{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:43:51Z","timestamp":1785545031380,"version":"3.56.0"},"reference-count":66,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Hum Factors"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Digital decision-support tools for labor care remain limited, with few technologies successfully addressing the complex, time-sensitive decisions required during labor triage. Fit4Labour is a clinician-facing, data-driven research tool, currently under development, that combines computerized cardiotocography interpretation with maternal and fetal risk factors to generate individualized risk scores at labor onset. Its primary aim is to support clinicians in identifying fetuses who may require closer monitoring or expedited delivery, while simultaneously providing reassurance in low-risk cases. By promoting consistent communication and timely escalation of care, the Fit4Labour tool seeks to strengthen clinical decision-making. Understanding and addressing usability and implementation barriers will be critical to its adoption in clinical practice.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to evaluate whether a digitally co-developed labor decision-support tool (Fit4Labour) maintains usability and implementation readiness across NHS hospitals with differing clinical contexts.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n We conducted a convergent parallel mixed methods study in 3 United Kingdom hospitals (December 2022 to May 2025). Phase 1 involved iterative co-development with midwives and doctors at Oxford University Hospitals NHS Foundation Trust; Phase 2 validated the locked version at Birmingham Women\u2019s and Children\u2019s NHS Foundation Trust and Buckinghamshire Healthcare NHS Trust. Participants completed scenario-based usability sessions evaluated with the System Usability Scale (SUS) and Single Ease Question (SEQ), and task completion time, followed by focus groups and interviews analyzed thematically.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Twenty-six health care professionals participated: 12 in co-development (7 midwives, 5 doctors) and 14 in validation (8 midwives, 6 doctors) phases. During co-development at Oxford, the tool met the \u201cexcellent\u201d usability threshold (mean SUS 82.1, SD 12.3), indicating readiness for the validation phase. The locked version (v4.0) independently met the \u201cexcellent\u201d threshold at both validation sites (combined mean SUS 85.8, SD 10.2; Birmingham 80.7, SD 10.8; Buckinghamshire 90.8, SD 7.2). Task completion times were comparable across validation sites (Birmingham 10.3, SD 1.6 min; Buckinghamshire 9.2, SD 1.9 min), while SEQ scores were consistently high across all scenarios (mean 6.1\/7, SD 0.8). Thematic analysis identified 12 themes within 3 domains: clinical integration and workflow, technology adoption and implementation, and patient safety and decision-making. Participants described the Fit4Labour tool as a supportive tool, \u201clike a co-pilot,\u201d improving confidence in decisions with the potential to aid triage assessment. Perceived limitations included an incomplete risk factor profile and the need for minor technical adjustments or integration with existing hospital systems.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Through systematic co-development, the Fit4Labour tool met the established usability benchmark at 2 independent NHS hospitals with markedly different clinical contexts. Clinicians viewed the tool as a supportive aid providing a shared language for risk communication and enhanced decision-making while preserving clinical autonomy. Whether these usability findings translate to improved clinical outcomes in real-world practice requires prospective evaluation.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/87589","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T18:50:07Z","timestamp":1782240607000},"page":"e87589-e87589","source":"Crossref","is-referenced-by-count":0,"title":["Multicenter Usability Evaluation and Co-Development of a Digital Decision-Support Tool for Labor Triage: Mixed Methods Study"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1503-4161","authenticated-orcid":false,"given":"Mariana","family":"Tome","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1966-008X","authenticated-orcid":false,"given":"Xavier","family":"Laurent","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4636-5594","authenticated-orcid":false,"given":"Kristiyan","family":"Georgiev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4119-9562","authenticated-orcid":false,"given":"John","family":"Tolladay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5202-5336","authenticated-orcid":false,"given":"Sarah","family":"Collins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2112-595X","authenticated-orcid":false,"given":"Deborah","family":"Hedgecott","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2784-2040","authenticated-orcid":false,"given":"Lyuba V","family":"Bozhilova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0176-2651","authenticated-orcid":false,"given":"Jane E","family":"Hirst","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4462-112X","authenticated-orcid":false,"given":"Lawrence","family":"Impey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5543-6683","authenticated-orcid":false,"given":"Antoniya","family":"Georgieva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"issue":"21","key":"R1","doi-asserted-by":"publisher","first-page":"2199","DOI":"10.1001\/jama.2018.17163","article-title":"Clinical decision support in the era of artificial intelligence","volume":"320","author":"Shortliffe","journal-title":"JAMA"},{"issue":"1","key":"R2","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","article-title":"High-performance medicine: the convergence of human and artificial intelligence","volume":"25","author":"Topol","journal-title":"Nat Med"},{"issue":"14","key":"R3","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1056\/NEJMra1814259","article-title":"Machine learning in medicine","volume":"380","author":"Rajkomar","journal-title":"N Engl J Med"},{"issue":"1","key":"R4","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-019-0158-1","article-title":"Why digital medicine depends on interoperability","volume":"2","author":"Lehne","journal-title":"NPJ Digit Med"},{"key":"R5","unstructured":"Global Strategy on Digital Health 2020-2025. 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