Evidence map›Paper›PMID 32027357›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2020

Measuring implementation feasibility of clinical decision support alerts for clinical practice recommendations.

Rachel L Richesson, Catherine J Staes, Brian J Douthit, Traci Thoureen, Daniel J Hatch, Kensaku Kawamoto, Guilherme Del Fiol

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Establishing Quality Indicators and Implementation Priorities for Post-Stroke Aphasia Services Through End-User Involvement.Health expectations : an international journal of public participation in health care and health policy · 2024
    Article
  3. Data Challenges in Identifying Patients Due for Colorectal Cancer Screening in Rural Clinics.Journal of the American Board of Family Medicine : JABFM · 2023
    Article
  4. Article
  5. Article
  6. Comparison of electronic versus manual abstraction for 2 standardized perinatal care measures.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Hot topics in clinical informatics.Journal of the American Medical Informatics Association : JAMIA · 2020
    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

7 authors.

Rachel L RichessonDuke University School of Nursing, Durham, North Carolina.
Catherine J StaesUniversity of Utah College of Nursing, Salt Lake City, Utah.
Brian J DouthitDuke University School of Nursing, Durham, North Carolina.
Traci ThoureenDivision of Emergency Medicine, Duke University Medical Center, Durham, North Carolina.
Daniel J HatchDuke University School of Nursing, Durham, North Carolina.
Kensaku KawamotoDepartment of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, Utah.
Guilherme Del FiolDepartment of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, Utah.

Funding

Quantifying System and Data Readiness for Automated Clinical Decision SupportR15LM012335 · NLM · DUKE UNIVERSITY · PI RICHESSON, RACHEL L · 2016 to 2016
$408k
NLM NIH HHS R15 LM012335
6 · The paper itself

Abstract

objectiveThe study sought to describe key features of clinical concepts and data required to implement clinical practice recommendations as clinical decision support (CDS) tools in electronic health record systems and to identify recommendation features that predict feasibility of implementation. MATERIALS AND

methodsUsing semistructured interviews, CDS implementers and clinician subject matter experts from 7 academic medical centers rated the feasibility of implementing 10 American College of Emergency Physicians Choosing Wisely Recommendations as electronic health record-embedded CDS and estimated the need for additional data collection. Ratings were combined with objective features of the guidelines to develop a predictive model for technical implementation feasibility.

resultsA linear mixed model showed that the need for new data collection was predictive of lower implementation feasibility. The number of clinical concepts in each recommendation, need for historical data, and ambiguity of clinical concepts were not predictive of implementation feasibility.

conclusionsThe availability of data and need for additional data collection are essential to assess the feasibility of CDS implementation. Authors of practice recommendations and guidelines can enable organizations to more rapidly assess data availability and feasibility of implementation by including operational definitions for required data.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsPractice Guidelines as TopicAcademic Medical CentersEvidence-Based MedicineFeasibility StudiesHumansInterviews as TopicLinear ModelsTomography, X-Ray Computedclinical decision supportclinical guidelinesfeasibility assessmentimplementation

Identifiers

PMID32027357
PMCPMC7075536

What OpenQuestion 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 OpenQuestion graph.