Evidence map›Paper›PMID 27348488›Full record

ArticleJournal of innovation in health informatics2016

Using the diffusion of innovations theory to assess socio-technical factors in planning the implementation of an electronic health record alert across multiple primary care clinics.

Ching-Pin Lin, Janelle Guirguis-Blake, Gina A Keppel, Sharon Dobie, Justin Osborn, Allison M Cole, Laura-Mae Baldwin

Open access · goldAbstract read
In one paragraph

Article in Journal of innovation in health informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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 at 3 institutions in 1 country.

Ching-Pin LinInstitute of Translational Health Sciences, University of Washington, Seattle, Washington, USA. ping@uw.edu.
Janelle Guirguis-BlakeInstitute of Translational Health Sciences, University of Washington, Seattle, Washington, USA. janelle.guirguis-blake@multicare.org.
Gina A KeppelDepartment of Family Medicine, University of Washington, Seattle, Washington, USA. gakeppel@uw.edu.
Sharon DobieDepartment of Family Medicine, University of Washington, Seattle, Washington, USA. dob@uw.edu.
Justin OsbornDepartment of Family Medicine, University of Washington, Seattle, Washington, USA. josborn@uw.edu.
Allison M ColeDepartment of Family Medicine, University of Washington, Seattle, Washington, USA. acole2@uw.edu.
Laura-Mae BaldwinDepartment of Family Medicine, University of Washington, Seattle, Washington, USA. lmb@uw.edu.
Seattle University · USInstitute of Translational Health Sciences · USUniversity of Washington · US

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
Institute of Translational Health SciencesUL1TR000423 · NCATS · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2012 to 2016
$49.4M
NCATS NIH HHS UL1 TR000423NCATS NIH HHS UL1 TR002319
6 · The paper itself

Abstract

backgroundAdverse drug events (ADEs) are a leading cause of death in the United States. Patients with stage 3 and 4 chronic kidney disease (CKD) are at particular risk because many medications are cleared by the kidneys. Alerts in the electronic health record (EHR) about drug appropriateness and dosing at the time of prescription have been shown to reduce ADEs for patients with stage 3 and 4 CKD in inpatient settings, but more research is needed about the implementation and effectiveness of such alerts in outpatient settings.

objectiveTo explore factors that might inform the implementation of an electronic drug-disease alert for patients with CKD in primary care clinics, using Rogers' diffusion of innovations theory as an analytic framework.

methodsInterviews were conducted with key informants in four diverse clinics using various EHR systems. Interviews were audio recorded and transcribed. results Although all clinics had a current method for calculating glomerular filtration rate (GFR), clinics were heterogeneous with regard to current electronic decision support practices, quality improvement resources, and organizational culture and structure.

conclusionUnderstanding variation in organizational culture and infrastructure across primary care clinics is important in planning implementation of an intervention to reduce ADEs among patients with CKD.

Indexed as

Diffusion of InnovationElectronic Health RecordsPrimary Health CareAmbulatory Care FacilitiesDrug-Related Side Effects and Adverse ReactionsHumansadverse drug eventchronic kidney diseaseselectronic health recordsmedication alert systemsoutpatient clinicprimary care

Identifiers

PMID27348488
PMCPMC5072363
OpenAlexW2340241475

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.