{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T20:02:38Z","timestamp":1777320158966,"version":"3.51.4"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684567","type":"print"},{"value":"9781643684574","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"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":[[2024,1,25]]},"abstract":"<jats:p>It is imperative to build clinician trust to reuse ever-growing amounts of rich clinical data. Utilising a proprietary, structured electronic health record, we address data quality by assessing the plausibility of chiropractors, physical therapists and osteopaths\u2019 data entry to help determine if the data is fit for use in predicting outcomes of work-related musculoskeletal disorders using machine learning. For most variables assessed, individual clinician data entry positively correlated to the clinician group\u2019s data entry, indicating data is fit for reuse. However, from the clinician\u2019s perspective, there were inconsistencies, which could lead to data mistrust. When assessing data quality in EHR studies, it is crucial to engage clinicians with their deep understanding of EHR use, as improvement suggestions could be made. Clinicians should be considered local knowledge experts.<\/jats:p>","DOI":"10.3233\/shti230949","type":"book-chapter","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:17:55Z","timestamp":1706177875000},"source":"Crossref","is-referenced-by-count":3,"title":["Understanding Clinician EHR Data Quality for Reuse in Predictive Modelling"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5171-5271","authenticated-orcid":false,"given":"Melinda","family":"Wassell","sequence":"first","affiliation":[{"name":"Central Queensland University, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James L.","family":"Murray","sequence":"additional","affiliation":[{"name":"Work Healthy Australia, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chaithra","family":"Kumar","sequence":"additional","affiliation":[{"name":"Work Healthy Australia, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karin","family":"Verspoor","sequence":"additional","affiliation":[{"name":"RMIT University, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kerryn","family":"Butler-Henderson","sequence":"additional","affiliation":[{"name":"RMIT University, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2023 \u2014 The Future Is Accessible"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230949","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:17:57Z","timestamp":1706177877000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230949"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,25]]},"ISBN":["9781643684567","9781643684574"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230949","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,25]]}}}