Literature DB >> 16501396

Exposure to automated drug alerts over time: effects on clinicians' knowledge and perceptions.

Peter A Glassman1, Pamela Belperio, Barbara Simon, Andrew Lanto, Martin Lee.   

Abstract

OBJECTIVE: We tested whether interval exposure to an automated drug alert system that included approximately 2000 drug-drug interaction alerts increased recognition of selected interacting drug pairs. We also examined other perceptions about computerized order entry. RESEARCH
DESIGN: We administered cross-sectional surveys in 2000 and 2002 that included more than 260 eligible clinicians in each time period.
SUBJECTS: We studied clinicians practicing in ambulatory settings within a Southern California Veterans Affairs Healthcare System and who responded to both surveys (97 respondents). MEASURES: We sought to measure (1) recognition of selected drug-drug and drug-condition interactions and (2) other benefits and barriers to using automated drug alerts.
RESULTS: Clinicians correctly categorized similar percentages of the 7 interacting drug-drug pairs at baseline and follow-up (53% vs. 54%, P = 0.51) but improved their overall recognition of the 3 contraindicated drug-drug pairs (51% vs. 60%, P = 0.01). No significant changes from baseline to follow-up were found for the 8 interacting drug-condition pairs (60% vs. 62%, P = 0.43) or the 4 contraindicated drug-condition pairs (52% vs. 56%, P = 0.24). More providers preferred using order entry at follow-up than baseline (63% vs. 45%, P < 0.001). Signal-to-noise ratio remained the biggest reported problem at follow-up and baseline (54 vs. 57%, P = 0.75). In 2002, clinicians reported seeing a median of 5 drug alerts per week (representing approximately 12.5% of prescriptions entered), with a median 5% reportedly leading to an action.
CONCLUSIONS: Interval exposure to automated drug alerts had little to no effect on recognition of selected drug-drug interactions. The primary perceived barrier to effective utilization of drug alerts remained the same over time.

Mesh:

Year:  2006        PMID: 16501396     DOI: 10.1097/01.mlr.0000199849.08389.91

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  24 in total

1.  Randomized clinical trial of a customized electronic alert requiring an affirmative response compared to a control group receiving a commercial passive CPOE alert: NSAID--warfarin co-prescribing as a test case.

Authors:  Brian L Strom; Rita Schinnar; Warren Bilker; Sean Hennessy; Charles E Leonard; Eric Pifer
Journal:  J Am Med Inform Assoc       Date:  2010 Jul-Aug       Impact factor: 4.497

2.  A randomized-controlled trial of computerized alerts to reduce unapproved medication abbreviation use.

Authors:  Jennifer S Myers; Sattar Gojraty; Wei Yang; Amy Linsky; Subha Airan-Javia; Rosemary C Polomano
Journal:  J Am Med Inform Assoc       Date:  2010-12-03       Impact factor: 4.497

3.  Prescribers' responses to alerts during medication ordering in the long term care setting.

Authors:  James Judge; Terry S Field; Martin DeFlorio; Jane Laprino; Jill Auger; Paula Rochon; David W Bates; Jerry H Gurwitz
Journal:  J Am Med Inform Assoc       Date:  2006-04-18       Impact factor: 4.497

4.  A nurse-led intervention for identification of drug-related problems.

Authors:  Monica Bergqvist; Johanna Ulfvarson; Eva Andersen Karlsson; Christer von Bahr
Journal:  Eur J Clin Pharmacol       Date:  2008-01-19       Impact factor: 2.953

5.  A human factors investigation of medication alerts: barriers to prescriber decision-making and clinical workflow.

Authors:  Alissa L Russ; Alan J Zillich; M Sue McManus; Bradley N Doebbeling; Jason J Saleem
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

Review 6.  Computerized clinical decision support for prescribing: provision does not guarantee uptake.

Authors:  Annette Moxey; Jane Robertson; David Newby; Isla Hains; Margaret Williamson; Sallie-Anne Pearson
Journal:  J Am Med Inform Assoc       Date:  2010 Jan-Feb       Impact factor: 4.497

7.  Pharmacy students' ability to identify potential drug-drug interactions.

Authors:  Kim R Saverno; Daniel C Malone; John Kurowsky
Journal:  Am J Pharm Educ       Date:  2009-04-07       Impact factor: 2.047

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

Authors:  Kai Zheng; Kathleen Fear; Bruce W Chaffee; Christopher R Zimmerman; Edward M Karls; Justin D Gatwood; James G Stevenson; Mark D Pearlman
Journal:  J Am Med Inform Assoc       Date:  2011-04-12       Impact factor: 4.497

9.  Decision Support Alerts for Medication Ordering in a Computerized Provider Order Entry (CPOE) System: A systematic approach to decrease alerts.

Authors:  M A Del Beccaro; R Villanueva; K M Knudson; E M Harvey; J M Langle; W Paul
Journal:  Appl Clin Inform       Date:  2010-09-29       Impact factor: 2.342

10.  Perceptions of standards-based electronic prescribing systems as implemented in outpatient primary care: a physician survey.

Authors:  C Jason Wang; Mihir H Patel; Anthony J Schueth; Melissa Bradley; Shinyi Wu; Jesse C Crosson; Peter A Glassman; Douglas S Bell
Journal:  J Am Med Inform Assoc       Date:  2009-04-23       Impact factor: 4.497

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