{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:48:50Z","timestamp":1747216130286,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643683881"},{"type":"electronic","value":"9781643683898"}],"license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"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":[[2023,5,18]]},"abstract":"<jats:p>Synthetic data generation can be applied to Electronic Health Records (EHRs) to obtain synthetic versions that do not compromise patients\u2019 privacy. However, the proliferation of synthetic data generation techniques has led to the introduction of a wide variety of methods for evaluating the quality of generated data. This makes the task of evaluating generated data from different models challenging as there is no consensus on the methods used. Hence the need for standard ways of evaluating the generated data. In addition, the available methods do not assess whether dependencies between different variables are maintained in the synthetic data. Furthermore, synthetic time series EHRs (patient encounters) are not well investigated, as the available methods do not consider the temporality of patient encounters. In this work, we present an overview of evaluation methods and propose an evaluation framework to guide the evaluation of synthetic EHRs.<\/jats:p>","DOI":"10.3233\/shti230149","type":"book-chapter","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T04:44:33Z","timestamp":1684471473000},"source":"Crossref","is-referenced-by-count":1,"title":["A Framework for Evaluating Synthetic Electronic Health Records"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4221-5467","authenticated-orcid":false,"given":"Emmanuella","family":"Budu","sequence":"first","affiliation":[{"name":"Center for Applied Intelligent Systems Research, Halmstad University, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amira","family":"Soliman","sequence":"additional","affiliation":[{"name":"Center for Applied Intelligent Systems Research, Halmstad University, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kobra","family":"Etminani","sequence":"additional","affiliation":[{"name":"Center for Applied Intelligent Systems Research, Halmstad University, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thorsteinn","family":"R\u00f6gnvaldsson","sequence":"additional","affiliation":[{"name":"Center for Applied Intelligent Systems Research, Halmstad University, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Caring is Sharing \u2013 Exploiting the Value in Data for Health and Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230149","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T10:57:46Z","timestamp":1685530666000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230149"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"ISBN":["9781643683881","9781643683898"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230149","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2023,5,18]]}}}