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Damoiseaux-Volman BA, van der Velde N, Ruige SG, et al. Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors. JMIR Med Inform. 2021;9(7):e28023doi: 10.2196/28023.
Damoiseaux-Volman, B. A., van der Velde, N., Ruige, S. G., Romijn, J. A., Abu-Hanna, A., & Medlock, S. (2021). Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors. JMIR medical informatics, 9(7), e28023. https://doi.org/10.2196/28023
Damoiseaux-Volman, Birgit A, et al. "Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors." JMIR medical informatics vol. 9,7 (2021): e28023. doi: https://doi.org/10.2196/28023
Damoiseaux-Volman BA, van der Velde N, Ruige SG, Romijn JA, Abu-Hanna A, Medlock S. Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors. JMIR Med Inform. 2021 Jul 16;9(7):e28023. doi: 10.2196/28023. PMID: 34269682; PMCID: PMC8325084.
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JMIR Med Inform. 2021 Jul 16;9(7):e28023. doi: 10.2196/28023.

Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors.

JMIR medical informatics

Birgit A Damoiseaux-Volman, Nathalie van der Velde, Sil G Ruige, Johannes A Romijn, Ameen Abu-Hanna, Stephanie Medlock

Affiliations

  1. Department of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
  2. Section of Geriatric Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
  3. Department of Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.

PMID: 34269682 PMCID: PMC8325084 DOI: 10.2196/28023

Abstract

BACKGROUND: Clinical decision support systems (CDSSs) form an implementation strategy that can facilitate and support health care professionals in the care of older hospitalized patients.

OBJECTIVE: Our study aims to systematically review the effects of CDSS interventions in older hospitalized patients. As a secondary aim, we aim to summarize the implementation and design factors described in effective and ineffective interventions and identify gaps in the current literature.

METHODS: We conducted a systematic review with a search strategy combining the categories older patients, geriatric topic, hospital, CDSS, and intervention in the databases MEDLINE, Embase, and SCOPUS. We included controlled studies, extracted data of all reported outcomes, and potentially beneficial design and implementation factors. We structured these factors using the Grol and Wensing Implementation of Change model, the GUIDES (Guideline Implementation with Decision Support) checklist, and the two-stream model. The risk of bias of the included studies was assessed using the Cochrane Collaboration's Effective Practice and Organisation of Care risk of bias approach.

RESULTS: Our systematic review included 18 interventions, of which 13 (72%) were effective in improving care. Among these interventions, 8 (6 effective) focused on medication review, 8 (6 effective) on delirium, 7 (4 effective) on falls, 5 (4 effective) on functional decline, 4 (3 effective) on discharge or aftercare, and 2 (0 effective) on pressure ulcers. In 77% (10/13) effective interventions, the effect was based on process-related outcomes, in 15% (2/13) interventions on both process- and patient-related outcomes, and in 8% (1/13) interventions on patient-related outcomes. The following implementation and design factors were potentially associated with effectiveness: a priori problem or performance analyses (described in 9/13, 69% effective vs 0/5, 0% ineffective interventions), multifaceted interventions (8/13, 62% vs 1/5, 20%), and consideration of the workflow (9/13, 69% vs 1/5, 20%).

CONCLUSIONS: CDSS interventions can improve the hospital care of older patients, mostly on process-related outcomes. We identified 2 implementation factors and 1 design factor that were reported more frequently in articles on effective interventions. More studies with strong designs are needed to measure the effect of CDSS on relevant patient-related outcomes, investigate personalized (data-driven) interventions, and quantify the impact of implementation and design factors on CDSS effectiveness.

TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews): CRD42019124470; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=124470.

©Birgit A Damoiseaux-Volman, Nathalie van der Velde, Sil G Ruige, Johannes A Romijn, Ameen Abu-Hanna, Stephanie Medlock. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 16.07.2021.

Keywords: aged; clinical decision support systems; geriatrics; hospital; quality of care

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