000007622 001__ 7622
000007622 005__ 20240124114247.0
000007622 0247_ $$2DOI$$a10.6083/m4c53kbm
000007622 037__ $$aETD
000007622 245__ $$aMeasuring agreement between electronic health records and medicaid claims across race and federal poverty level categories, in the presence of missing data
000007622 260__ $$bOregon Health and Science University
000007622 269__ $$a2017
000007622 336__ $$aThesis
000007622 502__ $$bM.S.
000007622 520__ $$aOur objective is to apply multiple imputation methods with statistics of agreement and electronic health records (EHR). These methods used together with this type of data is not well documented. By applying these methods in a novel way, we examine their potential for future use.  As a secondary objective, we assess for discrepancies in screening documentation between EHR and Medicaid claims data, across Race and Federal Poverty Level (FPL) categories which may reveal possible issues with data collection that would need to be addressed.
000007622 650__ $$aData Collection$$017385
000007622 650__ $$aElectronic Health Records$$038928
000007622 650__ $$aMedicaid$$021932
000007622 650__ $$aPoverty$$024482
000007622 6531_ $$acontinental population groups
000007622 691__ $$aSchool of Medicine$$041369
000007622 692__ $$aDepartment of Public Health and Preventive Medicine$$041444
000007622 7001_ $$aLatour, Emile
000007622 8564_ $$9b6798e02-0a71-4c90-be5e-b794e92aec4c$$s3401441$$uhttps://digitalcollections.ohsu.edu/record/7622/files/Latour.Emile.2017.pdf
000007622 905__ $$a/rest/prod/70/79/58/26/70795826v
000007622 909CO $$ooai:digitalcollections.ohsu.edu:7622$$pstudent-work
000007622 980__ $$aTheses and Dissertations