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Generating Subcounty Health Data Products: Methods and Recommendations From a Multistate Pilot Initiative
Trang Q Nguyen1, Isaac H Michaels, Dulce Bustamante-Zamora
1Office of Public Health Practice, New York State Department of Health, Albany, New York (Dr Nguyen, Mr Michaels, and Ms Li); Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, Rensselaer, New York (Dr Nguyen, Mr Michaels, and Ms Li); Office of Health Equity, California Department of Public Health, Sacramento, California (Dr Bustamante-Zamora); Hospital Industry Data Institute, Missouri Hospital Association, Jefferson City, Missouri (Dr Waterman); Division of General Medical Sciences, Department of Medicine, Washington University School of Medicine, St Louis, Missouri (Dr Nagasako); BJC HealthCare Center for Clinical Excellence, St Louis, Missouri (Dr Nagasako); and University of Wisconsin Population Health Institute, University of Wisconsin-Madison, Madison, Wisconsin (Drs Givens and Gennuso).
This study developed methods to create health data at subcounty levels, addressing the need for more localized health information. Lessons learned will guide future efforts in small-area health data analysis and dissemination.
Area of Science:
- Public Health Data Analytics
- Geospatial Health Information Systems
- Health Disparities Research
Background:
- County-level health data from County Health Rankings & Roadmaps (CHR&R) is valuable, but subcounty data are essential for targeted interventions.
- Pilot projects in California, Missouri, and New York explored methods for generating subcounty health data based on the CHR&R model.
- This work addresses the critical need for granular health data at geographic and demographic levels below the county.
Purpose of the Study:
- To explore and summarize technical and implementation considerations for producing subcounty health data.
- To identify challenges in analyzing and presenting subcounty health data for various audiences.
- To provide lessons learned and recommendations for future subcounty health data initiatives.
Main Methods:
- Utilized 12 data sources to create 40 subcounty measures approximating CHR&R county-level metrics.
- Employed varying technical approaches across three pilot projects, following stages of conceptual development, analysis, and dissemination.
- Developed a compendium of technical resources, including automated programs for subcounty data analysis and reporting.
Main Results:
- Successfully produced subcounty health measures using diverse technical methods and data sources.
- Identified unique technical considerations, including data suppression and stability, crucial for subcounty data.
- Summarized common and unique themes, technical challenges, and implementation hurdles encountered in subcounty data analysis.
Conclusions:
- Demonstrated three successful approaches for creating and disseminating subcounty data products.
- Highlighted the complexities of subcounty data, including estimate stability, accuracy validation, and confidentiality protection.
- Recommended further refinement of techniques to address critical considerations for future subcounty health data projects.
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