{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rabbani N"],"funding":["NIA NIH HHS","NIAID NIH HHS","NLM NIH HHS"],"pagination":["70-77"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9936847"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["113"],"pubmed_abstract":["<h4>Introduction</h4>Unnecessary laboratory testing contributes to patient morbidity and healthcare waste. Despite prior attempts at curbing such overutilization, there remains opportunity for improvement using novel data-driven approaches. This study presents the development and early evaluation of a clinical decision support tool that uses a predictive model to help providers reduce low-yield, repetitive laboratory testing in hospitalized patients.<h4>Methods</h4>We developed an EHR-embedded SMART on FHIR application that utilizes a laboratory test result prediction model based on historical laboratory data. A combination of semi-structured physician interviews, usability testing, and quantitative analysis on retrospective laboratory data were used to inform the tool's development and ev"],"journal":["Clinical biochemistry"],"pubmed_title":["Targeting repetitive laboratory testing with electronic health records-embedded predictive decision support: A pre-implementation study."],"pmcid":["PMC9936847"],"funding_grant_id":["R01 AI178121","P30 AG059307","R56 LM013365","P30 AG066515"],"pubmed_authors":["Ma SP","Winget M","Svec D","Shieh L","Weber S","Li RC","Chen JH","Boosi S","Rabbani N","Pham TD"],"additional_accession":[]},"is_claimable":false,"name":"Targeting repetitive laboratory testing with electronic health records-embedded predictive decision support: A pre-implementation study.","description":"<h4>Introduction</h4>Unnecessary laboratory testing contributes to patient morbidity and healthcare waste. Despite prior attempts at curbing such overutilization, there remains opportunity for improvement using novel data-driven approaches. This study presents the development and early evaluation of a clinical decision support tool that uses a predictive model to help providers reduce low-yield, repetitive laboratory testing in hospitalized patients.<h4>Methods</h4>We developed an EHR-embedded SMART on FHIR application that utilizes a laboratory test result prediction model based on historical laboratory data. A combination of semi-structured physician interviews, usability testing, and quantitative analysis on retrospective laboratory data were used to inform the tool's development and ev","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Mar","modification":"2025-04-03T23:50:15.203Z","creation":"2025-04-03T23:50:15.203Z"},"accession":"S-EPMC9936847","cross_references":{"pubmed":["36623759"],"doi":["10.1016/j.clinbiochem.2023.01.002"]}}