Statistical Data Integration for Health Policy Evidence-Building

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.

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Publication Details

Journal
Annual Review of Statistics and Its Application
Published
2024-08-19
DOI
https://doi.org/10.1146/annurev-statistics-112723-034507
Citations
1
Primary Topic
Primary Care and Health Outcomes
Type
article
Field-Weighted Citation Impact
0.85
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article

Statistical Data Integration for Health Policy Evidence-Building

Carolina Franco, Brenda Betancourt, Susan M. Paddock, F. Jay Breidt
1 citations
Annual Review of Statistics and Its Application
Primary Care and Health Outcomes
0.85
article

Statistical Data Integration for Health Policy Evidence-Building

Carolina Franco, Brenda Betancourt, Susan M. Paddock, F. Jay Breidt
article en
1 citations

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.

Annual Review of Statistics and Its ApplicationVol. 12(1)
National Opinion Research Center (US)
Openalex Percentile: Top 23%
Primary Care and Health Outcomes
0.85
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Statistical Data Integration for Health Policy Evidence-Building — Carolina Franco, Brenda Betancourt, et al. · Annual Review of Statistics and Its Application (2024) | TGRS Research Map | TGRS