{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rogers JR"],"funding":["National Center for Advancing Translational Sciences","National Library of Medicine","NCATS NIH HHS","NLM NIH HHS"],"pagination":["104032"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8920749"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["127"],"pubmed_abstract":["Objective
To present an approach on using electronic health record (EHR) data that assesses how different eligibility criteria, either individually or in combination, can impact patient count and safety (exemplified by all-cause hospitalization risk) and further assist with criteria selection for prospective clinical trials.Materials and methods
Trials in three disease domains - relapsed/refractory (r/r) lymphoma/leukemia; hepatitis C virus (HCV); stages 3 and 4 chronic kidney disease (CKD) - were analyzed as case studies for this approach. For each disease domain, criteria were identified and all criteria combinations were used to create EHR cohorts. Per combination, two values were derived: (1) number of eligible patients meeting the selected criteria; (2) hospitalization"],"journal":["Journal of biomedical informatics"],"pubmed_title":["Leveraging electronic health record data for clinical trial planning by assessing eligibility criteria's impact on patient count and safety."],"pmcid":["PMC8920749"],"funding_grant_id":["UL1 TR001873","T15 LM007079","R01 LM009886"],"pubmed_authors":["Ta CN","Weng C","Pavisic J","Rogers JR","Hripcsak G","Liu C","Soroush A","Kuen Cheung Y"],"additional_accession":[]},"is_claimable":false,"name":"Leveraging electronic health record data for clinical trial planning by assessing eligibility criteria's impact on patient count and safety.","description":"Objective
To present an approach on using electronic health record (EHR) data that assesses how different eligibility criteria, either individually or in combination, can impact patient count and safety (exemplified by all-cause hospitalization risk) and further assist with criteria selection for prospective clinical trials.Materials and methods
Trials in three disease domains - relapsed/refractory (r/r) lymphoma/leukemia; hepatitis C virus (HCV); stages 3 and 4 chronic kidney disease (CKD) - were analyzed as case studies for this approach. For each disease domain, criteria were identified and all criteria combinations were used to create EHR cohorts. Per combination, two values were derived: (1) number of eligible patients meeting the selected criteria; (2) hospitalization","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Mar","modification":"2025-04-04T21:44:02.072Z","creation":"2025-04-04T21:44:02.072Z"},"accession":"S-EPMC8920749","cross_references":{"pubmed":["35189334"],"doi":["10.1016/j.jbi.2022.104032"]}}