ArticleBMJ quality & safety2019
When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record.
Article in BMJ quality & safety, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- OrderRex clinical user testing: a randomized trial of recommender system decision support on simulated cases.Journal of the American Medical Informatics Association : JAMIA · 2020Trial
- Current Trends in Venous Thromboprophylaxis for Inpatient Care.Journal of personalized medicine · 2026Review
- Reducing Low-Value Delirium Care Using Behavioral Design in the Electronic Medical Record.Journal of Brown hospital medicine · 2026Article
- Right Idea, Wrong Time: Focusing on Alert Timing for Effective Decision Support.Applied clinical informatics · 2025Article
- Clinical Decision Support Aiming to Accelerate Triage and Time to Dextrose-Containing IV Fluids in the ED for Children with Severe Metabolic Conditions.Applied clinical informatics · 2025Article
- Strategies and Tools for Electronic Health Records and Physician Workflow Alignment: Protocol for a Scoping Review.JMIR research protocols · 2025Article
- Patterns and Perceptions of Standard Order Set Use Among Physicians Working Within a Multihospital System: Mixed Methods Study.JMIR formative research · 2024Article
- Realizing the Full Potential of Clinical Decision Support: Translating Usability Testing into Routine Practice in Health Care Operations.Applied clinical informatics · 2024Article
- Nudging towards Sleep-Friendly Health Care: A Multifaceted Approach on Reducing Unnecessary Overnight Interventions.Applied clinical informatics · 2024Article
- Article
- Trends and Components of Thyroid Status Evaluation in Commercially Insured Adults in the United States, 2006-2020.The Journal of clinical endocrinology and metabolism · 2024Article
- Graph-based clinical recommender: Predicting specialists procedure orders using graph representation learning.Journal of biomedical informatics · 2023Article
- Assessing Usability and Ambulatory Clinical Staff Satisfaction with Two Electronic Health Records.Applied clinical informatics · 2023Article
- The Effect of Implementation of Guideline Order Bundles Into a General Admission Order Set on Clinical Practice Guideline Adoption: Quasi-Experimental Study.JMIR medical informatics · 2023Article
- A Practical Approach to Optimize Computerized Provider Order Entry Systems and Reduce Clinician Burden: Pre-Post Evaluation of Vendor-Derived "Order Friction" Data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Objective risk assessment vs standard care for acute coronary syndromes-The Australian GRACE Risk tool Implementation Study (AGRIS): a process evaluation.BMC health services research · 2022Article
- Alert burden in pediatric hospitals: a cross-sectional analysis of six academic pediatric health systems using novel metrics.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- The influence of integrating clinical practice guideline order bundles into a general admission order set on guideline adoption.JAMIA open · 2021Article
- Effects of Electronic Health Record Implementation and Barriers to Adoption and Use: A Scoping Review and Qualitative Analysis of the Content.Life (Basel, Switzerland) · 2020Article
- Web Exclusive. Annals for Hospitalists Inpatient Notes - Realizing the Promises of Hospital Electronic Order Sets.Annals of internal medicine · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundOrder sets are widely used tools in the electronic health record (EHR) for improving healthcare quality. However, there is limited insight into how well they facilitate clinician workflow. We assessed four indicators based on order set usage patterns in the EHR that reflect potential misalignment between order set design and clinician workflow needs.
methodsWe used data from the EHR on all orders of medication, laboratory, imaging and blood product items at an academic hospital and an itemset mining approach to extract orders that frequently co-occurred with order set use. We identified the following four indicators: infrequent ordering of order set items, rapid retraction of medication orders from order sets, additional a la carte ordering of items not included in order sets and a la carte ordering of items despite being listed in the order set.
resultsThere was significant variability in workflow alignment across the 11 762 order set items used in the 77 421 inpatient encounters from 2014 to 2017. The median ordering rate was 4.1% (IQR 0.6%-18%) and median medication retraction rate was 4% (IQR 2%-10%). 143 (5%) medications were significantly less likely while 68 (3%) were significantly more likely to be retracted than if the same medication was ordered a la carte. 214 (39%) order sets were associated with least one additional item frequently ordered a la carte and 243 (45%) order sets contained at least one item that was instead more often ordered a la carte.
conclusionOrder sets often do not align with what clinicians need at the point of care. Quantitative insights from EHRs may inform how order sets can be optimised to facilitate clinician workflow.
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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.