{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T07:11:55Z","timestamp":1781248315679,"version":"3.54.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685960","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T00:00:00Z","timestamp":1747267200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,15]]},"abstract":"<jats:p>Data collection forms and questionnaires are widely used to capture patient data, but their development often receives insufficient attention. The RES-Q+ project aims to semantically standardise a widely used international stroke registry data collection form using interoperability standards such as SNOMED CT and HL7 FHIR, pursuing a canonical, knowledge-graph-based representation as an ultimate goal. We analysed patterns in this RES-Q data collection form to derive general principles for improving the design and semantic alignment of medical forms. We studied the way how residuals such as \u201cnone\u201d, \u201cother\u201d and \u201cunknown\u201d can be modelled using SNOMED CT codes bound to FHIR resources.<\/jats:p>","DOI":"10.3233\/shti250440","type":"book-chapter","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T08:56:59Z","timestamp":1747385819000},"source":"Crossref","is-referenced-by-count":2,"title":["Semantic Representation of Medical Data Collection Forms Using Standards"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7222-3287","authenticated-orcid":false,"given":"Stefan","family":"Schulz","sequence":"first","affiliation":[{"name":"Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1857-1744","authenticated-orcid":false,"given":"Catalina","family":"Mart\u00ednez Costa","sequence":"additional","affiliation":[{"name":"Department of Informatics and Systems, University of Murcia, CEIR Campus Mare Nostrum, IMIB-Arrixaca, Murcia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Intelligent Health Systems \u2013 From Technology to Data and Knowledge"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250440","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T08:56:59Z","timestamp":1747385819000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250440"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,15]]},"ISBN":["9781643685960"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250440","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,15]]}}}