Literature DB >> 18579840

Evaluating clinical decision support systems: monitoring CPOE order check override rates in the Department of Veterans Affairs' Computerized Patient Record System.

Ching-Ping Lin1, Thomas H Payne, W Paul Nichol, Patricia J Hoey, Curtis L Anderson, John H Gennari.   

Abstract

OBJECTIVE: To measure critical order check override rates in VA Puget Sound Health Care System's computerized practitioner order entry (CPOE) system and to compare 2006 results to a similar 2001 study.
DESIGN: Analysis of ordering and order check data gathered by a post-hoc logging program. Use of Pearson's chi-square contingency table test comparing results from this study and the earlier study. MEASUREMENTS: Factors measured were total number of orders, frequency of order check types, frequency of order check overrides by order check type and comparisons of these results with previous results.
RESULTS: A total of 37,040 orders generated 908 (2.5%) critical order checks. Drug-drug critical alert override rate was 74/85 (87%) in 2006 compared to 95/108 (88%) in 2001 (X ( 2 )=0.04, df=1, p=0.85). The drug-allergy override rate was 341/420 (81%) compared to 72/105 (69%) in 2001 (X ( 2 )=7.97, df=1, p=0.005). In 2001, 0.25% (105/42,621) orders generated a drug-allergy order check compared to 1.13% (420/37,040) in 2006 (X ( 2 )=238.45, df=1, p<0.0001).
CONCLUSION: Override rates of critical drug-drug and drug-allergy order checks remain high at VA Puget Sound Health Care System including significant increases in drug-allergy order checks. We recommend that monitoring override rates be regular practice in clinical computing systems and conclude that qualitative research should be carried out to better understand how physicians interact with decision support at the point of ordering.

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Mesh:

Year:  2008        PMID: 18579840      PMCID: PMC2528033          DOI: 10.1197/jamia.M2453

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  14 in total

1.  The transition to automated practitioner order entry in a teaching hospital: the VA Puget Sound experience.

Authors:  T H Payne
Journal:  Proc AMIA Symp       Date:  1999

2.  Improving allergy alerting in a computerized physician order entry system.

Authors:  S A Abookire; J M Teich; H Sandige; M D Paterno; M T Martin; G J Kuperman; D W Bates
Journal:  Proc AMIA Symp       Date:  2000

3.  Characteristics and override rates of order checks in a practitioner order entry system.

Authors:  Thomas H Payne; W Paul Nichol; Patty Hoey; James Savarino
Journal:  Proc AMIA Symp       Date:  2002

4.  VistA--U.S. Department of Veterans Affairs national-scale HIS.

Authors:  Steven H Brown; Michael J Lincoln; Peter J Groen; Robert M Kolodner
Journal:  Int J Med Inform       Date:  2003-03       Impact factor: 4.046

5.  Clinical relevance of automated drug alerts from the perspective of medical providers.

Authors:  Jeffrey R Spina; Peter A Glassman; Pamela Belperio; Rumi Cader; Steven Asch
Journal:  Am J Med Qual       Date:  2005 Jan-Feb       Impact factor: 1.852

6.  Implementing a commercial rule base as a medication order safety net.

Authors:  Richard M Reichley; Terry L Seaton; Ervina Resetar; Scott T Micek; Karen L Scott; Victoria J Fraser; W Claiborne Dunagan; Thomas C Bailey
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

7.  Practitioners' views on computerized drug-drug interaction alerts in the VA system.

Authors:  Yu Ko; Jacob Abarca; Daniel C Malone; Donna C Dare; Doug Geraets; Antoun Houranieh; William N Jones; W Paul Nichol; Gregory P Schepers; Michelle Wilhardt
Journal:  J Am Med Inform Assoc       Date:  2006-10-26       Impact factor: 4.497

8.  Reducing the frequency of errors in medicine using information technology.

Authors:  D W Bates; M Cohen; L L Leape; J M Overhage; M M Shabot; T Sheridan
Journal:  J Am Med Inform Assoc       Date:  2001 Jul-Aug       Impact factor: 4.497

9.  Physicians' decisions to override computerized drug alerts in primary care.

Authors:  Saul N Weingart; Maria Toth; Daniel Z Sands; Mark D Aronson; Roger B Davis; Russell S Phillips
Journal:  Arch Intern Med       Date:  2003-11-24

10.  Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system.

Authors:  Tyken C Hsieh; Gilad J Kuperman; Tonushree Jaggi; Patricia Hojnowski-Diaz; Julie Fiskio; Deborah H Williams; David W Bates; Tejal K Gandhi
Journal:  J Am Med Inform Assoc       Date:  2004-08-06       Impact factor: 4.497

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  45 in total

1.  Integration of heterogeneous clinical decision support systems and their knowledge sets: feasibility study with Drug-Drug Interaction alerts.

Authors:  Hye Jin Kam; Jeong Ah Kim; InSook Cho; Yoon Kim; Rae Woong Park
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  Cognitive analysis of decision support for antibiotic prescribing at the point of ordering in a neonatal intensive care unit.

Authors:  Barbara Sheehan; David Kaufman; Peter Stetson; Leanne M Currie
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

3.  Computerized physician order entry: promise, perils, and experience.

Authors:  Raman Khanna; Tony Yen
Journal:  Neurohospitalist       Date:  2014-01

4.  Electronic alerts for triage protocol compliance among emergency department triage nurses: a randomized controlled trial.

Authors:  James F Holmes; Joshua Freilich; Sandra L Taylor; David Buettner
Journal:  Nurs Res       Date:  2015 May-Jun       Impact factor: 2.381

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

6.  Can an electronic prescribing system detect doctors who are more likely to make a serious prescribing error?

Authors:  Jamie J Coleman; Karla Hemming; Peter G Nightingale; Ian R Clark; Mary Dixon-Woods; Robin E Ferner; Richard J Lilford
Journal:  J R Soc Med       Date:  2011-05       Impact factor: 5.344

7.  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

8.  Adverse drug event detection in pediatric oncology and hematology patients: using medication triggers to identify patient harm in a specialized pediatric patient population.

Authors:  Rosemary J Call; Jonathan D Burlison; Jennifer J Robertson; Jeffrey R Scott; Donald K Baker; Michael G Rossi; Scott C Howard; James M Hoffman
Journal:  J Pediatr       Date:  2014-04-25       Impact factor: 4.406

9.  Report of the AMIA EHR-2020 Task Force on the status and future direction of EHRs.

Authors:  Thomas H Payne; Sarah Corley; Theresa A Cullen; Tejal K Gandhi; Linda Harrington; Gilad J Kuperman; John E Mattison; David P McCallie; Clement J McDonald; Paul C Tang; William M Tierney; Charlotte Weaver; Charlene R Weir; Michael H Zaroukian
Journal:  J Am Med Inform Assoc       Date:  2015-05-28       Impact factor: 4.497

10.  Evaluation of Harm Associated with High Dose-Range Clinical Decision Support Overrides in the Intensive Care Unit.

Authors:  Adrian Wong; Christine Rehr; Diane L Seger; Mary G Amato; Patrick E Beeler; Sarah P Slight; Adam Wright; David W Bates
Journal:  Drug Saf       Date:  2019-04       Impact factor: 5.606

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