Evidence map›Paper›PMID 37130626›Full record

ArticleBMJ health & care informatics2023

Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review.

Lucrezia Greta Armando, Gianluca Miglio, Pierluigi de Cosmo, Clara Cena

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ health & care informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 4 pooled it
–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

16 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

4 authors.

Lucrezia Greta ArmandoDepartment of Drug Science and Technology, University of Turin, Torino, Italy lucrezia.armando@edu.unito.it.ORCID http://orcid.org/0000-0001-9395-8047
Gianluca MiglioDepartment of Drug Science and Technology, University of Turin, Torino, Italy.
Pierluigi de CosmoInfologic srl, Padova, Italy.
Clara CenaDepartment of Drug Science and Technology, University of Turin, Torino, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveClinical decision support systems (CDSSs) can reduce medical errors increasing drug prescription appropriateness. Deepening knowledge of existing CDSSs could increase their use by healthcare professionals in different settings (ie, hospitals, pharmacies, health research centres) of clinical practice. This review aims to identify the characteristics common to effective studies conducted with CDSSs. MATERIALS AND

methodsThe article sources were Scopus, PubMed, Ovid MEDLINE and Web of Science, queried between January 2017 and January 2022. Inclusion criteria were prospective and retrospective studies that reported original research on CDSSs for clinical practice support; studies should describe a measurable comparison of the intervention or observation conducted with and without the CDSS; article language Italian or English. Reviews and studies with CDSSs used exclusively by patients were excluded. A Microsoft Excel spreadsheet was prepared to extract and summarise data from the included articles.

resultsThe search resulted in the identification of 2424 articles. After title and abstract screening, 136 studies remained, 42 of which were included for final evaluation. Most of the studies included rule-based CDSSs that are integrated into existing databases with the main purpose of managing disease-related problems. The majority of the selected studies (25 studies; 59.5%) were successful in supporting clinical practice, with most being pre-post intervention studies and involving the presence of a pharmacist. DISCUSSION AND

conclusionA number of characteristics have been identified that may help the design of studies feasible to demonstrate the effectiveness of CDSSs. Further studies are needed to encourage CDSS use.

Indexed as

Decision Support Systems, ClinicalDrug PrescriptionsHumansProspective StudiesRetrospective Studiesdecision support systems, clinicalelectronic health recordshealth information exchangehealth information systemsmedical informatics

Identifiers

PMID37130626
PMCPMC10163516

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.