Evidence map›Paper›PMID 40050038›Full record

ArticleBMJ open quality2025

Utilisation of a cocreation methodology to develop claims-based indicators for feedback on implementation of comparative effectiveness research results into practice.

Vera de Weerdt, Hanna Willems, Geeske Hofstra, Sjoerd Repping, Xander Koolman, Eric van der Hijden

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Article in BMJ open quality, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Vera de WeerdtHealth Economics, School of Business & Economics, Vrije Universiteit, Amsterdam, the Netherlands v.de.weerdt@vu.nl.ORCID http://orcid.org/0000-0003-3644-620X
Hanna WillemsDepartment of Geriatrics, University of Amsterdam, Amsterdam, the Netherlands.
Geeske HofstraZorginstituut Nederland, Diemen, the Netherlands.
Sjoerd ReppingUniversity of Amsterdam, Amsterdam, the Netherlands.
Xander KoolmanHealth Economics, School of Business & Economics, Vrije Universiteit, Amsterdam, the Netherlands.
Eric van der HijdenHealth Economics, School of Business & Economics, Vrije Universiteit, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionComparative effectiveness research (CER) often fails to create quality improvement since implementation of CER results in clinical practice is lacking. Claims-based Audit & Feedback (A&F) provides a resource efficient tool to stimulate implementation, but it is unknown whether medical professionals accept claims-based A&F in the context of CER. Therefore, in this study, we developed claims-based indicators using a cocreation approach and evaluated medical professionals' perception regarding the validity and acceptability of these indicators.

methodsBetween July 2019 and November 2021, we used a cocreation approach with medical experts to develop claims-based indicators for six CER trials. The aim is to use the indicators for group level feedback on implementation of CER results to medical professionals across all healthcare providers in the Netherlands. To build the indicators, we used the most recent available Dutch national healthcare-related claims data of the year 2017. The cocreation process consisted of the following steps: (1) defining the target indicator, (2) selecting relevant claims codes, (3) testing feasibility of the indicators using Dutch claims data, (4) discussing results of feasibility testing and (5) defining the final indicators and reflecting on the acceptability of the indicators for feedback on implementation of CER results by the experts.

resultsClaims-based indicators could not perfectly reflect the CER population for any of the six CER trials. However, the cocreation process did lead to a final indicator that medical experts found acceptable in four of six cases. Recommendations of medical experts for improving claims-based indicators included: select patients with minimal over- or underestimation of the CER population, use proxies to identify patients, determine incidence rather than prevalence for chronic conditions and use data linkage with diagnostic test results.

conclusionA cocreation approach was a successful way to develop claims-based indicators on implementation of CER results, which were imperfect, but in some cases still acceptable as feedback to medical experts. Thus, for certain topics, claims data may provide a resource efficient data source for A&F interventions aiming to implement CER trials.

Indexed as

Comparative Effectiveness ResearchFeedbackInsurance Claim ReviewHumansNetherlandsAudit and feedbackComparative effectiveness researchHealthcare quality improvementImplementation scienceQuality improvement

Identifiers

PMID40050038
PMCPMC11887289

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.