Evidence map›Paper›PMID 40355281›Full record

ArticleBMJ health & care informatics2025

Leveraging real-world data for continuous evaluation of computational clinical practice guidelines.

Kees C W J Ebben, Cornelis D de Kroon, Channa E Schmeink, Olga L van der Hel, Thijs van Vegchel, Michèle Thissen, Ignace H J T de Hingh, Jurrian van der Werf

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Article in BMJ health & care informatics, 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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Kees C W J EbbenDepartment of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands k.ebben@iknl.nl.ORCID http://orcid.org/0000-0003-1069-2357
Cornelis D de KroonDepartment of Obstetrics and Gynecology, Leiden University Medical Center, Leiden, The Netherlands.
Channa E SchmeinkDepartment of Obstetrics and Gynecology, Anna Hospital, Geldrop, The Netherlands.
Olga L van der HelDepartment of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands.
Thijs van VegchelDepartment of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands.
Michèle ThissenDepartment of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands.
Ignace H J T de HinghDepartment of Epidemiology, GROW-school for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
Jurrian van der WerfDepartment of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThere is a bidirectional interaction between clinical practice guidelines and clinical care, with each informing the other. Structural signalling of trends in guideline adherence in clinical practice is essential for advanced updates. Recent advances in computable care guidelines allow automated evaluation using real-world registry data. Here, we assess the feasibility by evaluating adherence to Dutch endometrial cancer (EC) guidelines.

methodsThis retrospective cohort study uses real-world data of EC patients from the Netherlands Cancer Registry (NCR) between January 2010 and May 2022. The Dutch guideline for EC was parsed into clinical decision trees (CDTs). Primary outcome was guideline adherence for multiple (sub)populations, with secondary outcomes encompassing adherence trends, recommendation implementation pace, non-adherent treatment strategies and impact of additional non-guideline-based patient and tumour characteristics on adherence.

resultsThe Dutch EC guideline was parsed into 10 CDTs, revealing 22 patient and disease characteristics and 46 interventions. NCR data were mapped to CDT data items. Four CDTs were successfully populated with NCR data, and 21 602 cases were assessed. Adherence levels were computed, which showed a mean adherence of 82.7% (range 44-100%). Three statistically significant trends in adherence were identified: two increasing trends in the 'non-adherent' compared with the 'adherent' group, and one decreasing trend. DISCUSSION: This study introduces a novel framework for continuously evaluating (non-)adherence to cancer guidelines. Future efforts should focus on the inclusion of health outcome measurements.

conclusionThrough the integration of real-world data with a computer-interpretable guideline, we effectively calculated various facets of adherence to guidelines for EC.

Indexed as

Endometrial NeoplasmsGuideline AdherencePractice Guidelines as TopicAgedFemaleHumansMiddle AgedNetherlandsRegistriesRetrospective StudiesCommon Data ElementsDecision TreesElectronic Data ProcessingHealth Information InteroperabilityMedical Informatics Computing

Identifiers

PMID40355281
PMCPMC12083447

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