Evidence map›Paper›PMID 21486876›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2011

Development and validation of a survey instrument for assessing prescribers' perception of computerized drug-drug interaction alerts.

Kai Zheng, Kathleen Fear, Bruce W Chaffee, Christopher R Zimmerman, Edward M Karls, Justin D Gatwood, James G Stevenson, Mark D Pearlman

Abstract readValidation Study
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Alert dwell time: introduction of a measure to evaluate interruptive clinical decision support alerts.Journal of the American Medical Informatics Association : JAMIA · 2016
    Article
  8. Article
  9. Article
  10. Clinical research informatics: a conceptual perspective.Journal of the American Medical Informatics Association : JAMIA · 2012
    Article
  11. 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

8 authors.

Kai ZhengDepartment of Health Management and Policy, School of Public Health, The University of Michigan, Ann Arbor, Michigan 48109-2029, USA. kzheng@umich.edu
Kathleen Fear
Bruce W Chaffee
Christopher R Zimmerman
Edward M Karls
Justin D Gatwood
James G Stevenson
Mark D Pearlman

Funding

MICHIGAN INSTITUTE FOR CLINICAL AND HEALTH RESEARCH (MICHR) (UL1): (BPCA)UL1RR024986 · NCRR · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHANLEY, THOMAS P. · 2007 to 2011
$51.2M
NCRR NIH HHS UL1 RR024986NCRR NIH HHS UL1RR024986
6 · The paper itself

Abstract

objectiveTo develop a theoretically informed and empirically validated survey instrument for assessing prescribers' perception of computerized drug-drug interaction (DDI) alerts. MATERIALS AND

methodsThe survey is grounded in the unified theory of acceptance and use of technology and an adapted accident causation model. Development of the instrument was also informed by a review of the extant literature on prescribers' attitude toward computerized medication safety alerts and common prescriber-provided reasons for overriding. To refine and validate the survey, we conducted a two-stage empirical validation study consisting of a pretest with a panel of domain experts followed by a field test among all eligible prescribers at our institution.

resultsThe resulting survey instrument contains 28 questionnaire items assessing six theoretical dimensions: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived fatigue, and perceived use behavior. Satisfactory results were obtained from the field validation; however, a few potential issues were also identified. We analyzed these issues accordingly and the results led to the final survey instrument as well as usage recommendations. DISCUSSION: High override rates of computerized medication safety alerts have been a prevalent problem. They are usually caused by, or manifested in, issues of poor end user acceptance. However, standardized research tools for assessing and understanding end users' perception are currently lacking, which inhibits knowledge accumulation and consequently forgoes improvement opportunities. The survey instrument presented in this paper may help fill this methodological gap.

conclusionWe developed and empirically validated a survey instrument that may be useful for future research on DDI alerts and other types of computerized medication safety alerts more generally.

Indexed as

Attitude of Health PersonnelDrug InteractionsMedical Order Entry SystemsReminder SystemsSurveys and QuestionnairesAttitude to ComputersData CollectionDrug Therapy, Computer-AssistedHumans

Identifiers

PMID21486876
PMCPMC3241157

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.