Evidence map›Paper›PMID 35428282›Full record

ArticleBMC medical informatics and decision making2022

Retrospective descriptive assessment of clinical decision support medication-related alerts in two Saudi Arabian hospitals.

Jamilah Ahmed Alsaidan, Jane Portlock, Sondus I Ata, Hisham S Aljadhey, Bryony Dean Franklin

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Computer-Assisted Clinical Diagnosis and Treatment.Current allergy and asthma reports · 2023
    Review
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

5 authors.

Jamilah Ahmed AlsaidanKing Saud University, Riyadh, Kingdom of Saudi Arabia. jalsaidan@ksu.edu.sa.
Jane PortlockSchool of Life Sciences, University of Sussex, Brighton, UK.
Sondus I AtaDepartment of Pharmacy Services, King Saud University Medical City, Riyadh, Saudi Arabia.
Hisham S AljadheySaudi Food and Drug Authority, Riyadh, Saudi Arabia.
Bryony Dean FranklinUCL School of Pharmacy, University College London, London, UK.

Funding

Department of Health
6 · The paper itself

Abstract

objectivesTo determine the frequency of clinical decision support system (CDSS) medication-related alerts generated, accepted, or overridden, to assess appropriateness of alert display and overrides, and to characterise the documentation of clinician justification for these overrides in an academic medical centre in Saudi Arabia. MATERIALS AND

methodsSystem-generated CDSS reports for the period June 2015 to December 2017 were retrospectively reviewed and analysed. Alerts were classified into different types, and rates of alert overrides calculated as percentages of all generated alerts. A subset of 307 overridden alerts was assessed for appropriateness of display and override by two clinical pharmacists. Physician documentation of reasons for overriding alerts were categorised.

resultsA total of 4,446,730 medication-related alerts were generated from both inpatient and outpatient settings, and 4,231,743 (95.2%) were overridden. The most common alert type was 'duplicate drug', accounting for 3,549,736 (79.8%) of alerts. Of 307 alerts assessed for appropriateness, 246 (80%) were judged to be appropriately displayed and 244 (79%) were overridden appropriately. New drug allergy and drug allergy alerts had the highest percentage of being judged as inappropriately overridden. For 1,594,313 alerts (37.7%), 'no overridden reason selected' was chosen from the drop-down menu.

conclusionsThe alert generation and override rate were higher than reported previously in the literature. The small sample size of 307 alerts assessed for appropriateness of alert display and override is a potential limitation. Revision of the CDSS rules for alerts (focusing on specificity and relevance for the local context) is now recommended. Future research should prospectively assess providers' perspectives, and determine patient harm associated with overridden alerts.

Indexed as

Decision Support Systems, ClinicalDrug HypersensitivityMedical Order Entry SystemsDrug InteractionsHospitalsHumansRetrospective StudiesSaudi ArabiaClinical (MeSH)Computerised provider order systems (MeSH)Decision support systemsMedication alert systems (MeSH)Medication error (MeSH)

Identifiers

PMID35428282
PMCPMC9012024

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.