ArticleBMC medical informatics and decision making2020
Development and initial implementation of electronic clinical decision supports for recognition and management of hospital-acquired acute kidney injury.
Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed.
- Development and Validation of an Automated Acute Kidney Injury E-Alert System Integrated with Clinical Decision Support for Hospitalized Patients.Journal of medical systems · 2026Article
- Hospital Digital Transformation, Nursing Data Burden, and Leadership and Governance Capacity: A Critical Narrative Review.Journal of nursing management · 2026Review
- User experience study to evaluate a clinical decision support system prototype supporting continuous kidney replacement therapy in a simulated ICU environment.BMC medical informatics and decision making · 2025Article
- Perspectives on AI-Driven Nursing Science Among Nursing Professionals from China: A Qualitative Study.Nursing reports (Pavia, Italy) · 2025Article
- Implementation and delivery of electronic health records training programs for nurses working in inpatient settings: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Stepped-Wedge Trial of Decision Support for Acute Kidney Injury on Surgical Units.Kidney international reports · 2024Article
- Clinical Decision Support Tools in the Electronic Medical Record.Kidney international reports · 2024Review
- Information displays for automated surveillance algorithms of in-hospital patient deterioration: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Does acute kidney injury alerting improve patient outcomes?BMC nephrology · 2023Article
- Completion of postoperative polysomnography for children with severe obstructive sleep apnea: A quality improvement project.Laryngoscope investigative otolaryngology · 2022Article
- Real-world Health Data and Precision for the Diagnosis of Acute Kidney Injury, Acute-on-Chronic Kidney Disease, and Chronic Kidney Disease: Observational Study.JMIR medical informatics · 2022Article
- Management of Patients With Kidney Disease in Need of Cardiovascular Catheterization: A Scientific Workshop Cosponsored by the National Kidney Foundation and the Society for Cardiovascular Angiography and Interventions.Journal of the Society for Cardiovascular Angiography & InterventionsReview
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundAcute kidney injury (AKI) is common in hospitalized patients and is associated with poor patient outcomes and high costs of care. The implementation of clinical decision support tools within electronic medical record (EMR) could improve AKI care and outcomes. While clinical decision support tools have the potential to enhance recognition and management of AKI, there is limited description in the literature of how these tools were developed and whether they meet end-user expectations.
methodsWe developed and evaluated the content, acceptability, and usability of electronic clinical decision support tools for AKI care. Multi-component tools were developed within a hospital EMR (Sunrise Clinical Manager™, Allscripts Healthcare Solutions Inc.) currently deployed in Calgary, Alberta, and included: AKI stage alerts, AKI adverse medication warnings, AKI clinical summary dashboard, and an AKI order set. The clinical decision support was developed for use by multiple healthcare providers at the time and point of care on general medical and surgical units. Functional and usability testing for the alerts and clinical summary dashboard was conducted via in-person evaluation sessions, interviews, and surveys of care providers. Formal user acceptance testing with clinical end-users, including physicians and nursing staff, was conducted to evaluate the AKI order set.
resultsConsiderations for appropriate deployment of both non-disruptive and interruptive functions was important to gain acceptability by clinicians. Functional testing and usability surveys for the alerts and clinical summary dashboard indicated that the tools were operating as desired and 74% (17/23) of surveyed healthcare providers reported that these tools were easy to use and could be learned quickly. Over three-quarters of providers (18/23) reported that they would utilize the tools in their practice. Three-quarters of the participants (13/17) in user acceptance testing agreed that recommendations within the order set were useful. Overall, 88% (15/17) believed that the order set would improve the care and management of AKI patients.
conclusionsDevelopment and testing of EMR-based decision support tools for AKI with clinicians led to high acceptance by clinical end-users. Subsequent implementation within clinical environments will require end-user education and engagement in system-level initiatives to use the tools to improve care.
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