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Using Existing Clinical Information Models for Dutch Quality Registries to Reuse Data and Follow COUMT Paradigm.
Schepens, Maike H J; Trompert, Annemarie C; van Hooff, Miranda L; van der Velde, Erik; Kallewaard, Marjon; Verberk-Jonkers, Iris J A M; Cense, Huib A; Somford, Diederik M; Repping, Sjoerd; Tromp, Selma C; Wouters, Michel W J M.
Afiliación
  • Schepens MHJ; Cirka BV, Healthcare Strategy and Innovation, Zeist, The Netherlands.
  • Trompert AC; Department of Biomedical Data Sciences, LUMC, Leiden, The Netherlands.
  • van Hooff ML; Dutch Institute for Clinical Auditing, Leiden, The Netherlands.
  • van der Velde E; Department of Orthopedics, Radboud UMC, Nijmegen, The Netherlands.
  • Kallewaard M; Department of Orthopedics, Sint Maartenskliniek, Nijmegen, The Netherlands.
  • Verberk-Jonkers IJAM; Dutch Association of Medical Specialists, Utrecht, The Netherlands.
  • Cense HA; Zorgverbeteraars, Healthcare IT Consulting, Roden, The Netherlands.
  • Somford DM; Dutch Association of Medical Specialists, Utrecht, The Netherlands.
  • Repping S; Dutch Association of Medical Specialists, Utrecht, The Netherlands.
  • Tromp SC; Department of Nephrology, Maasstad Hospital, Rotterdam, The Netherlands.
  • Wouters MWJM; Department of Surgery, Rode Kruis Hospital, Beverwijk, The Netherlands.
Appl Clin Inform ; 14(2): 326-336, 2023 03.
Article en En | MEDLINE | ID: mdl-37137338
ABSTRACT

BACKGROUND:

Reuse of health care data for various purposes, such as the care process, for quality measurement, research, and finance, will become increasingly important in the future; therefore, "Collect Once Use Many Times" (COUMT). Clinical information models (CIMs) can be used for content standardization. Data collection for national quality registries (NQRs) often requires manual data entry or batch processing. Preferably, NQRs collect required data by extracting data recorded during the health care process and stored in the electronic health record.

OBJECTIVES:

The first objective of this study was to analyze the level of coverage of data elements in NQRs with developed Dutch CIMs (DCIMs). The second objective was to analyze the most predominant DCIMs, both in terms of the coverage of data elements as well as in their prevalence across existing NQRs.

METHODS:

For the first objective, a mapping method was used which consisted of six steps, ranging from a description of the clinical pathway to a detailed mapping of data elements. For the second objective, the total number of data elements that matched with a specific DCIM was counted and divided by the total number of evaluated data elements.

RESULTS:

An average of 83.0% (standard deviation 11.8%) of data elements in studied NQRs could be mapped to existing DCIMs . In total, 5 out of 100 DCIMs were needed to map 48.6% of the data elements.

CONCLUSION:

This study substantiates the potential of using existing DCIMs for data collection in Dutch NQRs and gives direction to further implementation of DCIMs. The developed method is applicable to other domains. For NQRs, implementation should start with the five DCIMs that are most prevalently used in the NQRs. Furthermore, a national agreement on the leading principle of COUMT for the use and implementation for DCIMs and (inter)national code lists is needed.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Atención a la Salud / Registros Electrónicos de Salud Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Appl Clin Inform Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Atención a la Salud / Registros Electrónicos de Salud Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Appl Clin Inform Año: 2023 Tipo del documento: Article País de afiliación: Países Bajos