NQR such as
Riksstroke can provide opportunities for local stroke care quality improvement. This study
represents 97% of all stroke units across Sweden and a broad scope of managers, physicians
and nurses involved in the local assignment with Riksstroke and found that most participants
considered resources spent on Riksstroke to be worthwhile. Yet, data analyses and quality
improvements as a result of data received less attention than the registration of data. In
addition, the use of Riksstroke data for quality improvement initiatives was related to the
interest and engagement of fellow stroke care staff and managers. This is a call for further
initiatives to engage entire stroke teams in understanding the potential for applying registry
data in planning, performing and evaluating initiatives to improve stroke care.
Acknowledgement
We are grateful to the researchers and clinicians who participated in the validation of the
survey tool and to all respondents who completed the survey.
Funding
The research leading to these results was supported by the Swedish Association of Local
Authorities and Regions (SALAR).
Competing interests
The authors declare that we have no competing interests.
Contributions
All authors participated in designing the study, and drafting and testing the survey. Validation was performed by SV. TD performed the analyses in dialogue with ACE, LW and MF. ACE, UW, LW and MF attained funding for the study. ACE drafted the paper and completed it in collaboration with all authors, who have approved the final version prior to submission.
Data Sharing
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No additional data available.
References
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improvement. U.S. Department of Health and Human Services website.
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7. Riksstroke. http://www.riksstroke.org/eng/ Accessed 5 November 2015.
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11. Rosén M. Översyn av de nationella kvalitetsregistren. Guldgruvan i hälso- och
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14. [Blinded for review.]
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Supplementary files
I. Overview of the KVAK web survey content and structure (English version)
II. The dependent and independent variables
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FACTORS FACILITATING A NATIONAL QUALITY REGISTRY TO AID CLINICAL
QUALITY IMPROVEMENT.
I. Overview of the KVAK web survey content and structure (English version)
Section A. Background
Item number Items
1-5
My: sex, age, professional role, role in the
local work with the registry, and number of
years in registry role
Section B. Quality of care and access to resources
Item number Items Response alternatives
6-7 Quality of Stroke Care Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
8 Quality of Local Data Likert scale, five
alternatives ranging from
Very Poor to Very Good
Section C. Data from the quality registry
Item number Items Response alternatives
9-13 Riksstroke data Likert scale, five
alternatives ranging from
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Strongly Disagree to
Strongly Agree
Section D. Organisational conditions for registry work
Item number Items Response alternatives
14-16 Resources for entry and
analysis of data and quality
improvements
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
17-19 Managers’ support Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
20-23 Where I turn for support Five alternatives, at
department, hospital,
regional and national level
24-28 Support received Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
Section E. My use of registry data
Item number Items Response alternatives
29-30 Simplicity in retrieving and
reporting data/output
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
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31 Motivation Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
32-37 My role in the data
management process (from
entering data, to analysis, and
stroke care quality
improvement)
Likert scale, four
alternatives ranging from
Never to Often
Section F. The organisation’s use of registry data
Item number Items Response alternatives
38-45 Our use of the Riksstroke data,
in general and in quality
improvement
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
46-49 Others’ interest in our results
in Riksstroke
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
Section G. Concluding question
Item number Item Response alternatives
50 Efforts in relation to use of
Riksstroke
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
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The KVAK survey is licensed as a CC Attribution-NonCommercial (CC BY-NC) product.
For further communication and access to the survey, please contact [blinded for review] at:
link blinded for review. Further details on the license can be found at
https://creativecommons.org/
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FACTORS FACILITATING A NATIONAL QUALITY REGISTRY TO AID CLINICAL
QUALITY IMPROVEMENT.
II. The dependent and independent variables
In a series of dialogues, the research team identified sets of variables representing specific
constructs by processing: previous research (our own and others’, collated in a literature
review); theoretical aspects of the implementation of innovations and evidence-based practice,
and understanding of NQRs at the macro, meso and micro levels. We eventually arrived at
five indexes and seven single items.
• Firstly, the dependent variable was created, representing Respondent’s depiction of their
stroke unit’s use of registry data. This includes items 39-45 (from section F in the
survey), hence the following follow-up items to the opening line “In my department,
we…”:
o use the registry indicators in our activity plan;
o perform own analyses of our data in the registry;
o use registry data to identify issues where there is a need to change;
o carry out the improvements which we have deemed necessary based on our results
in the registry;
o regularly present our results in the registry to members of staff;
o use registry data to compare our results to similar organisations, and
o use registry data when introducing new clinical methods and procedures.
All items in the index use a Likert scale approach for responses, with five alternatives ranging
from Strongly Disagree to Strongly Agree. The categorization of response alternatives was
non-agreement vs. agreement, with a cut-off at “Agree”.
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Secondly, the indexes of independent variables convey:
• Data Quality and Usefulness, includes items 9-13 (section C), i.e., follow-up items to the
opening line “Data from the registry…”: are of high quality; capture the essential aspects
of quality of care; are a useful tool for identifying improvement areas; enable reliable
internal comparisons over time, and enable reliable external comparisons with other
organisations registering in Riksstroke. Again, the categorization of response alternatives
was non-agreement vs. agreement, with a cut-off at “Agree”.
• Support from Outer Setting includes follow-up items 25-27 (from section D) to the
opening line “I get the support I ask for from…”: support functions at the hospital; the
county council (equivalent to region), and a regional registry centre. The categorization of
response alternatives was non-agreement vs. agreement, with a cut-off at “Agree”.
• Resources consists of item 7 from section B: “I believe the care of our stroke patients has
sufficient resources to maintain a high quality”, and items 14-16 from section D,
following the opening line “We have sufficient resources (for example, allocated time and
competence) to…”: enter complete mandatory data in the registry; analyse outdata from
the registry, and perform improvement work based on registry data. Yet again, the
categorization of response alternatives was non-agreement vs. agreement, with a cut-off at
“Agree”.
• Management Request for Registry Data includes item 17, “My manager (the manager I
report to) calls for data from the registry”, and items 47-49, all follow-ups to an opening
line from section D, “Our results in Riksstroke are called for by”: department managers;
the hospital board of directors, and the county council board (equivalent to region). An
identical categorization of response alternatives as above was made, that is to say non-
agreement vs. agreement, with a cut-off at “Agree”.
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• Management Involvement in Registry-based Quality Improvement originates from
section D (items 18 and 19) and its follow-up items, 18 and 19, to “My manager …”:
“supports improvement work initiated by others based on registry data”, and “initiates
improvement work based on registry data”. Once again, categorization of response
alternatives was non-agreement vs. agreement, with a cut-off at “Agree”.
Thirdly, a number of single items were included as independent variables:
• Item 8, “I consider our results in Riksstroke to be…”. This item was accompanied by
an alternative Likert scale ranging from “Very Poor” to” Very Good”. The
categorization of response alternatives was “Poor” versus “Good”, with a cut-off at
“Rather Good”.
• Item 24, “I get the support I ask for from my own department.”
• Item 28, “I get the support I ask for from the registry organisation.”
• Item 29, “It is simple to retrieve registry data.”
• Item 30, “It is simple to explain our department’s results to colleagues and managers.”
• Item 31, “I am motivated to improve the stroke care we provide as a result of our
results in the registry.”
• Item 46, “Our results in Riksstroke are called for by the department’s members of
staff.”
The six latter single items applied the same Likert scale approach for responses as described
above, that is, with five alternatives ranging from “Strongly Disagree” to “Strongly Agree”.
Thus, the categorization of response alternatives was non-agreement vs. agreement, with a
cut-off at “Agree”.
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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cross-sectional studies
Section/Topic Item
# Recommendation Reported on page #
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 1
(b) Provide in the abstract an informative and balanced summary of what was done and what was found 1
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 2-3
Objectives 3 State specific objectives, including any prespecified hypotheses 3
Methods
Study design 4 Present key elements of study design early in the paper 4
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data
collection
5
Participants
6
(a) Give the eligibility criteria, and the sources and methods of selection of participants 5
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if
applicable
6, and
Supplementary file II
Data sources/
measurement
8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe
comparability of assessment methods if there is more than one group
4-5
Bias 9 Describe any efforts to address potential sources of bias 4 and 5
Study size 10 Explain how the study size was arrived at 5
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and
why
5-6, Table 1, and
Supplementary file II
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 10-11
(b) Describe any methods used to examine subgroups and interactions n/a
(c) Explain how missing data were addressed 17
(d) If applicable, describe analytical methods taking account of sampling strategy n/a
(e) Describe any sensitivity analyses n/a
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Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,
confirmed eligible, included in the study, completing follow-up, and analysed
11
(b) Give reasons for non-participation at each stage 11
(c) Consider use of a flow diagram n/a
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential
confounders
11, and Table 2
(b) Indicate number of participants with missing data for each variable of interest Table 2 footnote (p
17)
Outcome data 15* Report numbers of outcome events or summary measures 17, and Table 5
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence
interval). Make clear which confounders were adjusted for and why they were included
17, and Table 4 and
5
(b) Report category boundaries when continuous variables were categorized 13, and Table 3
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period n/a
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses n/a
Discussion
Key results 18 Summarise key results with reference to study objectives 19-21
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and
magnitude of any potential bias
21
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from
similar studies, and other relevant evidence
21
Generalisability 21 Discuss the generalisability (external validity) of the study results 21
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on
which the present article is based
22
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE
checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.
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FACTORS FACILITATING A NATIONAL QUALITY REGISTRY
TO AID CLINICAL QUALITY IMPROVEMENT – FINDINGS OF
A NATIONAL SURVEY.
Journal: BMJ Open
Manuscript ID bmjopen-2016-011562.R1
Article Type: Research
Date Submitted by the Author: 21-Jun-2016
Complete List of Authors: Eldh, Ann ; Uppsala Universitet, Department of Public Health and Caring Sciences ; Hogskolan Dalarna Wallin, Lars; Hogskolan Dalarna; Karolinska Institutet, Department of
Neurobiology, Care Sciences and Society Fredriksson, Mio; Uppsala Universitet, Department of Public Health and Caring Sciences Vengberg, Sofie; Uppsala Universitet, Department of Public Health and Caring Sciences Winblad, Ulrika; Uppsala Universitet, Department of Public Health and Caring Sciences Halford, Christina; Uppsala Universitet, Department of Public Health and Caring Sciences Dahlström, Tobias; Uppsala Universitet, Department of Public Health and Caring Sciences
<b>Primary Subject
Heading</b>: Health services research
Secondary Subject Heading: Neurology, Evidence based practice
Keywords:
Stroke < NEUROLOGY, HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Organisational development < HEALTH SERVICES ADMINISTRATION & MANAGEMENT, Quality in health care < HEALTH SERVICES ADMINISTRATION & MANAGEMENT
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FACTORS FACILITATING A NATIONAL QUALITY REGISTRY TO AID CLINICAL
QUALITY IMPROVEMENT – FINDINGS OF A NATIONAL SURVEY.
Authors
Ann Catrine Eldh*, PhD, Associate Professor1, 2
Lars Wallin, Professor2, 3
Mio Fredriksson, PhD1
Sofie Vengberg, MSc1
Ulrika Winblad, PhD, Associate Professor1
Christina Halford, MD, PhD1
Tobias Dahlström, PhD1
Affiliations
1 Department of Public Health and Caring Sciences, Uppsala University, UPPSALA, Sweden
2 School of Health and Social Science, Dalarna University, Falun, Sweden
3 Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska
Institutet, Stockholm, Sweden
Corresponding author
Ann Catrine Eldh, School of Health and Social Science, Dalarna University, SE791 88 Falun,
Sweden. Telephone +46 (0)23 77 86 97. E-mail [email protected]
Keywords
Evidence-based practice, Facilitation, Quality improvement, Quality registry, Stroke
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Word count
3006
Number of references
35
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Abstract
Objectives
While national quality registries (NQRs) are suggested to provide opportunities for systematic
follow-up and learning opportunities, and thus clinical improvements, features in registries
and contexts triggering such processes are not fully known. This study focuses one of the
world’s largest stroke registries, the Swedish NQR Riksstroke, investigating what aspects of
the registry and healthcare organisations facilitate or hinder the use of registry data in clinical
quality improvement.
Methods
Following particular qualitative studies, we performed a quantitative survey in an exploratory
sequential design. The survey, including 50 items on context, processes and the registry, was
sent to managers, physicians and nurses engaged in Riksstroke in all 72 Swedish stroke units.
Altogether 242 individuals were presented with the survey; 163 responded, representing all
but two units. Data were analyzed descriptively and through multiple linear regression.
Results
A majority (88%) considered Riksstroke data to facilitate detection of stroke care
improvement needs and acknowledged that their data motivated quality improvements (78%).
The use of Riksstroke for quality improvement initiatives was associated (R2 = 0.76) with
“Colleagues’ call for local results” (p=<0.001), “Management Request of Registry data”
(p=<0.001), and it was said to be “Simple to explain the results to colleagues” (p=0.02).
Using stepwise regression, “Colleagues’ call for local results” was identified as the most
influential factor. Yet, while 73% reported that managers request registry data, only 39%
reported that their colleagues call for the unit’s Riksstroke results.
Conclusions
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While a NQR like Riksstroke demonstrates improvement needs and motivates stakeholders to
make progress, local stroke care staff and managers need to engage to keep momentum going
in terms of applying registry data when planning, performing and evaluating quality
initiatives.
Strengths and limitations of this study
• A survey providing novel insight as to what facilitate clinical quality improvements with
regards to quality registries.
• Represents a study with good response rate, using a validated survey, from across almost
all units’ stakeholders in one of the largest registries on stroke worldwide.
• While national quality registries are more common in countries like Australia, Sweden
and UK, the findings may be applicable to users of other medical registries.
• Representing a well-established NQR, findings from Riksstroke may not illustrate barriers
in developing registries and/or their use in clinical practice.
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Introduction
Systematic collection and analysis of performance data is a commended approach for
monitoring quality of care and identifying areas of improvement.1 Many countries have thus
introduced medical registries to improve healthcare quality.2-4 Sweden has an extensive track
record of national quality registries (NQRs).5 Providing for individual-based data entries on
particular diagnoses, treatment interventions, and outcomes, NQRs offer opportunities to
monitor and thus improve healthcare quality.6
The NQR on stroke, Riksstroke, represents a renowned diagnosis-based registry. It was
established in 1994, and since 1998, all hospitals providing stroke care partake in the registry,
including 25,000–26,000 unique care episodes each year.7 Riksstroke comprises the acute
care following a stroke and follow-up at three and twelve months after discharge for each
individual, including medical aspects as well as the multiprofessional stroke care process. It
currently contains over 450,000 stroke events, making it one of the world’s largest stroke
registries.7
While Riksstroke is said to provide opportunities for systematic follow-up and learning
opportunities,8 9 neither this nor other NQRs have proven to be the expected drivers of local
quality improvement. The local focus is often on entering complete data, while local analysis
and initiation of improvements by the data is less common.10 Thus, the most recent national
subsidisation of NQRs is accompanied by the prospect that NQRs will aid facilitation of
continuous quality improvement, cultivating effectiveness and balancing differences in
quality of care between health providers.11 However, the complete picture as to how and when
NQRs contribute to or initiate such processes is pending. Internationally, factors such as
registry coverage, methods for data collection, and the definition of variables are still
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discussed and compared between national stroke registries. Furthermore, a recent review
concluded that there is uncertainty about how NQRs on stroke feedback on the quality of care
to hospitals or patients, which is important for behaviour change leading to better stroke care
outcomes. There is also a lack of detail on how data from such registries are used in quality
improvement.12
Previously, using Riksstroke as a case in a series of qualitative studies, we found barriers and
facilitators for quality improvement within the registry itself and in the interplay between
inner and outer stroke care contexts.13-15 Beyond particular stroke process projects, the use of
Riksstroke was ambiguous and highly dependent on devoted professionals in stroke units and
among stakeholders at the politico-administrative level. While these studies provided a
profound understanding, including a sample of stroke care in Sweden, a more comprehensive
understanding of how a NQR like Riksstroke promotes quality improvement is needed. This
study investigates what aspects of Riksstroke and healthcare organisations facilitate or hinder
the use of registry data in clinical quality improvement.
Methods
Survey development
This quantitative study is the second phase of an exploratory sequential design.16 Previous
qualitative findings exposed several factors for further investigation: the organisation’s
context; the individuals involved in local NQR work; the stroke healthcare process; data
registration; data analysis; and experiences applying the NQR for initiating change.13 14 From
these studies and a literature review, we produced a national survey. The survey was in
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Swedish, but an overview of the content and structure is presented in English (see
Supplementary file I). The complete survey can be obtained from the research team.
The preliminary survey was tested for content validity and response process validity in three
phases in January through May, 2014.17 Initially, the research team examined the content
validity in a workshop. Secondly, another six healthcare researchers external to the team
examined the survey’s structure, content, layout and responses in individual think-aloud
interviews.18 The input prompted minor changes to the wording of questions and response
options. Thirdly, the survey was tested in its target population, including five NQR users from
across Sweden, all in charge of the local work in their units using three similar NQRs. They
were appointed for individual telephone interviews; at the start of each interview, respondents
received the survey by e-mail, in accordance with the planned distribution for the main study.
They were prompted to respond to the survey and to think aloud on its structure, content and
layout. The test resulted in minor changes regarding wording and a reordering of certain
items.
The final survey was designed in a web survey program (LimeSurvey, version 1.90+) and
comprised 50 questions organised in 7 sections: (A) Background information about the
respondent; (B) Quality of care; (C) Data quality; (D) Organisational conditions; (E) The
respondent’s use of registry data; (F) The stroke unit’s use of registry data, and (G) Perceived
value of the registry. We mainly used a Likert scale approach for the responses, with five
alternatives ranging from “Strongly Disagree” to “Strongly Agree”. However, section B partly
applied a five-alternative Likert scale ranging from “Very Poor” to ”Very Strong”, and
section E partly applied a four-alternative frequency scale ranging from “Never” to “Often”.
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Each section included an opportunity to provide additional remarks in free text, and the
survey program allowed for each section to appear consecutively.
Sampling and procedure
At each stroke unit, the survey was sent to: a) the head of the clinic, b) the physician(s) in
charge of Riksstroke (or, if there were none, the physician in charge of the stroke unit), and c)
the registered nurse(s), licensed practical nurse(s), and/or medical secretary (if any) in charge
of registering local Riksstroke data. To identify respondents, the national Riksstroke registry
administration shared their inventory of all 72 hospital units providing stroke care in Sweden,
and the name and address of the contact person at each stroke unit. From this information, we
identified potential recipients and obtained names and email addresses, including at least 2
and at most 5 individuals per stroke unit (mean 3.5).
The survey was distributed via email in September 2014. After two, three and four weeks,
respectively, corresponding reminders were sent to those who had not yet replied. A final
reminder was sent after week five that included an opportunity to provide reasons for not
partaking. Prior to the study, approval from the Regional Ethical Review Board in Uppsala,
Sweden, was obtained (2013/181). Individual consent to participate was achieved by the
voluntary completion and submission of the survey.
Independent and dependent variables
We identified sets of dependent and independent variables (indexes) by processing theoretical
knowledge and clinical experience, including our previous qualitative studies13 14, and a
literature review; all indexes are outlined in Supplementary file II. Essentially, an index was
created as a dependent variable that depicted the healthcare unit’s use of registry data as
reported by the respondents (Cronbach’s Alpha=0.89). The following indexes, serving as
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independent variables, were constructed to capture: Support from Outer Setting; Management
Request for Registry Data; Management Involvement in Registry-based Quality
Improvement; Data Quality and Usefulness, and Resources. In addition, a number of single
questions (items 8, 24, 28, 29, 30, 31, and 46) were included as independent variables
comprising: the unit’s local results; support from the local department and the registry;
simplicity of retrieving data from the registry and explaining the results to colleagues and
managers; motivation, and colleagues’ interest in Riksstroke data.
Validation of indexes
A factor analysis was conducted using SPSS v23 to validate that our indexes contained
relevantly grouped individual items. The factors were first extracted using direct oblimin
rotation. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.75, indicating that a
factor analysis was appropriate for the material, while Bartlett’s Test of Sphericity had a
significance of .000, indicating that the data were appropriate for factor analysis. The highest
correlation between our factors was 0.35, validating the use of the direct oblimin rotation. The
scree plot suggested using four factors, but performing the exploratory factor analysis to
validate our five indexes, we chose to extract five factors. The factor analysis generally
validated our scales as seen in Table 1. The extracted factors had a high degree of
correspondence with those constructed on theoretical bases a priori. As a final test, we
calculated the Cronbach alpha (using SPSS, version 23) on our indexes, identifying a range
from 0.73 for “Data Quality and Usefulness”, to 0.91 for “Management Request of Registry
Data”. Details are found in Table 1 and Supplementary file II.
Table 1. Factor loadings
Pattern Matrix Factor loadings (only loadings above 0.5 are shown)
Index Item 1 2 3 4 5
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Data Quality
and
Usefulness
(Cronbach’s
Alpha= 0.88)
9. Data from the
registry are of high
quality
10. Data from the
registry capture the
essential aspects of
quality of care 0.85
11. Data from the
registry are a useful tool
for identifying
improvement areas 0.66
12. Data from the
registry enable reliable
internal comparisons
over time
0.52
13. Data from the
registry enable reliable
external comparisons
with other organisations
registering in
Riksstroke
0.74
Resources
(Cronbach’s
Alpha= 0.73)
7. I believe the care of
our stroke patients has
sufficient resources to
maintain a high quality
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14. We have sufficient
resources (for example,
allocated time and
competence) to enter
complete mandatory
data in the registry
-0.82
15. We have sufficient
resources (for example,
allocated time and
competence) to analyse
data from the registry -0.79
16. We have sufficient
resources (for example,
allocated time and
competence) to perform
improvement work
based on registry data -0.59
Support
from Outer
Setting
(Cronbach’s
Alpha=0.79)
25. I get the support I
ask for from support
functions at the hospital 0.79
26. I get the support I
ask for from the county
council (equivalent to
region)
0.74
27. I get the support I
0.72
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ask for from a regional
registry centre
Management
Request for
Registry
Data
(Cronbach’s
Alpha=0.91)
17. My manager (the
manager I report to)
calls for data from the
registry 0.66
47. Our results in
Riksstroke are called for
by the department
managers 0.83
48. Our results in
Riksstroke are called for
by the hospital’s board
of directors 0.99
49. Our results in
Riksstroke are called for
by the county council
board (equivalent to
region) 0.94
Management
Involvement
in Registry-
based
Quality
Improvement
18. My manager (the
manager I report to)
supports improvement
work initiated by others
based on registry data -0.52
19. My manager (the -0.61
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(Cronbach’s
Alpha=0.80)
manager I report to)
initiates improvement
work based on registry
data
Included as
single items
24. I get the support I
ask for from my own
department 0.54
30. It is simple to
explain our
department’s results to
colleagues and
managers
0.59
46. Our results in
Riksstroke are called for
by the department’s
members of staff
8. I consider our results
in Riksstroke to be…
28. I get the support I
ask for from Riksstroke
29. It is simple to
retrieve registry data
0.51
31. I am motivated to
improve the stroke care
we provide as a result of 0.65
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our results in the
registry
Statistical analyses
A descriptive analysis of individual respondents’ demographics and responses was conducted
using SPSS v23, dichotomising the items with a cut-off at Agree. A descriptive analysis of the
independent variables used in the regression analysis was also conducted. Using STATA
version 13, a multiple linear regression analysis was performed. The chosen unit of analysis
was “stroke unit” (not individual respondent) to avoid stroke units with more respondents
having a larger impact on the results. Normal distribution of the residuals was verified (the sk-
test and Shapiro-Wilk test) and the test for heteroscedasticity, (the Breusch-Pagan test) could
not reject constant variance. We used the forward selection criteria to determine the order of
inclusion in the stepwise regression and then the nestreg command to determine the change in
R2.
Results
Response rate and demographics
The survey was sent to 242 individuals, 163 of which responded (67%), representing 70 of the
72 Swedish hospitals with stroke units (97%). Most respondents were registered nurses,
followed by physicians and managers, and completed more than one task with Riksstroke, for
example data registration and data analysis (see Table 2). A vast majority had been engaged
with the local Riksstroke three years or longer, indicating potential for experience with full
annual cycles of reporting, feedback and analyses. Those who did not respond (but specified
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why) were mainly managers who reported not working with Riksstroke enough to respond to
the survey.
Table 2. Demographics of respondents
Type of demographics Replies Number (%)
n=163
Sex Women
Men
119 (72.6)
43 (26.4)
Profession* Physician
Secretary
Registered nurse
Licensed practical nurse
Manager
Other
47 (28.8)
7 (4.3)
69 (42.3)
13 (8)
35 (21.5)
17 (10.4)
Role in the local work with Riksstroke Local responsibility for
the registry
Entering data in the
registry
Collecting data for the
registry
Manager
Other
52 (31.9)
71 (43.6)
65 (39.9)
48 (29.5)
21 (12.8)
Number of years in this role Less than one year
1-2 years
3-5 years
23 (14)
30 (18)
39 (24)
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6 years or more 71 (44)
* Multiple answers are possible.
Descriptive results
Aggregating the response alternatives “Strongly agree” and “Agree”, most respondents felt
Riksstroke provided data for identifying areas in need of improvement (88%) and reported
using Riksstroke data to do so (76%). Slightly fewer, 63%, reported performing local analyses
of their data in Riksstroke, but only 42% reported having enough resources, for instance time
and skills, in the stroke unit to analyse their data. Even with this potential lack of resources,
61% of respondents reported that they retrieve data, and 68% that they participate in data
analysis. A slight majority (59%) reported that their manager supports quality improvement
based on their unit’s data and still more (73%) that their managers request data from the
registry. While 63% considered it simple to explain data to fellow staff and managers and
79% presented registry data to others, only 39% reported that their colleagues call for
Riksstroke results from their unit. All details are represented in Table 3.
Table 3. Descriptive results – details
Items, including their respective openings when
appropriate
Number (percent) agreeing
(incl. Strongly agree and
Agree)
(n=163)*
I believe the care of our
stroke patients…
is of high quality 153 (94)
has sufficient resources to
maintain a high quality
70 (44)
I consider our results in Riksstroke to be…** 124 (77)
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Data from the registry… are of high quality 134 (83)
capture the essential aspects
of quality of care
136 (84)
are a useful tool for
identifying improvement
areas
142 (88)
enable reliable internal
comparisons over time
145 (89)
enable reliable external
comparisons with other
organisations registering in
Riksstroke
126 (77)
We have sufficient resources
(for example, allocated time
and competence) to…
enter complete mandatory
data in the registry
88 (54)
analyse data from the registry 69 (42)
perform improvement work
based on registry data
64 (40)
My manager (the manager I
report to)…
calls for data from the
registry
102 (63)
supports improvement work
initiated by others based on
registry data
94 (59)
initiates improvement work
based on registry data
67 (42)
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I get the support I ask for
from…
my own department 102 (65)
support functions at the
hospital
39 (27)
the county council
(equivalent to region)
22 (15)
a regional registry centre 24 (17)
Riksstroke (the registry
organisation)
110 (71)
It is simple to… retrieve registry data 93 (59)
explain our department’s
results to colleagues and
managers
99 (63)
I am motivated to improve the stroke care we provide as a
result of our results in the registry
99 (78)
I… retrieve registry data 99 (61)
partake in analysis of registry
data
109 (68)
report registry results to
others
126 (79)
suggest improvements to our
stroke care by means of our
results in the registry
127 (79)
participate in improvements
in our organisation by means
120 (70)
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of our results in the registry
manage improvements in our
organisation by means of our
results in the registry
91 (58)
In my department, we… enter complete mandatory
data in the registry for all
eligible patients
150 (93)
use the registry indicators in
our activity plan
105 (66)
perform own analyses of our
data in the registry
99 63
use registry data to identify
issues where there is a need
to change
121 (76)
carry out the improvements
which we have deemed
necessary based on our
results in the registry
109 (70)
regularly present our results
in the registry to members of
staff
93 (60)
use registry data to compare
our results to similar
organisations
94 (59)
use registry data when 61 (39)
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introducing new clinical
methods and procedures
Our results in Riksstroke are
called for by...
the department’s members of
staff
62 (39)
department managers 118 (73)
the hospital board of directors 101 (64)
the county council board
(equivalent to region)
81 (54)
I believe that what we gain from partaking in the registry
justifies the resources spent on working with it
104 (65)
* Missing responses, range 0-22 (mean 4.7).
**Item response alternatives ranging from ‘very poor’ to ‘very strong’.
Multiple regression results
Using the index of the healthcare unit’s use of registry data as a dependent variable, three
independent variables were found to be significant: one index “Management Request of
Registry Data” (p=<0.001), and two single items: “It is simple to explain our department’s
results to colleagues and managers” (p=<0.001) and “Our results are called for by staff
members” (p=<0.001). These three variables explained 75% of the total variance (R2= 0.75).
Neither data quality nor resources were found to be significant for the unit’s use of Riksstroke
for quality improvement (see Table 4). Using stepwise regression, we could see “Our results
are called for by Members of Staff” had the highest impact on explained variance, followed
by the index “Management Consideration of Data “(see Table 5).
Table 4. Regression results, multiple regression
Independent variables Coefficient P
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Support from Outer Setting -.098 0.572
Management Request for Registry Data .447 <0.001
Management Involvement in Registry-based Quality Improvement .009 0.976
Resources .160 0.272
Data Quality and Usefulness -.031 0.880
I consider our results in Riksstroke to be… .250 0.747
I get the support I ask for from my own department -.016 0.974
I get the support I ask for from the registry organisation .490 0.315
It is simple to retrieve registry data -.333 0.502
It is simple to explain our department’s results to colleagues and
managers 1.411 0.022
I am motivated to improve the stroke care we provide as a result of
our results in the registry -.610 0.323
Our results in Riksstroke are called for by members or staff 2.642 <0.001
Constant 5.776 0.110
N 70
R2 0.759
Table 5. Regression results, stepwise regression
Inserted variable Block R2
Change
R2
Our results in Riksstroke are called for by members or staff (item
46) 1 0.59
Management Request for Registry Data 2 0.71 0.12
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It is simple to explain our department’s results to colleagues and
managers (item 30) 3 0.74 0.03
Discussion
While quality registries are suggested as a vehicle for improving quality of care, the complete
picture of how and when registries inform or drive these processes has not been fully
appraised. Riksstroke is often employed in research19 and thus contributes to better care for
stroke patients. However, as with many healthcare innovations, it is not fully known if, how,
where and when the NQR is applied in clinical practice20 and what lies behind its
effectiveness in improving care, although organisational factors are generally pointed out as
important.21 In previous qualitative studies, we found that health professionals and decision-
makers depicted contextual factors at the stroke unit, hospital and regional levels to affect the
use or lack of use of Riksstroke to improve stroke care.13 14 Additional features were found in
this study to further illustrate the application of Riksstroke in local quality initiatives.
Primarily, the role of managers and co-workers will be considered, along with the limited
support this study provides for the notion that resources and data quality shape quality
improvement.
Besides research, local quality improvements are needed to advance healthcare. Access to
local data is crucial for quality improvement.21 Our findings emphasise that recipients need to
understand their local performance in conjunction with healthcare quality to capture
improvement needs.22 While a NQR like Riksstroke can provide stroke units with
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opportunities to access their local longitudinal data on aggregated levels, and to benchmark
their care to national standards and/or other stroke units,23 feedback should be managed in
groups of peers, with repeated communication on the data to feed improvement initiatives.24
The registry can then function as a platform to improve outcomes by engaging physicians and
other clinical staff in the shared task of improving the quality of care.25
Although Sweden and other countries like Australia and the UK have invested in NQRs like
Riksstroke,26 27 most efforts focus on securing data quality.13 14 For future progress, quality
improvement initiatives must focus on enhancing improvement knowledge and skills, an
assignment beyond stroke care expertise.28 A comparison between Sweden and the United
States of America (USA) suggests that the Swedish registries are prone to foster clinical
quality improvement, given the accommodating regulations and resources provided at
national level. However, the US system, with for example automated data capture, allow
recourses to be spent on improvement initiatives, rather than data registration.29 Registry
expertise and experience shared across countries could stimulate further development in how
to use comprehensive process- and results data in improving for example stroke care.30 In
Sweden one of the limitations of registries such as Riksstroke is evidently the burden of
registering data.29 This is most likely reflected in that merely 65% of the Riksstroke
respondents considered the gain from partaking in the registry justifying the resources spent
on working with it. Implementing automatized data capture could shift resources from
securing data to data-led quality improvement work; however, to facilitate clinical
improvement, health professionals, managers and policy makers need further support and
opportunities to engage in joint ventures.15
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A closer look at the results reveals a complex picture: while neither data quality nor resources
were significantly correlated with the use of NQR data in local quality improvement, more
professionals involved in Riksstroke reported that they themselves use data to improve quality
than their stroke unit using data for this purpose. The limited engagement from colleagues and
the obvious influence of the use of data on local quality improvement suggests the image of a
lone stroke expert deciphering local data, while the stroke team members are unaware of the
opportunities for quality improvement at their fingertips. Local Riksstroke stakeholders
aggregate and present data to peers and managers and find this rather simple. However, this
does not seem to increase engagement from peers. Our previous study showed that staff
members engaged in Riksstroke at the stroke unit level are aware of the need to identify
unique selling points to involve their colleagues.13 But more collaborative efforts and an
understanding of quality improvement are necessary if the data is to help improve stroke care
and not just provide feedback. Managers are often considered key to support clinical quality
improvement,13 14 31 which our findings also support. But our results show that peer support is
just as important, if not more so, to keep up the momentum to improve stroke care based on a
NQR like Riksstroke. This factor had the strongest association with the unit’s use of
Riksstroke data for quality improvement. The need for team collaboration and support among
co-workers is congruent with findings from studies on quality improvement,32 suggesting that
successful quality improvement is a joint effort, and support from others is a motivating factor
for facilitating improvement.33 The importance of interplay between the adoption of
innovations34 by individuals and organisations further emphasizes the motivating impact of
others being engaged in the same issues as oneself. Improvements are social processes, and
relationships and communication are thus significant for quality improvement. Leaders are
important in quality improvement,35 but locally appointed staff working with the registry
apparently need staff members to engage to improve stroke care.
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Methodological considerations
Sweden has a universal, comprehensive and tax-based healthcare system similar to those of
larger nations like Australia, the United Kingdom and Canada. As a result, experiences with
NQRs in Sweden may be relevant to registry initiatives in other countries. Riksstroke is a
well-known and acclaimed registry, giving this study the potential to pinpoint factors that
facilitate quality improvements to stroke care and other similar registries.
The match between the indexes constructed a priori and the factors identified in the factor
analysis worked out relatively well. To facilitate the interpretation of the regression analysis,
we chose to keep the theoretically constructed indexes instead of using the factor solution.
Given our cross-sectional design, the results cannot distinguish between cause and effect.
While we have not tested for causation, it is reasonable to believe that the identified
associations are not unidirectional, but rather that there are feedback loops.
Conclusions
Previous studies have shown that besides being a rich source for research, a NQR such as
Riksstroke can provide opportunities for local stroke care quality improvement. This study
represents 97% of all stroke units across Sweden and a broad scope of managers, physicians
and nurses involved in the local assignment with Riksstroke; we found that most participants
considered Riksstroke to enable comparisons using relevant and reliable data, and resources
spent on Riksstroke to be worthwhile. Yet, data analyses and quality improvements based on
the data received less attention than the registration of data. In addition, the use of Riksstroke
data for quality improvement initiatives was strongly related to the interest and engagement of
fellow stroke care staff and managers. This is a call for further initiatives to engage entire
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stroke teams in enhancing the potential for applying registry data in planning, performing and
evaluating initiatives to improve stroke care.
Acknowledgement
We are grateful to the researchers and clinicians who participated in the validation of the
survey tool and to all respondents who completed the survey.
Funding
The research leading to these results was supported by the Swedish Association of Local
Authorities and Regions (SALAR).
Competing interests
The authors declare that we have no competing interests. The dataset is available at Uppsala
University, Sweden.
Contributions
All authors participated in designing the study, and drafting and testing the survey. Validation
was performed by SV. TD performed the analyses in dialogue with ACE, LW and MF. ACE,
UW, LW and MF attained funding for the study. ACE drafted the paper and completed it in
collaboration with all authors, who have approved the final version prior to submission.
Data Sharing
The complete dataset is available at Uppsala University, Sweden.
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21. van der Veer SN, de Keizer NF, Ravelli AC, et al. Improving quality of care. A systematic
review on how medical registries provide information feedback to health care providers. Int J
Med Inform 2010;79:305-23.
22. Sigsbee B, Bever CTJ, Jones LKJ. Practice improvement requires more than guidelines
and quality measures. Neurology 2016;86:188-93.
23. Schwamm L, Reeves MJ, Frankel M. Designing a sustainable national registry for stroke
quality improvement. Am J Prev Med 2006;31:S251-7.
24. Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, et al. Audit
and feedback: effects on professional practice and healthcare outcomes. Cochrane Database
Syst Rev 2012;6:CD00025.
25. Larsson S, Lawyer P, Garellick G, et al. Use of 13 disease registries in 5 countries
demonstrates the potential to use outcome data to improve health care's value. Health Aff
(Millwood) 2012;31:220-7.
26. Evans SM, Bohensky M, Cameron PA, et al. A survey of Australian clinical registries:
Can quality of care be measured? Intern Med J 2011;41:42-8.
27. Chung SC, Sundström J, Gale CP, et al. Comparison of hospital variation in acute
myocardial infarction care and outcome between Sweden and United Kingdom: population
based cohort study using nationwide clinical registries. BMJ 2015;351:h3913.
28. Batalden P, Davidoff F. Teaching quality improvement: The devil is in the details. JAMA
2007;298:1059-61.
29. Levay C. Policies to foster quality improvement registries: lessons from the Swedish case.
J Intern Med 2016;279:160-72.
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30. Salinas J, Sprinkhuizen SM, Ackerson T, et al. An international standard set of patient-
centered outcome measures after stroke. Stroke 2016;47:180-6.
31. Aarons GA, Ehrhart MG, Farahnak LR, et al. Aligning leadership across systems and
organizations to develop a strategic climate for evidence-based practice implementation. Annu
Rev Public Health 2014;35:255-74.
32. Daudelin DH, Kulick ER, D'Amore K, et al. The Massachusetts Emergency Medical
Service Stroke Quality Improvement Collaborative, 2009-2012. Prev Chronic Dis
2013;10:E161.
33. LaBresh KA, Registry PCNAS. Quality of acute stroke care improvement framework for
the paul coverdell national acute stroke registry: Facilitating policy and system change at the
hospital level. Am J Prev Med 2006;31:S246-50.
34. Rogers EM. Diffusion of innovations. New York, USA: Free Press; 2003.
35. Ovretveit J. Improvement leaders: What do they and should they do? A summary of a
review of research. Qual Saf Health Care 2010;19:490-2.
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Supplementary files
I. Overview of the KVAK web survey content and structure (English version)
II. The dependent and independent variables
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I. Overview of the KVAK web survey content and structure (English version)
Section A. Background
Item number Items
1-5
My: sex, age, professional role, role in the
local work with the registry, and number of
years in registry role
Section B. Quality of care and access to resources
Item number Items Response alternatives
6-7 Quality of Stroke Care Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
8 Quality of Local Data Likert scale, five
alternatives ranging from
Very Poor to Very Good
Section C. Data from the quality registry
Item number Items Response alternatives
9-13 Riksstroke data Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
Section D. Organisational conditions for registry work
Item number Items Response alternatives
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14-16 Resources for entry and
analysis of data and quality
improvements
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
17-19 Managers’ support Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
20-23 Where I turn for support Five alternatives, at
department, hospital,
regional and national level
24-28 Support received Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
Section E. My use of registry data
Item number Items Response alternatives
29-30 Simplicity in retrieving and
reporting data/output
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
31 Motivation Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
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32-37 My role in the data
management process (from
entering data, to analysis, and
stroke care quality
improvement)
Likert scale, four
alternatives ranging from
Never to Often
Section F. The organisation’s use of registry data
Item number Items Response alternatives
38-45 Our use of the Riksstroke data,
in general and in quality
improvement
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
46-49 Others’ interest in our results
in Riksstroke
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
Section G. Concluding question
Item number Item Response alternatives
50 Efforts in relation to use of
Riksstroke
Likert scale, five
alternatives ranging from
Strongly Disagree to
Strongly Agree
The KVAK survey is licensed as a CC Attribution-NonCommercial (CC BY-NC) product.
For further communication and access to the survey, please contact Associate Professor
Ulrika Winblad, Uppsala University, Sweden at: [email protected] Further
details on the license can be found at https://creativecommons.org/
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II. The dependent and independent variables
In a series of dialogues, the research team identified sets of variables representing specific
constructs by processing: previous research (our own and others’, collated in a literature
review); theoretical aspects of the implementation of innovations and evidence-based practice,
and understanding of NQRs at the macro, meso and micro levels. We eventually arrived at
five indexes and seven single items.
Firstly, the dependent variable was created, representing Respondent’s depiction of their
stroke unit’s use of registry data. This includes items 39-45 (from section F in the
survey), hence the following follow-up items to the opening line “In my department,
we…”:
o use the registry indicators in our activity plan;
o perform own analyses of our data in the registry;
o use registry data to identify issues where there is a need to change;
o carry out the improvements which we have deemed necessary based on our results
in the registry;
o regularly present our results in the registry to members of staff;
o use registry data to compare our results to similar organisations, and
o use registry data when introducing new clinical methods and procedures.
All items in the index use a Likert scale approach for responses, with five alternatives ranging
from Strongly Disagree to Strongly Agree. The categorization of response alternatives was
non-agreement vs. agreement, with a cut-off at “Agree”.
Secondly, the indexes of independent variables convey:
Data Quality and Usefulness, includes items 9-13 (section C), i.e., follow-up items to the
opening line “Data from the registry…”: are of high quality; capture the essential aspects
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of quality of care; are a useful tool for identifying improvement areas; enable reliable
internal comparisons over time, and enable reliable external comparisons with other
organisations registering in Riksstroke. Again, the categorization of response alternatives
was non-agreement vs. agreement, with a cut-off at “Agree”.
Support from Outer Setting includes follow-up items 25-27 (from section D) to the
opening line “I get the support I ask for from…”: support functions at the hospital; the
county council (equivalent to region), and a regional registry centre. The categorization of
response alternatives was non-agreement vs. agreement, with a cut-off at “Agree”.
Resources consists of item 7 from section B: “I believe the care of our stroke patients has
sufficient resources to maintain a high quality”, and items 14-16 from section D,
following the opening line “We have sufficient resources (for example, allocated time and
competence) to…”: enter complete mandatory data in the registry; analyse outdata from
the registry, and perform improvement work based on registry data. Yet again, the
categorization of response alternatives was non-agreement vs. agreement, with a cut-off at
“Agree”.
Management Request for Registry Data includes item 17, “My manager (the manager I
report to) calls for data from the registry”, and items 47-49, all follow-ups to an opening
line from section D, “Our results in Riksstroke are called for by”: department managers;
the hospital board of directors, and the county council board (equivalent to region). An
identical categorization of response alternatives as above was made, that is to say non-
agreement vs. agreement, with a cut-off at “Agree”.
Management Involvement in Registry-based Quality Improvement originates from
section D (items 18 and 19) and its follow-up items, 18 and 19, to “My manager …”:
“supports improvement work initiated by others based on registry data”, and “initiates
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improvement work based on registry data”. Once again, categorization of response
alternatives was non-agreement vs. agreement, with a cut-off at “Agree”.
Thirdly, a number of single items were included as independent variables:
Item 8, “I consider our results in Riksstroke to be…”. This item was accompanied by
an alternative Likert scale ranging from “Very Poor” to” Very Good”. The
categorization of response alternatives was “Poor” versus “Good”, with a cut-off at
“Rather Good”.
Item 24, “I get the support I ask for from my own department.”
Item 28, “I get the support I ask for from the registry organisation.”
Item 29, “It is simple to retrieve registry data.”
Item 30, “It is simple to explain our department’s results to colleagues and managers.”
Item 31, “I am motivated to improve the stroke care we provide as a result of our
results in the registry.”
Item 46, “Our results in Riksstroke are called for by the department’s members of
staff.”
The six latter single items applied the same Likert scale approach for responses as described
above, that is, with five alternatives ranging from “Strongly Disagree” to “Strongly Agree”.
Thus, the categorization of response alternatives was non-agreement vs. agreement, with a
cut-off at “Agree”.
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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cross-sectional studies
Section/Topic Item
# Recommendation Reported on page #
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract 1
(b) Provide in the abstract an informative and balanced summary of what was done and what was found 1
Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 2-3
Objectives 3 State specific objectives, including any prespecified hypotheses 3
Methods
Study design 4 Present key elements of study design early in the paper 4
Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data
collection
5
Participants
6
(a) Give the eligibility criteria, and the sources and methods of selection of participants 5
Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if
applicable
6, and
Supplementary file II
Data sources/
measurement
8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe
comparability of assessment methods if there is more than one group
4-5
Bias 9 Describe any efforts to address potential sources of bias 4 and 5
Study size 10 Explain how the study size was arrived at 5
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and
why
5-6, Table 1, and
Supplementary file II
Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding 10-11
(b) Describe any methods used to examine subgroups and interactions n/a
(c) Explain how missing data were addressed 17
(d) If applicable, describe analytical methods taking account of sampling strategy n/a
(e) Describe any sensitivity analyses n/a
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Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility,
confirmed eligible, included in the study, completing follow-up, and analysed
11
(b) Give reasons for non-participation at each stage 11
(c) Consider use of a flow diagram n/a
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential
confounders
11, and Table 2
(b) Indicate number of participants with missing data for each variable of interest Table 2 footnote (p
17)
Outcome data 15* Report numbers of outcome events or summary measures 17, and Table 5
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence
interval). Make clear which confounders were adjusted for and why they were included
17, and Table 4 and
5
(b) Report category boundaries when continuous variables were categorized 13, and Table 3
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period n/a
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses n/a
Discussion
Key results 18 Summarise key results with reference to study objectives 19-21
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and
magnitude of any potential bias
21
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from
similar studies, and other relevant evidence
21
Generalisability 21 Discuss the generalisability (external validity) of the study results 21
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on
which the present article is based
22
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE
checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.
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