BMJ Open · BMJ Open: first published as 10.1136/bmjopen-2016-011562 on 9 November 2016. Downloaded from . For peer review only 4 particular diagnoses, treatment interventions, and

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

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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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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Word count

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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


are a useful tool for

identifying improvement

areas 0.66


enable reliable internal

comparisons over time

0.52


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



allocated time and

competence) to analyse

outdata from the registry -0.79



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


for from the county council

(equivalent to region) 0.74


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



hospital’s board of directors 0.99


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


for from my own

department 0.54

30. It is simple to explain

our department’s results to

colleagues and managers

0.59



department’s members of

staff

8. I consider our results in

Riksstroke to be…


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)


of quality of care

136 (84)



areas

142 (88)



145 (89)




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)



registry data

94 (59)

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initiates improvement work


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


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


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


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


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


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


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.

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improvement. U.S. Department of Health and Human Services website.

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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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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


Very Poor to Very Good

Section C. Data from the quality registry


9-13 Riksstroke data Likert scale, five


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Strongly Agree

Section D. Organisational conditions for registry work


14-16 Resources for entry and

analysis of data and quality

improvements

Likert scale, five



Strongly Agree

17-19 Managers’ support Likert scale, five



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



Strongly Agree

Section E. My use of registry data


29-30 Simplicity in retrieving and

reporting data/output

Likert scale, five



Strongly Agree

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31 Motivation Likert scale, five



Strongly Agree

32-37 My role in the data

management process (from

entering data, to analysis, and

stroke care quality

improvement)

Likert scale, four


Never to Often

Section F. The organisation’s use of registry data


38-45 Our use of the Riksstroke data,

in general and in quality

improvement

Likert scale, five



Strongly Agree

46-49 Others’ interest in our results

in Riksstroke

Likert scale, five



Strongly Agree

Section G. Concluding question

Item number Item Response alternatives

50 Efforts in relation to use of

Riksstroke

Likert scale, five



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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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


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


BMJ Open on A

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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


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allocated time and

competence) to enter

complete mandatory


-0.82



allocated time and

competence) to analyse

data from the registry -0.79



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


ask for from the county

council (equivalent to

region)

0.74


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



registry 0.66

47. Our results in

Riksstroke are called for

by the department

managers 0.83

48. Our results in


by the hospital’s board

of directors 0.99

49. Our results in


by the county council

board (equivalent to

region) 0.94

Management

Involvement

in Registry-

based

Quality

Improvement

18. My manager (the


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)


initiates improvement

work based on registry

data

Included as

single items


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


by the department’s

members of staff

8. I consider our results

in Riksstroke to be…


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


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)


of quality of care

136 (84)



areas

142 (88)



145 (89)




Riksstroke

126 (77)

We have sufficient resources

(for example, allocated time

and competence) to…

enter complete mandatory


88 (54)

analyse data from the registry 69 (42)

perform improvement work


64 (40)

My manager (the manager I

report to)…


registry

102 (63)



registry data

94 (59)

initiates improvement work


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


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


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


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


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


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


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


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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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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Supplementary files



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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


6-7 Quality of Stroke Care Likert scale, five



Strongly Agree

8 Quality of Local Data Likert scale, five


Very Poor to Very Good

Section C. Data from the quality registry


9-13 Riksstroke data Likert scale, five



Strongly Agree

Section D. Organisational conditions for registry work


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14-16 Resources for entry and

analysis of data and quality

improvements

Likert scale, five



Strongly Agree

17-19 Managers’ support Likert scale, five



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



Strongly Agree

Section E. My use of registry data


29-30 Simplicity in retrieving and

reporting data/output

Likert scale, five



Strongly Agree

31 Motivation Likert scale, five



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


Never to Often

Section F. The organisation’s use of registry data


38-45 Our use of the Riksstroke data,

in general and in quality

improvement

Likert scale, five



Strongly Agree

46-49 Others’ interest in our results

in Riksstroke

Likert scale, five



Strongly Agree

Section G. Concluding question

Item number Item Response alternatives

50 Efforts in relation to use of

Riksstroke

Likert scale, five



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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mailto:[email protected]

https://creativecommons.org/



1


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


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


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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