Evidence mapPaperPMID 35477148Full record

ArticleApplied clinical informatics2022

Clinician Acceptance of Order Sets for Pain Management: A Survey in Two Urban Hospitals.

Yifan Liu, Haijing Hao, Mohit M Sharma, Yonaka Harris, Jean Scofi, Richard Trepp, Brenna Farmer, Jessica S Ancker, Yiye Zhang

Abstract read
In one paragraph

Article in Applied clinical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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  5. Article
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

9 authors.

Yifan LiuDepartment of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States.
Haijing HaoDepartment of Computer Information Systems, Bentley University, Waltham, Massachusetts, United States.
Mohit M SharmaDepartment of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States.
Yonaka HarrisDepartment of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States.
Jean ScofiDepartment of Emergency Medicine, Weill Cornell Medicine, New York, New York, United States.
Richard TreppDepartment of Emergency Medicine, Columbia University, New York, New York, United States.
Brenna FarmerDepartment of Emergency Medicine, Weill Cornell Medicine, New York, New York, United States.
Jessica S AnckerDepartment of Biomedical Informatics, Vanderbilt University Medical Center, New York, New York, United States.
Yiye ZhangDepartment of Population Health Sciences, Weill Cornell Medicine, New York, New York, United States.

Funding

AHRQ HHS R03 HS026266NLM NIH HHS K01 LM013257
6 · The paper itself

Abstract

backgroundOrder sets are a clinical decision support (CDS) tool in computerized provider order entry systems. Order set use has been associated with improved quality of care. Particularly related to opioids and pain management, order sets have been shown to standardize and reduce the prescription of opioids. However, clinician-level barriers often limit the uptake of this CDS modality.

objectiveTo identify the barriers to order sets adoption, we surveyed clinicians on their training, knowledge, and perceptions related to order sets for pain management.

methodsWe distributed a cross-sectional survey between October 2020 and April 2021 to clinicians eligible to place orders at two campuses of a major academic medical center. Survey questions were adapted from the widely used framework of Unified Theory of Acceptance and Use of Technology. We hypothesize that performance expectancy (PE) and facilitating conditions (FC) are associated with order set use. Survey responses were analyzed using logistic regression.

resultsThe intention to use order sets for pain management was associated with PE to existing order sets, social influence (SI) by leadership and peers, and FC for electronic health record (EHR) training and function integration. Intention to use did not significantly differ by gender or clinician role. Moderate differences were observed in the perception of the effort of, and FC for, order set use across gender and roles of clinicians, particularly emergency medicine and internal medicine departments.

conclusionThis study attempts to identify barriers to the adoption of order sets for pain management and suggests future directions in designing and implementing CDS systems that can improve order sets adoption by clinicians. Study findings imply the importance of order set effectiveness, peer influence, and EHR integration in determining the acceptability of the order sets.

Indexed as

Analgesics, OpioidMedical Order Entry SystemsCross-Sectional StudiesHospitals, UrbanHumansPainAnalgesics, Opioid

Identifiers

PMID35477148
PMCPMC9045963

What Socratic holds

Textmetadata
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 Socratic graph.