Evidence map›Paper›PMID 29572298›Full record

ArticleBMJ quality & safety2018

Impact of a commercial order entry system on prescribing errors amenable to computerised decision support in the hospital setting: a prospective pre-post study.

Sarah K Pontefract, James Hodson, Ann Slee, Sonal Shah, Alan J Girling, Robin Williams, Aziz Sheikh, Jamie J Coleman

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ quality & safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 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

8 authors.

Sarah K PontefractInstitute of Clinical Sciences, University of Birmingham, Birmingham, UK.
James HodsonUniversity Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
Ann SleeDigital Technology, NHS England, London, UK.
Sonal ShahInstitute of Clinical Sciences, University of Birmingham, Birmingham, UK.
Alan J GirlingInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.
Robin WilliamsInstitute for the Study of Science, University of Edinburgh, Edinburgh, UK.
Aziz SheikhUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
Jamie J ColemanUniversity Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn this UK study, we investigated the impact of computerised physician order entry (CPOE) and clinical decision support (CDS) implementation on the rate of 78 high-risk prescribing errors amenable to CDS.

methodsWe conducted a preintervention/postintervention study in three acute hospitals in England. A predefined list of prescribing errors was incorporated into an audit tool. At each site, approximately 4000 prescriptions were reviewed both pre-CPOE and 6 months post-CPOE implementation. The number of opportunities for error and the number of errors that occurred were collated. Error rates were then calculated and compared between periods, as well as by the level of CDS.

resultsThe prescriptions of 1244 patients were audited pre-CPOE and 1178 post-CPOE implementation. A total of 28 526 prescriptions were reviewed, with 21 138 opportunities for error identified based on 78 defined errors. Across the three sites, for those prescriptions where opportunities for error were identified, the error rate was found to reduce significantly post-CPOE implementation, from 5.0% to 4.0% (P<0.001). CDS implementation by error type was found to differ significantly between sites, ranging from 0% to 88% across clinical contraindication, dose/frequency, drug interactions and other error types (P<0.001). Overall, 43/78 (55%) of the errors had some degree of CDS implemented in at least one of the hospitals.

conclusionsImplementation of CPOE with CDS was associated with clinically important reductions in the rate of high-risk prescribing errors. Given the pre-post design, these findings however need to be interpreted with caution. The occurrence of errors was found to be highly dependent on the level of restriction of CDS presented to the prescriber, with the effect that different configurations of the same CPOE system can produce very different results.

Indexed as

Decision Support Systems, ClinicalHospitalsHumansMedical AuditMedical Order Entry SystemsMedication ErrorsMedication Systems, HospitalPilot ProjectsProspective StudiesQuality ImprovementState MedicineUnited Kingdomdecision support, clinicaldecision support, computerizedhospital medicinemedication safety

Identifiers

PMID29572298
PMCPMC6109251

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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.