Statistical Data Integration for Health Policy Evidence-Building

Abstract

Health policy evidence-building requires data sources such as health care claims, electronic health records, probability and nonprobability survey data, epidemiological surveillance databases, administrative data, and more, all of which have strengths and limitations for a given policy analysis. Data integration techniques leverage the relative strengths of input sources to obtain a blended source that is richer, more informative, and more fit for use than any single input component. This review notes the expansion of opportunities to use data integration for health policy analyses, reviews key methodological approaches to expand the number of variables in a data set or to increase the precision of estimates, and provides directions for future research. As data quality improvement motivates data integration, key data quality frameworks are provided to structure assessments of candidate input data sources.