Abstract
Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component
of a learning healthcare system. Research shows that the effectiveness of CDS is mixed.
Multifaceted context, system, recommendation and implementation factors may potentially affect the success of
CDS interventions. This paper describes the development of a checklist that is intended to support professionals to
implement CDS successfully.
Methods: We developed the checklist through an iterative process that involved a systematic review of evidence
and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert
panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients
and healthcare consumers and pilot testing of the checklist.
Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for
guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains,
i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist
positively as an instrument that could support people implementing guideline-based CDS across a wide range of
settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality
improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy.
Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of
CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS
effectiveness. Relying on a structured approach may prevent that important factors are missed.
Keywords: Clinical computerised decision support systems, Practice Guidelines, Guideline adherence,
Evidence-based medicine, Implementation
of a learning healthcare system. Research shows that the effectiveness of CDS is mixed.
Multifaceted context, system, recommendation and implementation factors may potentially affect the success of
CDS interventions. This paper describes the development of a checklist that is intended to support professionals to
implement CDS successfully.
Methods: We developed the checklist through an iterative process that involved a systematic review of evidence
and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert
panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients
and healthcare consumers and pilot testing of the checklist.
Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for
guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains,
i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist
positively as an instrument that could support people implementing guideline-based CDS across a wide range of
settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality
improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy.
Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of
CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS
effectiveness. Relying on a structured approach may prevent that important factors are missed.
Keywords: Clinical computerised decision support systems, Practice Guidelines, Guideline adherence,
Evidence-based medicine, Implementation
| Original language | English |
|---|---|
| Pages (from-to) | 1-12 |
| Number of pages | 12 |
| Journal | Implementation Science |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 25 Jun 2018 |
Bibliographical note
Funding:This project has received funding from the EU’s Horizon 2020 Research and
Innovation Programme under the Marie Sklodowska-Curie grant agreement
No 654981. The funder was not involved in any parts of the research.
Research programs
- EMC NIHES-02-65-01
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