{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T23:06:25Z","timestamp":1779491185292,"version":"3.53.1"},"reference-count":24,"publisher":"Georg Thieme Verlag KG","issue":"02","funder":[{"name":"Major Science and Technology Project of the Changzhou Health Commission","award":["ZD202320"],"award-info":[{"award-number":["ZD202320"]}]},{"name":"Nursing Research Project of Nanjing Medical University Changzhou Medical Center","award":["CMC2023HL04"],"award-info":[{"award-number":["CMC2023HL04"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Intravenous medication administration is a high-risk clinical procedure, where medication errors can lead to adverse consequences. Evidence-based clinical practice guidelines provide recommendations for the administration and monitoring of intravenous infusions. These guidelines are being increasingly integrated into clinical decision support systems (CDSS). The development of CDSS should emphasize nurses as core users, closely align with their clinical workflows, and ultimately create practical, user-friendly tools through thoughtful interface design, functional logic, and intelligent alert mechanisms.<\/jats:p>\n                  <jats:p>We aimed to design and develop a clinical decision support tool based on the Data-Information-Knowledge-Wisdom model, which minimizes infusion errors by providing real-time alerts and standardizing workflows.<\/jats:p>\n                  <jats:p>A nonrandomized trial (May\u2013July 2024) in a tertiary hospital compared traditional practices (n\u2009=\u20091,204) with a CDSS (n\u2009=\u20091,207) using 300 clinical rules and a personal digital assistant interface. Outcomes included error rates, severity, nurse satisfaction, and efficiency.<\/jats:p>\n                  <jats:p>The CDSS reduced errors by 56.8% (16.69\u20137.21%, p\u2009&lt;\u20090.001), eliminated severe errors (Level 3\u20134), improved nurse satisfaction (mean: 69.1\/85 on a 17\u201385 scale), and reduced prescription processing time by 41%.<\/jats:p>\n                  <jats:p>This nurse-led CDSS enhances infusion safety and efficiency, offering a scalable solution. Artificial intelligence-driven predictive error detection could further optimize outcomes.<\/jats:p>","DOI":"10.1055\/a-2867-0618","type":"journal-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T22:43:26Z","timestamp":1778107406000},"page":"347-356","source":"Crossref","is-referenced-by-count":0,"title":["Development and Application of a Nurse-Led Clinical Decision Support System for Safe Intravenous Medication Administration: A Nonrandomized Controlled Trial"],"prefix":"10.1055","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9081-7255","authenticated-orcid":false,"given":"Fuling","family":"Zhang","sequence":"additional","affiliation":[{"name":"Nursing Department, Changzhou Second People\u2019s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu Province, China"},{"name":"School of Nursing, Nanjing Medical University, Nanjing, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjuan","family":"Yun","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Changzhou Second People\u2019s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7358-4017","authenticated-orcid":false,"given":"Lili","family":"Qin","sequence":"additional","affiliation":[{"name":"Nursing Department, Changzhou Second People\u2019s Hospital, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu Province, China"},{"name":"School of Nursing, Nanjing Medical University, Nanjing, Jiangsu, 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