Evidence map›Paper›PMID 34837238›Full record

ArticleBritish journal of clinical pharmacology2022

Clinical validation of clinical decision support systems for medication review: A scoping review.

Birgit A Damoiseaux-Volman, Stephanie Medlock, Delanie M van der Meulen, Jesse de Boer, Johannes A Romijn, Nathalie van der Velde, Ameen Abu-Hanna

Abstract readScoping Review
In one paragraph

Article in British journal of clinical pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
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  9. Review
  10. Article
  11. Article
  12. Polypharmacy and precision medicine.Cambridge prisms. Precision medicine · 2023
    Review
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Birgit A Damoiseaux-VolmanDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0003-2779-8211
Stephanie MedlockDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0002-2679-8095
Delanie M van der MeulenDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0002-1678-2057
Jesse de BoerDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0001-9859-1774
Johannes A RomijnDepartment of Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0003-0676-0409
Nathalie van der VeldeSection of Geriatric Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0002-6477-6209
Ameen Abu-HannaDepartment of Medical Informatics, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0003-4324-7954

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this scoping review is to summarize approaches and outcomes of clinical validation studies of clinical decision support systems (CDSSs) to support (part of) a medication review. A literature search was conducted in Embase and Medline. In total, 30 articles validating a CDSS were ultimately included. Most of the studies focused on detection of adverse drug events, potentially inappropriate medications and drug-related problems. We categorized the included articles in three groups: studies subjectively reviewing the clinical relevance of CDSS's output (21/30 studies) resulting in a positive predictive value (PPV) for clinical relevance of 4-80%; studies determining the relationship between alerts and actual events (10/30 studies) resulting in a PPV for actual events of 5-80%; and studies comparing output of CDSSs to chart/medication reviews in the whole study population (10/30 studies) resulting in a sensitivity of 28-85% and specificity of 42-75%. We found heterogeneity in the methods used and in the outcome measures. The validation studies did not report the use of a published CDSS validation strategy. To improve the effectiveness and uptake of CDSSs supporting a medication review, future research would benefit from a more systematic and comprehensive validation strategy.

Indexed as

Decision Support Systems, ClinicalDrug-Related Side Effects and Adverse ReactionsHumansMedication ReviewOutcome Assessment, Health CarePotentially Inappropriate Medication Listadverse drug eventsclinical decision support systemsinappropriate prescriptionsvalidation studies

Identifiers

PMID34837238
PMCPMC9299995

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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.