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Interventions to increase attendance for diabetic retinopathy screening

Overview of attention for article published in Cochrane database of systematic reviews, January 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
2 news outlets
policy
2 policy sources
twitter
53 tweeters
facebook
2 Facebook pages
wikipedia
1 Wikipedia page

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
327 Mendeley
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Title
Interventions to increase attendance for diabetic retinopathy screening
Published in
Cochrane database of systematic reviews, January 2018
DOI 10.1002/14651858.cd012054.pub2
Pubmed ID
Authors

John G Lawrenson, Ella Graham-Rowe, Fabiana Lorencatto, Jennifer Burr, Catey Bunce, Jillian J Francis, Patricia Aluko, Stephen Rice, Luke Vale, Tunde Peto, Justin Presseau, Noah Ivers, Jeremy M Grimshaw

Abstract

Despite evidence supporting the effectiveness of diabetic retinopathy screening (DRS) in reducing the risk of sight loss, attendance for screening is consistently below recommended levels. The primary objective of the review was to assess the effectiveness of quality improvement (QI) interventions that seek to increase attendance for DRS in people with type 1 and type 2 diabetes.Secondary objectives were:To use validated taxonomies of QI intervention strategies and behaviour change techniques (BCTs) to code the description of interventions in the included studies and determine whether interventions that include particular QI strategies or component BCTs are more effective in increasing screening attendance;To explore heterogeneity in effect size within and between studies to identify potential explanatory factors for variability in effect size;To explore differential effects in subgroups to provide information on how equity of screening attendance could be improved;To critically appraise and summarise current evidence on the resource use, costs and cost effectiveness. We searched the Cochrane Library, MEDLINE, Embase, PsycINFO, Web of Science, ProQuest Family Health, OpenGrey, the ISRCTN, ClinicalTrials.gov, and the WHO ICTRP to identify randomised controlled trials (RCTs) that were designed to improve attendance for DRS or were evaluating general quality improvement (QI) strategies for diabetes care and reported the effect of the intervention on DRS attendance. We searched the resources on 13 February 2017. We did not use any date or language restrictions in the searches. We included RCTs that compared any QI intervention to usual care or a more intensive (stepped) intervention versus a less intensive intervention. We coded the QI strategy using a modification of the taxonomy developed by Cochrane Effective Practice and Organisation of Care (EPOC) and BCTs using the BCT Taxonomy version 1 (BCTTv1). We used Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital (PROGRESS) elements to describe the characteristics of participants in the included studies that could have an impact on equity of access to health services.Two review authors independently extracted data. One review author entered the data into Review Manager 5 and a second review author checked them. Two review authors independently assessed risks of bias in the included studies and extracted data. We rated certainty of evidence using GRADE. We included 66 RCTs conducted predominantly (62%) in the USA. Overall we judged the trials to be at low or unclear risk of bias. QI strategies were multifaceted and targeted patients, healthcare professionals or healthcare systems. Fifty-six studies (329,164 participants) compared intervention versus usual care (median duration of follow-up 12 months). Overall, DRS attendance increased by 12% (risk difference (RD) 0.12, 95% confidence interval (CI) 0.10 to 0.14; low-certainty evidence) compared with usual care, with substantial heterogeneity in effect size. Both DRS-targeted (RD 0.17, 95% CI 0.11 to 0.22) and general QI interventions (RD 0.12, 95% CI 0.09 to 0.15) were effective, particularly where baseline DRS attendance was low. All BCT combinations were associated with significant improvements, particularly in those with poor attendance. We found higher effect estimates in subgroup analyses for the BCTs 'goal setting (outcome)' (RD 0.26, 95% CI 0.16 to 0.36) and 'feedback on outcomes of behaviour' (RD 0.22, 95% CI 0.15 to 0.29) in interventions targeting patients, and 'restructuring the social environment' (RD 0.19, 95% CI 0.12 to 0.26) and 'credible source' (RD 0.16, 95% CI 0.08 to 0.24) in interventions targeting healthcare professionals.Ten studies (23,715 participants) compared a more intensive (stepped) intervention versus a less intensive intervention. In these studies DRS attendance increased by 5% (RD 0.05, 95% CI 0.02 to 0.09; moderate-certainty evidence).Fourteen studies reporting any QI intervention compared to usual care included economic outcomes. However, only five of these were full economic evaluations. Overall, we found that there is insufficient evidence to draw robust conclusions about the relative cost effectiveness of the interventions compared to each other or against usual care.With the exception of gender and ethnicity, the characteristics of participants were poorly described in terms of PROGRESS elements. Seventeen studies (25.8%) were conducted in disadvantaged populations. No studies were carried out in low- or middle-income countries. The results of this review provide evidence that QI interventions targeting patients, healthcare professionals or the healthcare system are associated with meaningful improvements in DRS attendance compared to usual care. There was no statistically significant difference between interventions specifically aimed at DRS and those which were part of a general QI strategy for improving diabetes care. This is a significant finding, due to the additional benefits of general QI interventions in terms of improving glycaemic control, vascular risk management and screening for other microvascular complications. It is likely that further (but smaller) improvements in DRS attendance can also be achieved by increasing the intensity of a particular QI component or adding further components.

Twitter Demographics

The data shown below were collected from the profiles of 53 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 327 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 327 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 55 17%
Researcher 43 13%
Student > Bachelor 39 12%
Student > Ph. D. Student 35 11%
Student > Postgraduate 22 7%
Other 60 18%
Unknown 73 22%
Readers by discipline Count As %
Medicine and Dentistry 95 29%
Nursing and Health Professions 56 17%
Social Sciences 22 7%
Psychology 21 6%
Engineering 9 3%
Other 33 10%
Unknown 91 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 58. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2021.
All research outputs
#442,548
of 17,446,661 outputs
Outputs from Cochrane database of systematic reviews
#996
of 11,688 outputs
Outputs of similar age
#18,487
of 469,422 outputs
Outputs of similar age from Cochrane database of systematic reviews
#24
of 202 outputs
Altmetric has tracked 17,446,661 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,688 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.1. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 469,422 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 202 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.