000041528 001__ 41528
000041528 005__ 20240418110341.0
000041528 0247_ $$2doi$$a10.6083/bpxhc41528
000041528 037__ $$aIR
000041528 041__ $$aeng
000041528 245__ $$aUnique biases in electronic health records data for research: a systematic review
000041528 260__ $$bOregon Health and Science University
000041528 269__ $$a2023-08-15
000041528 336__ $$aAbstract
000041528 520__ $$aObservational data fill in knowledge gaps when randomized controlled trials (RCTs) are not ethical or feasible. Electronic health records (EHRs) provide a source of observational data from diverse patient samples that reflect real-world settings. However, observational data are susceptible to biases and EHR data contain new forms of bias(es) because they were collected for clinical and not research purposes.
000041528 540__ $$fCC BY
000041528 542__ $$fIn copyright - joint owners
000041528 650__ $$aElectronic Health Records$$038928
000041528 650__ $$aBias$$028791
000041528 650__ $$aSystematic Reviews as Topic$$012907
000041528 6531_ $$aclinical research
000041528 6531_ $$abioinformatics
000041528 6531_ $$arandomized controlled trials
000041528 6531_ $$aEHR
000041528 691__ $$aSchool of Medicine$$041369
000041528 692__ $$aDepartment of Medical Informatics and Clinical Epidemiology$$041422
000041528 7001_ $$aHsu, Frances$$uOregon Health and Science University$$041354
000041528 7001_ $$aWeiskopf, Nicole$$uOregon Health and Science University$$041354
000041528 711__ $$aResearch Week$$uOregon Health and Science University$$d2023
000041528 8564_ $$94d3f89fb-6d2f-4b2d-947c-65c5228aee96$$s71879$$uhttps://digitalcollections.ohsu.edu/record/41528/files/ResearchWeek.2023.Hsu.Frances.pdf
000041528 980__ $$aResearch Week
000041528 981__ $$aPublished$$b2023-08-15