Measuring Population Health Using Electronic Health Records: Exploring Biases and Representativeness in a Community Health Information Exchange.
Assessment is a core function of public health. Comprehensive clinical data may enhance community health assessment by providing up-to-date, representative data for use in public health programs and policies, especially when combined with community-level data relevant to social determinants. In this study we examine routinely collected and geospatially-enhanced EHR data to assess population health at various levels of geographic granularity available from a regional health information exchange. We present preliminary findings and discuss important biases in EHR data. Future work is needed to develop methods for correcting for those biases to support routine epidemiology work of public health.
Indiana University Fairbanks School of Public Health, Department of Epidemiology, Indianapolis, IN, USA.
Brian E
BE
Dixon
Indiana University Fairbanks School of Public Health, Department of Epidemiology, Indianapolis, IN, USA.
P Joseph
PJ
Gibson
Indiana University-Purdue University Indianapolis, Polis Center, Indianapolis, IN, USA.
Karen
K
Frederickson Comer
Regenstrief Institute, Center for Biomedical Informatics, Indianapolis, IN, USA.
Marc
M
Rosenman
D001291:Attitude of Health Personnel; D001292:Attitude to Computers; D015982:Bias; D003920:Diabetes Mellitus / Q000175:diagnosis / Q000453:epidemiology*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D019538:Health Care Surveys / Q000379:methods; D066275:Health Information Exchange / Q000706:statistics & numerical data*; D006801:Humans; D007196:Indiana / Q000453:epidemiology; D011159:Population Surveillance; D015995:Prevalence; D015397:Program Evaluation / Q000379:methods; D014600:Utilization Review / Q000458:organization & administration*