Evidence map›Paper›PMID 33120412›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2021

Associations of physicians' prescribing experience, work hours, and workload with prescription errors.

Ilona Leviatan, Bernice Oberman, Eyal Zimlichman, Gideon Y Stein

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  6. GP workload and patient safety.The British journal of general practice : the journal of the Royal College of General Practitioners · 2024
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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.

Ilona LeviatanSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0002-5606-0980
Bernice ObermanGertner Institute for Epidemiology and Health Policy Research, Tel HaShomer, Ramat Gan, Israel.
Eyal ZimlichmanSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Gideon Y SteinSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0001-8510-9803

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe aimed to assess associations of physician's work overload, successive work shifts, and work experience with physicians' risk to err. MATERIALS AND

methodsThis large-scale study included physicians who prescribed at least 100 systemic medications at Sheba Medical Center during 2012-2017 in all acute care departments, excluding intensive care units. Presumed medication errors were flagged by a high-accuracy computerized decision support system that uses machine-learning algorithms to detect potential medication prescription errors. Physicians' successive work shifts (first or only shift, second, and third shifts), workload (assessed by the number of prescriptions during a shift) and work-experience, as well as a novel measurement of physicians' prescribing experience with a specific drug, were assessed per prescription. The risk to err was determined for various work conditions.

results1 652 896 medical orders were prescribed by 1066 physicians; The system flagged 3738 (0.23%) prescriptions as erroneous. Physicians were 8.2 times more likely to err during high than normal-low workload shifts (5.19% vs 0.63%, P < .0001). Physicians on their third or second successive shift (compared to a first or single shift) were more likely to err (2.1%, 1.8%, and 0.88%, respectively, P < .001). Lack of experience in prescribing a specific medication was associated with higher error rate (0.37% for the first 5 prescriptions vs 0.13% after over 40, P < .001). DISCUSSION: Longer hours and less experience in prescribing a specific medication increase risk of erroneous prescribing.

conclusionRestricting successive shifts, reducing workload, increasing training and supervision, and implementing smart clinical decision support systems may help reduce prescription errors.

Indexed as

Medical Staff, HospitalWorkloadAcademic Medical CentersClinical CompetenceDatasets as TopicFatigueHumansIsraelMedication ErrorsPractice Patterns, Physicians'adverse drug eventsclinical decision support systemphysician fatigueprescription errors

Identifiers

PMID33120412
PMCPMC8200263

What OpenQuestion holds

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Registered trials

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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.