Evidence map›Paper›PMID 29866642›Full record

ReviewJMIR medical informatics2018

Health Information Technology in Healthcare Quality and Patient Safety: Literature Review.

Sue S Feldman, Scott Buchalter, Leslie W Hayes

Erratum issuedAbstract readReview
In one paragraph

Review in JMIR medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Prediction of prolonged length of stay from first 2 days of hospitalization data: a SHAP value-based variable selection method for a simplified model.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2025
    Article
  5. Review
  6. AHRQ's digital healthcare research program: 20 years of advancing innovation and discovery.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  7. Article
  8. Article
  9. Using automated methods to detect safety problems with health information technology: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  10. Observational
  11. Article
  12. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing.Annual review of genomics and human genetics · 2022
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Sue S Feldman *Department of Health Services Adminstration, The University of Alabama at Birmingham, Birmingham, AL, United States.ORCID http://orcid.org/0000-0002-1173-3993
Scott Buchalter *Pulmonary and Critical Care, The University of Alabama at Birmingham Medical Center, Birmingham, AL, United States.ORCID http://orcid.org/0000-0003-1455-8374
Leslie W Hayes *Department of Pediatrics, The University of Alabama at Birmingham Medical Center, Birmingham, AL, United States.ORCID http://orcid.org/0000-0002-7400-9054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe area of healthcare quality and patient safety is starting to use health information technology to prevent reportable events, identify them before they become issues, and act on events that are thought to be unavoidable. As healthcare organizations begin to explore the use of health information technology in this realm, it is often unclear where fiscal and human efforts should be focused.

objectiveThe purpose of this study was to provide a foundation for understanding where to focus health information technology fiscal and human resources as well as expectations for the use of health information technology in healthcare quality and patient safety.

methodsA literature review was conducted to identify peer-reviewed publications reporting on the actual use of health information technology in healthcare quality and patient safety. Inductive thematic analysis with open coding was used to categorize a total of 41 studies. Three pre-set categories were used: prevention, identification, and action. Three additional categories were formed through coding: challenges, outcomes, and location.

resultsThis study identifies five main categories across seven study settings. A majority of the studies used health IT for identification and prevention of healthcare quality and patient safety issues. In this realm, alerts, clinical decision support, and customized health IT solutions were most often implemented. Implementation, interface design, and culture were most often noted as challenges.

conclusionsThis study provides valuable information as organizations determine where they stand to get the most "bang for their buck" relative to health IT for quality and patient safety. Knowing what implementations are being effectivity used by other organizations helps with fiscal and human resource planning as well as managing expectations relative to cost, scope, and outcomes. The findings from this scan of the literature suggest that having organizational champion leaders that can shepherd implementation, impact culture, and bridge knowledge with developers would be a valuable resource allocation to consider.

Indexed as

Healthcare QualityHealth Information TechnologyPatient Safety

Identifiers

PMID29866642
PMCPMC6006013

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.