{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T21:08:13Z","timestamp":1788901693193,"version":"build-2803163510"},"reference-count":29,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Clinical decision support systems (CDSSs) are widely implemented in hospitals, yet their uptake in nursing practice remains inconsistent. While electronic health records continuously capture nursing decision data, these data are rarely used to support structured quality improvement. Decision mining offers a novel approach by reconstructing and visualizing decision logic from clinical decision logs to support retrospective reflection and protocol evaluation rather than real-time alerting. Before such tools can be integrated into quality improvement programs, their acceptance by clinical users must be empirically examined.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to conduct an early-stage, user-centered evaluation of a clinical decision mining tool for nursing quality improvement and to examine how nurses evaluate the factors influencing their intention to use the tool, using the unified theory of acceptance and use of technology (UTAUT) as a conceptual organizing framework.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n An exploratory qualitative design was used, using a theory-guided expert discussion as the primary method. A purposive sample of 5 quality improvement nurses from a large Dutch hospital participated in a 90-minute session comprising a structured prototype demonstration, a 12-item UTAUT-derived questionnaire administered as a facilitation instrument, and an expert discussion. Questionnaire scores were summarized descriptively by construct to anchor and organize the expert group discussion. Expert discussion data were analyzed using directed content analysis, with UTAUT constructs\u2014performance expectancy, effort expectancy, attitude toward use, social influence, and behavioral intention\u2014as sensitizing categories. Attitude toward use was included following UTAUT extensions validated in nursing informatics contexts.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Performance expectancy scores were consistently high, driven by perceived value for protocol evaluation and data-supported quality improvement discussions. Effort expectancy was moderate and variable, reflecting concerns about data interpretation and limited data literacy rather than interface usability. Attitude toward use showed the lowest construct-level scores and the widest variation, contingent on whether the tool was framed as learning-oriented rather than a monitoring or control mechanism. Behavioral intention was relatively high for targeted use, but participants positioned adoption in structured quality improvement meetings rather than daily in bedside practice, reflecting role differentiation rather than rejection. Social influence did not emerge as a substantive theme at this preimplementation stage.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Nurses perceived strong value in the CDM tool\u2019s capacity to make protocol adherence and decision variation transparent and discussable within quality improvement settings. Acceptance was conditional on a learning-oriented framing, interpretive scaffolding, and investment in data literacy. The findings suggest that governance framing and interpretive burden function as adoption determinants for retrospective decision support tools in ways not fully captured by standard UTAUT constructs. Retrospective decision mining may complement existing CDSSs not by adding alerts but by strengthening local data-driven learning cycles.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/100274","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T20:21:47Z","timestamp":1788898907000},"page":"e100274-e100274","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of a Decision Mining Tool for Nursing Quality Improvement by Hospital Nurses: Theory-Guided Qualitative Study"],"prefix":"10.2196","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3708-3658","authenticated-orcid":false,"given":"Matthijs","family":"Berkhout","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7269-2892","authenticated-orcid":false,"given":"Jobbe P L","family":"Leenen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1161-7941","authenticated-orcid":false,"given":"Koen","family":"Smit","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6173-2454","authenticated-orcid":false,"given":"Thijs","family":"van Houwelingen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.2196\/76025","article-title":"Understanding the role of clinical decision support systems among hospital nurses using the FITT (fit between individuals, tasks, and technology) framework: qualitative study","volume":"27","author":"Berkhout","journal-title":"J Med Internet Res"},{"key":"R2","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-020-0221-y","article-title":"An overview of clinical decision support systems: benefits, risks, and strategies for success","volume":"3","author":"Sutton","journal-title":"NPJ Digit Med"},{"issue":"1","key":"R3","doi-asserted-by":"publisher","first-page":"29","DOI":"10.7326\/0003-4819-157-1-201207030-00450","article-title":"Effect of clinical decision-support systems: a systematic review","volume":"157","author":"Bright","journal-title":"Ann Intern Med"},{"key":"R4","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.m3216","article-title":"Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials","volume":"370","author":"Kwan","journal-title":"BMJ"},{"key":"R5","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.f657","article-title":"Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials","volume":"346","author":"Roshanov","journal-title":"BMJ"},{"issue":"1","key":"R6","doi-asserted-by":"publisher","DOI":"10.1186\/s13012-022-01199-3","article-title":"Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake","volume":"17","author":"Kouri","journal-title":"Implement Sci"},{"issue":"1","key":"R7","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-025-01662-7","article-title":"A systematic review of clinicians\u2019 acceptance and use of clinical decision support systems over time","volume":"8","author":"Newton","journal-title":"NPJ Digit Med"},{"issue":"11","key":"R8","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0293950","article-title":"Impact of clinical decision support system assisted prevention and management for delirium on guideline adherence and cognitive load among intensive care unit nurses (CDSSD-ICU): protocol of a multicentre, cluster randomized trial","volume":"18","author":"Zhang","journal-title":"PLOS One"},{"issue":"12","key":"R9","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2021-053886","article-title":"Effects of computerised clinical decision support systems (CDSS) on nursing and allied health professional performance and patient outcomes: a systematic review of experimental and observational studies","volume":"11","author":"Mebrahtu","journal-title":"BMJ Open"},{"issue":"4","key":"R10","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1097\/CIN.0000000000001107","article-title":"The effect of clinical decision support systems on patients, nurses, and work environment in ICUs: a systematic review","volume":"42","author":"Sarik\u00f6se","journal-title":"Comput Inform Nurs"},{"issue":"1","key":"R11","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-024-02486-3","article-title":"Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process","volume":"24","author":"Berkhout","journal-title":"BMC Med Inform Decis Mak"},{"issue":"6","key":"R12","doi-asserted-by":"publisher","DOI":"10.3390\/jpm13060929","article-title":"Clinician perspectives on clinical decision support for familial hypercholesterolemia","volume":"13","author":"Bangash","journal-title":"J Pers Med"},{"key":"R13","doi-asserted-by":"crossref","unstructured":"Berkhout M van Barneveld A Smit K van Houwelingen T . \u201cRage against the machine?\u201d: the impact of clinical decision support systems on hospital nursing decision-making, workflow efficiency, and patient outcomes: a rapid review. In: Pucihar A Kljaji\u0107 Bor\u0161tnar S Blatnik M Marolt RWH Bons K Smit M , editors. 38th Bled eConference: Empowering Transformation: Shaping Digital Futures for All: Conference Proceedings. University of Maribor Press; 2025:351-366. [doi: 10.18690\/um.fov.4.2025.22]","DOI":"10.18690\/um.fov.4.2025.22"},{"key":"R14","unstructured":"Decision Model and Notation (DMN), version 1.2. Object Management Group; 2019. URL: https:\/\/www.omg.org\/spec\/DMN\/1.3\/PDF [Accessed 11-08-2026]"},{"issue":"1","key":"R15","doi-asserted-by":"publisher","DOI":"10.1186\/s13012-017-0644-2","article-title":"What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation","volume":"12","author":"Liberati","journal-title":"Implement Sci"},{"issue":"3","key":"R16","doi-asserted-by":"publisher","first-page":"425","DOI":"10.2307\/30036540","article-title":"User acceptance of information technology: toward a unified view","volume":"27","author":"Venkatesh","journal-title":"MIS Q"},{"issue":"1","key":"R17","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.ijmedinf.2014.09.004","article-title":"Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an electronic patient record in acute care settings: an extension of the UTAUT","volume":"84","author":"Maillet","journal-title":"Int J Med Inform"},{"issue":"1","key":"R18","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-022-01958-8","article-title":"Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model","volume":"22","author":"Zha","journal-title":"BMC Med Inform Decis Mak"},{"key":"R19","doi-asserted-by":"crossref","unstructured":"Stebbins RA . Exploratory Research in the Social Sciences. SAGE Publications, Inc; 2001. ISBN: 9780761923985","DOI":"10.4135\/9781412984249"},{"issue":"6","key":"R20","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1093\/intqhc\/mzm042","article-title":"Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups","volume":"19","author":"Tong","journal-title":"Int J Qual Health Care"},{"issue":"5","key":"R21","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1016\/j.jpsychires.2010.10.008","article-title":"The role and interpretation of pilot studies in clinical research","volume":"45","author":"Leon","journal-title":"J Psychiatr Res"},{"issue":"13","key":"R22","doi-asserted-by":"publisher","first-page":"1753","DOI":"10.1177\/1049732315617444","article-title":"Sample size in qualitative interview studies: guided by information power","volume":"26","author":"Malterud","journal-title":"Qual Health Res"},{"key":"R23","unstructured":"Holloway I Galvin K . Qualitative Research in Nursing and Healthcare. 4th ed. John Wiley & Sons; 2017. ISBN: 9781118874493"},{"issue":"7000","key":"R24","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1136\/bmj.311.7000.299","article-title":"Qualitative research. Introducing focus groups","volume":"311","author":"Kitzinger","journal-title":"BMJ"},{"key":"R25","doi-asserted-by":"crossref","unstructured":"Stewart DW Shamdasani PN Rook DW . Focus Groups: Theory and Practice. SAGE; 2007. ISBN: 9780761925835","DOI":"10.4135\/9781412991841"},{"issue":"9","key":"R26","doi-asserted-by":"publisher","first-page":"1277","DOI":"10.1177\/1049732305276687","article-title":"Three approaches to qualitative content analysis","volume":"15","author":"Hsieh","journal-title":"Qual Health Res"},{"key":"R27","unstructured":"Miles MB Huberman AM Salda\u00f1a J . Qualitative Data Analysis: A Methods Sourcebook. SAGE Publications, Inc; 2014. ISBN: 978-1-4522-5787-7"},{"issue":"1","key":"R28","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.jbi.2009.07.002","article-title":"The technology acceptance model: its past and its future in health care","volume":"43","author":"Holden","journal-title":"J Biomed Inform"},{"issue":"1","key":"R29","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-023-00899-4","article-title":"Barriers and facilitators to utilizing digital health technologies by healthcare professionals","volume":"6","author":"Borges do Nascimento","journal-title":"NPJ Digit Med"}],"container-title":["JMIR Formative Research"],"original-title":[],"language":"en","deposited":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T20:21:50Z","timestamp":1788898910000},"score":1,"resource":{"primary":{"URL":"https:\/\/formative.jmir.org\/2026\/1\/e100274"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,8]]},"references-count":29,"URL":"https:\/\/doi.org\/10.2196\/100274","relation":{},"ISSN":["2561-326X"],"issn-type":[{"value":"2561-326X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,8]]},"article-number":"v10i1e100274"}}