{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T05:49:59Z","timestamp":1768888199350,"version":"3.49.0"},"reference-count":39,"publisher":"Georg Thieme Verlag KG","issue":"01","funder":[{"name":"EU\/IMI project Electronic Health Records for Clinical Research","award":["115189"],"award-info":[{"award-number":["115189"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n          Background\u2003Even though clinical trials are indispensable for medical research, they are frequently impaired by delayed or incomplete patient recruitment, resulting in cost overruns or aborted studies. Study protocols based on real-world data with precisely expressed eligibility criteria and realistic cohort estimations are crucial for successful study execution. The increasing availability of routine clinical data in electronic health records (EHRs) provides the opportunity to also support patient recruitment during the prescreening phase. While solutions for electronic recruitment support have been published, to our knowledge, no method for the prioritization of eligibility criteria in this context has been explored.<\/jats:p><jats:p>\n          Methods\u2003In the context of the Electronic Health Records for Clinical Research (EHR4CR) project, we examined the eligibility criteria of the KATHERINE trial. Criteria were extracted from the study protocol, deduplicated, and decomposed. A paper chart review and data warehouse query were executed to retrieve clinical data for the resulting set of simplified criteria separately from both sources. Criteria were scored according to disease specificity, data availability, and discriminatory power based on their content and the clinical dataset.<\/jats:p><jats:p>\n          Results\u2003The study protocol contained 35 eligibility criteria, which after simplification yielded 70 atomic criteria. For a cohort of 106 patients with breast cancer and neoadjuvant treatment, 47.9% of data elements were captured through paper chart review, with the data warehouse query yielding 26.9% of data elements. Score application resulted in a prioritized subset of 17 criteria, which yielded a sensitivity of 1.00 and specificity 0.57 on EHR data (paper charts, 1.00 and 0.80) compared with actual recruitment in the trial.<\/jats:p><jats:p>\n          Conclusion\u2003It is possible to prioritize clinical trial eligibility criteria based on real-world data to optimize prescreening of patients on a selected subset of relevant and available criteria and reduce implementation efforts for recruitment support. The performance could be further improved by increasing EHR data coverage.<\/jats:p>","DOI":"10.1055\/s-0040-1721010","type":"journal-article","created":{"date-parts":[[2021,1,14]],"date-time":"2021-01-14T00:03:56Z","timestamp":1610582636000},"page":"017-026","source":"Crossref","is-referenced-by-count":15,"title":["Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials"],"prefix":"10.1055","volume":"12","author":[{"given":"Georg","family":"Melzer","sequence":"additional","affiliation":[{"name":"Chair of Medical Informatics, Friedrich-Alexander University Erlangen-N\u00fcrnberg, Erlangen, Germany"}]},{"given":"Tim","family":"Maiwald","sequence":"additional","affiliation":[{"name":"Institute for Electronics Engineering, Department Electrical Engineering, Friedrich-Alexander University Erlangen-N\u00fcrnberg, Erlangen, Germany"}]},{"given":"Hans-Ulrich","family":"Prokosch","sequence":"additional","affiliation":[{"name":"Chair of Medical Informatics, Friedrich-Alexander University Erlangen-N\u00fcrnberg, Erlangen, Germany"}]},{"given":"Thomas","family":"Ganslandt","sequence":"additional","affiliation":[{"name":"Chair of Medical Informatics, Friedrich-Alexander University Erlangen-N\u00fcrnberg, Erlangen, Germany"},{"name":"Heinrich-Lanz-Center for Digital Health, Department of Biomedical Informatics, Mannheim University Medicine, Ruprecht-Karls-University Heidelberg, Mannheim, Germany"}]}],"member":"194","published-online":{"date-parts":[[2021,1,13]]},"reference":[{"issue":"30","key":"ref1","first-page":"A-2111\/B-1763\/C-1695","article-title":"Registration of Clinical Studies from View of Ethics Committees (german language)","volume":"101","author":"N Victor","year":"2004","journal-title":"Deutsches \u00c4rzteblatt"},{"issue":"06","key":"ref2","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.ijmedinf.2011.02.003","article-title":"Comparing semi-automatic systems for recruitment of patients to clinical trials","volume":"80","author":"M Cuggia","year":"2011","journal-title":"Int J Med Inform"},{"key":"ref3","first-page":"1","volume-title":"Controlled clinical trials - an introduction (german language)","author":"M Schumacher","year":"2008"},{"key":"ref4","first-page":"108","article-title":"Case report from the EHR4CR project\u2014A European Survey on Electronic Health Records Systems for Clinical Research","author":"D Kalra","year":"2011","journal-title":"iHealth Connections"},{"issue":"20","key":"ref5","first-page":"1","article-title":"Factors that limit the quality, number and progress of randomised controlled trials","volume":"3","author":"R J Prescott","year":"1999"},{"issue":"04","key":"ref8","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1177\/2168479016632271","article-title":"The impact of protocol amendments on clinical trial performance and cost","volume":"50","author":"K A Getz","year":"2016","journal-title":"Ther Innov Regul Sci"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"90S","DOI":"10.1177\/0022034513487560","article-title":"Using electronic dental record data for research: a data-mapping study","volume":"92","author":"K Liu","year":"2013","journal-title":"J Dent Res"},{"key":"ref10","first-page":"231","article-title":"Development of an electronic health record-based clinical trial alert system to enhance recruitment at the point of care","volume":"2005","author":"P J Embi","year":"2005","journal-title":"AMIA Annu Symp Proc"},{"issue":"03","key":"ref11","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.ijmedinf.2012.11.008","article-title":"Secondary use of routinely collected patient data in a clinical trial: an evaluation of the effects on patient recruitment and data acquisition","volume":"82","author":"F K\u00f6pcke","year":"2013","journal-title":"Int J Med Inform"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.jbi.2014.10.006","article-title":"Using electronic health records for clinical research: the case of the EHR4CR project","volume":"53","author":"G De Moor","year":"2015","journal-title":"J Biomed Inform"},{"issue":"12","key":"ref13","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.ijmedinf.2014.08.007","article-title":"Does single-source create an added value? 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