ArticleInteractive journal of medical research2013
Evaluation of user interface and workflow design of a bedside nursing clinical decision support system.
Article in Interactive journal of medical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimizing Clinical Decision Support System Functionality by Leveraging Specific Human-Computer Interaction Elements: Insights From a Systematic Review.JMIR human factors · 2025Pooled it
- Developing an AI-Assisted Tool That Identifies Patients With Multimorbidity and Complex Polypharmacy to Improve the Process of Medication Reviews: Qualitative Interview and Focus Group Study.Journal of medical Internet research · 2026Article
- Analytical validation of Exandra: a clinical decision support system for promoting guideline-directed therapy of type-2 diabetes in primary care - a collaborative study with experts from Diabetes Canada.BMC medical informatics and decision making · 2025Article
- The Cooperation Between Nurses and a New Digital Colleague "AI-Driven Lifestyle Monitoring" in Long-Term Care for Older Adults: Viewpoint.JMIR nursing · 2024Article
- Methods used to evaluate usability of mobile clinical decision support systems for healthcare emergencies: a systematic review and qualitative synthesis.JAMIA open · 2023Review
- Handheld Computer Devices to Support Clinical Decision-making in Acute Nursing Practice: Systematic Scoping Review.Journal of medical Internet research · 2023Article
- A comparative evaluation of three point-of-care tools by registered nurses.Journal of the Medical Library Association : JMLA · 2022Article
- Assessing the Usability of a Clinical Decision Support System: Heuristic Evaluation.JMIR human factors · 2022Article
- Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis.JMIR medical informatics · 2020Article
- Evaluating a handheld decision support device in pediatric intensive care settings.JAMIA open · 2019Article
- Informatics Solutions for Application of Decision-Making Skills.Critical care nursing clinics of North America · 2018Review
- A Breastfeed-Promoting Mobile App Intervention: Usability and Usefulness Study.JMIR mHealth and uHealth · 2018Article
- Orders on file but no labs drawn: investigation of machine and human errors caused by an interface idiosyncrasy.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Integrative review of clinical decision support for registered nurses in acute care settings.Journal of the American Medical Informatics Association : JAMIA · 2017Review
- Assessment of the usability of a digital learning technology prototype for monitoring intracranial pressure.Revista latino-americana de enfermagem · 2016Article
- Dynamic software design for clinical exome and genome analyses: insights from bioinformaticians, clinical geneticists, and genetic counselors.Journal of the American Medical Informatics Association : JAMIA · 2016Article
- Usability Testing of a Complex Clinical Decision Support Tool in the Emergency Department: Lessons Learned.JMIR human factors · 2015Article
- Successful electronic implementation of discharge referral decision support has a positive impact on 30- and 60-day readmissions.Research in nursing & health · 2015Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinical decision support systems (CDSS) are important tools to improve health care outcomes and reduce preventable medical adverse events. However, the effectiveness and success of CDSS depend on their implementation context and usability in complex health care settings. As a result, usability design and validation, especially in real world clinical settings, are crucial aspects of successful CDSS implementations.
objectiveOur objective was to develop a novel CDSS to help frontline nurses better manage critical symptom changes in hospitalized patients, hence reducing preventable failure to rescue cases. A robust user interface and implementation strategy that fit into existing workflows was key for the success of the CDSS.
methodsGuided by a formal usability evaluation framework, UFuRT (user, function, representation, and task analysis), we developed a high-level specification of the product that captures key usability requirements and is flexible to implement. We interviewed users of the proposed CDSS to identify requirements, listed functions, and operations the system must perform. We then designed visual and workflow representations of the product to perform the operations. The user interface and workflow design were evaluated via heuristic and end user performance evaluation. The heuristic evaluation was done after the first prototype, and its results were incorporated into the product before the end user evaluation was conducted. First, we recruited 4 evaluators with strong domain expertise to study the initial prototype. Heuristic violations were coded and rated for severity. Second, after development of the system, we assembled a panel of nurses, consisting of 3 licensed vocational nurses and 7 registered nurses, to evaluate the user interface and workflow via simulated use cases. We recorded whether each session was successfully completed and its completion time. Each nurse was asked to use the National Aeronautics and Space Administration (NASA) Task Load Index to self-evaluate the amount of cognitive and physical burden associated with using the device.
resultsA total of 83 heuristic violations were identified in the studies. The distribution of the heuristic violations and their average severity are reported. The nurse evaluators successfully completed all 30 sessions of the performance evaluations. All nurses were able to use the device after a single training session. On average, the nurses took 111 seconds (SD 30 seconds) to complete the simulated task. The NASA Task Load Index results indicated that the work overhead on the nurses was low. In fact, most of the burden measures were consistent with zero. The only potentially significant burden was temporal demand, which was consistent with the primary use case of the tool.
conclusionsThe evaluation has shown that our design was functional and met the requirements demanded by the nurses' tight schedules and heavy workloads. The user interface embedded in the tool provided compelling utility to the nurse with minimal distraction.
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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.