ArticleJournal of the American Medical Informatics Association : JAMIA
Types of unintended consequences related to computerized provider order entry.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01262053 (Investigating Wrong-Patient CPOE Errors), which is not on this map. Cited by 276 papers, 8 of them syntheses that pooled it.
What it found
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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.
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.
Investigating Wrong-Patient CPOE Errors
Who cites it
276 citing papers in PubMed, 8 syntheses or guidelines pooled it.
- Effect of electronic drug-drug interaction alerts on patient and clinician outcomes: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- How does medical scribes' work inform development of speech-based clinical documentation technologies? A systematic review.Journal of the American Medical Informatics Association : JAMIA · 2020Pooled it
- Systematic review of interventions to improve safety and quality of anticoagulant prescribing for therapeutic indications for hospital inpatients.European journal of clinical pharmacology · 2019Pooled it
- Problems with health information technology and their effects on care delivery and patient outcomes: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Usability Flaws in Medication Alerting Systems: Impact on Usage and Work System.Yearbook of medical informatics · 2015Pooled it
- The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis.Systematic reviews · 2014Pooled it
- Risks to patient safety associated with implementation of electronic applications for medication management in ambulatory care--a systematic review.BMC medical informatics and decision making · 2013Pooled it
- Does user-centred design affect the efficiency, usability and safety of CPOE order sets?Journal of the American Medical Informatics Association : JAMIA · 2011Trial
- A framework for developing, validating, and utilizing automated measures of order errors using the retract-and-reorder methodology.JAMIA open · 2026Article
- Factors contributing to electronic prescribing errors in healthcare settings: a qualitative study.BMC medical informatics and decision making · 2026Article
- Optimizing clinical documentation in virtual hospitals: a task-technology fit perspective.JAMIA open · 2026Article
- Article
- Evaluation of Health Professions Trainee Experiences Transitioning to New VHA Electronic Health Record.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2026Article
- Nested order panels for adult primary care modestly improves ordering efficiency among high utilizers.JAMIA open · 2026Article
- Article
- Development and application of desiderata for automated clinical ordering.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Electronic Health Record Burnout in Surgery and Strategies to Improve Burnout: A Narrative Review.Cureus · 2025Review
- Using human centred design and human factors to support a rapid health information technology patient safety response.BMC health services research · 2025Article
- Understanding Antecedents of Nurses' and Physicians' Workaround Behavior Regarding Hospital Information Systems: Qualitative Interview Study.Journal of medical Internet research · 2025Article
216 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveTo identify types of clinical unintended adverse consequences resulting from computerized provider order entry (CPOE) implementation.
designAn expert panel provided initial examples of adverse unintended consequences of CPOE. The authors, using qualitative methods, gathered and analyzed additional examples from five successful CPOE sites.
methodsUsing a card sort method, the authors developed a categorization scheme for the 79 unintended consequences initially identified and then iteratively modified the scheme to categorize 245 additional adverse consequences resulting from fieldwork. Because the focus centered on consequences requiring prevention or remedial action, the authors did not further analyze reported unintended beneficial (positive) consequences.
resultsUnintended adverse consequences (UACs) fell into nine major categories (in order of decreasing frequency): 1) more/new work for clinicians; 2) unfavorable workflow issues; 3) never ending system demands; 4) problems related to paper persistence; 5) untoward changes in communication patterns and practices; 6) negative emotions; 7) generation of new kinds of errors; 8) unexpected changes in the power structure; and 9) overdependence on the technology. Clinical decision support features introduced many of these unintended consequences.
conclusionIdentifying and understanding the types and in some instances the causes of unintended adverse consequences associated with CPOE will enable system developers and implementers to better manage implementation and maintenance of future CPOE projects.
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What OpenQuestion holds
Registered trials
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.