Evidence map›Paper›PMID 37105228›Full record

ArticleApplied clinical informatics2023

Reducing Therapeutic Duplication in Inpatient Medication Orders.

Thomas E Dawson, Jonathan Beus, Evan W Orenstein, Uwem Umontuen, Denice McNeill, Swaminathan Kandaswamy

Abstract read
In one paragraph

Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline 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

6 authors.

Thomas E DawsonDepartment of Information Systems & Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.
Jonathan BeusDepartment of Information Systems & Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.
Evan W OrensteinDepartment of Information Systems & Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.
Uwem UmontuenDepartment of Information Systems & Technology, Children's Healthcare of Atlanta, Atlanta, Georgia, United States.
Denice McNeillDepartment of Clinical Development & Medical Affairs, PharmaEssentia USA Corporation, Burlington, Massachusetts, United States.
Swaminathan KandaswamyDepartment of pediatrics, Emory University, Atlanta, Georgia, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTherapeutic duplication, the presence of multiple agents prescribed for the same indication without clarification for when each should be used, can contribute to serious medical errors. Joint Commission standards require that orders contain clarifying information about when each order should be given. In our system, as needed (PRN) acetaminophen and ibuprofen orders are major contributors to therapeutic duplication.

objectiveThe objective of this study is to design and evaluate effectiveness of clinical decision support (CDS) to reduce therapeutic duplication with acetaminophen and ibuprofen orders.

methodsThis study was done in a pediatric health system with three freestanding hospitals. We iteratively designed and implemented two CDS strategies aimed at reducing the therapeutic duplication with these agents: (1) interruptive alert prompting clinicians for clarifying PRN comments at order entry and (2) addition of discrete "first-line" and "second-line" PRN reasons to orders. Therapeutic duplications were measured by manual review of orders for 30-day periods before and after each intervention and 6 months later.

resultsTherapeutic duplications decreased from 1,485 in the 30 days prior to the first alert implementation to 818 in the 30 days after but rose back to 1,208 in the 30 days prior to the second intervention. After discrete reasons were added to the order, therapeutic duplication decreased to 336 in the immediate 30 days and 6 months later remained at 277. Alerts firing rates decreased from 76.0 per 1,000 PRN acetaminophen or ibuprofen orders to 42.9 after the second intervention.

conclusionInterruptive alerts may reduce therapeutic duplication but are associated with high rates of user frustration and alert fatigue. Leveraging discrete PRN reasons for "first line" and "second line" produced a greater reduction in therapeutic duplication as well as fewer interruptive alerts and less manual entry for providers.

Indexed as

Decision Support Systems, ClinicalMedical Order Entry SystemsAcetaminophenChildHumansIbuprofenInpatientsMedication ErrorsAcetaminophenIbuprofen

Identifiers

PMID37105228
PMCPMC10356184

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.