{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T12:03:55Z","timestamp":1648555435918},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,1,14]],"date-time":"2022-01-14T00:00:00Z","timestamp":1642118400000},"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":[[2022,1,14]]},"abstract":"<jats:p>We interviewed six clinicians to learn about their lived experience using electronic health records (EHR, Allscripts users) using a semi-structured interview guide in an academic medical center in New York City from October to November 2016. Each participant interview lasted approximately one to two hours. We applied a clustering algorithm to the interview transcript to detect topics, applying natural language processing (NLP). We visualized eight themes using network diagrams (Louvain modularity 0.70). Novel findings include the need for a concise and organized display and data entry page, the user controlling functions for orders, medications, radiology reports, and missing signals of indentation or filtering functions in the order page and lab results. Application of topic modeling to qualitative interview data provides far-reaching research insights into the clinicians\u2019 lived experience of EHR and future optimal EHR design to address human-computer interaction issues in an acute care setting.<\/jats:p>","DOI":"10.3233\/shti210864","type":"book-chapter","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T15:48:12Z","timestamp":1642434492000},"source":"Crossref","is-referenced-by-count":0,"title":["Application of Natural Language Processing to Learn Insights on the Clinician\u2019s Lived Experience of Electronic Health Records"],"prefix":"10.3233","author":[{"given":"Yalini","family":"Senathirajah","sequence":"first","affiliation":[{"name":"Biomedical Informatics, School of Medicine, University of Pittsburgh, USA"}]},{"given":"Hwayoung","family":"Cho","sequence":"additional","affiliation":[{"name":"College of Nursing, University of Florida, USA"}]},{"given":"Jaime","family":"Fawcett","sequence":"additional","affiliation":[{"name":"Biomedical Informatics, School of Medicine, University of Pittsburgh, USA"}]},{"given":"Karla M.","family":"Mondejar","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease, Mount Sinai Health System, USA"}]},{"given":"Kenrick","family":"Cato","sequence":"additional","affiliation":[{"name":"School of Nursing, Columbia University, USA"}]},{"given":"Peter","family":"Broadwell","sequence":"additional","affiliation":[{"name":"Center for Interdisciplinary Digital Research, Stanford University, USA"}]},{"given":"Sunmoo","family":"Yoon","sequence":"additional","affiliation":[{"name":"Department of Medicine, Columbia University Irving Medical Center, USA"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Informatics and Technology in Clinical Care and Public Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI210864","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T15:48:13Z","timestamp":1642434493000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI210864"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,14]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti210864","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,14]]}}}