Evidence map›Paper›PMID 27330074›Full record

ReviewJournal of the American Medical Informatics Association : JAMIA2017

Integrative review of clinical decision support for registered nurses in acute care settings.

Karen Dunn Lopez, Sheila M Gephart, Rebecca Raszewski, Vanessa Sousa, Lauren E Shehorn, Joanna Abraham

Abstract readReview
In one paragraph

Review in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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

  1. A Concept Analysis of Nurses' Clinical Decision Making: Implications for Korea.International journal of environmental research and public health · 2022
    Pooled it
  2. Trial
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  5. Article
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  13. Inpatient nurses' preferences and decisions with risk information visualization.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  14. Article
  15. Nursing Informatics' Contribution to One Health.Yearbook of medical informatics · 2023
    Article
  16. Article
  17. Article
  18. Article
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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.

Karen Dunn LopezDepartment of Health Systems Science, College of Nursing, University of Illinois at Chicago, IL, USA.
Sheila M GephartCommunity and Systems Health Science, College of Nursing, University of Arizona, Tucson, USA.
Rebecca RaszewskiInformation Services, Library of Health Sciences, University of Illinois at Chicago, IL, USA.
Vanessa SousaDepartment of Health Systems Science, College of Nursing, University of Illinois at Chicago, IL, USA.
Lauren E ShehornCommunity and Systems Health Science, College of Nursing, University of Arizona, Tucson, USA.
Joanna AbrahamBiomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, IL, USA.

Funding

Clinical decision support optimizing NEC prevention implementation in NICUK08HS022908 · AHRQ · UNIVERSITY OF ARIZONA · PI GEPHART, SHEILA MARIA · 2014 to 2018
$696k
AHRQ HHS K08 HS022908
6 · The paper itself

Abstract

Objective: To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses. Materials and Methods: We performed an integrative review of qualitative and quantitative peer-reviewed original research studies using a structured search of PubMed, Embase, Cumulative Index to Nursing and Applied Health Literature (CINAHL), Scopus, Web of Science, and IEEE Xplore (Institute of Electrical and Electronics Engineers Xplore Digital Library). We included articles that reported on CDS targeting bedside nurses and excluded in stages based on rules for titles, abstracts, and full articles. We extracted research design and methods, CDS purpose, electronic health record integration, usability, and process and patient outcomes. Results: Our search yielded 3157 articles. After removing duplicates and applying exclusion rules, 28 articles met the inclusion criteria. The majority of studies were single-site, descriptive or qualitative (43%) or quasi-experimental (36%). There was only 1 randomized controlled trial. The purpose of most CDS was to support diagnostic decision-making (36%), guideline adherence (32%), medication management (29%), and situational awareness (25%). All the studies that included process outcomes (7) and usability outcomes (4) and also had analytic procedures to detect changes in outcomes demonstrated statistically significant improvements. Three of 4 studies that included patient outcomes and also had analytic procedures to detect change showed statistically significant improvements. No negative effects of CDS were found on process, usability, or patient outcomes. Discussion and Conclusions: Clinical support systems targeting bedside nurses have positive effects on outcomes and hold promise for improving care quality; however, this research is lagging behind studies of CDS targeting medical decision-making in both volume and level of evidence.

Indexed as

Decision Support Systems, ClinicalNursesNursing InformaticsPoint-of-Care SystemsDiagnosis, Computer-AssistedHospitalsHumansInformation Storage and Retrievalcomputerized clinical decision supportdecision-makingnursing informaticsregistered nursereview

Identifiers

PMID27330074
PMCPMC7651925

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.