How to analyze federal state and county level healthcare databases for college assignment with examples and recommendations

Federal, State, and County Healthcare Databases: Analysis, Ownership, Users, Features, Shortcomings, and Improvement Recommendations for College Assignments

Locate one of each federal-, state- and county-level healthcare database (except NLM).

Consider databases that provide comprehensive health statistics relevant to public health policy and research.

Analyze what type of data it contains and how it differs.

Who owns and maintains it?

Who are its users and for what purpose do they use it?

Researchers frequently rely on these resources to inform evidence-based decisions in healthcare planning.

Are the desired data easily processed according to the entered requirements?

Evaluate the special features each database has and its shortcomings.

What recommendation would you make for its improvements?

Enhancements could focus on improving user interfaces to make data extraction more intuitive for beginners.

Your APA formatted assignment comprising 2-4, double-spaced, typed in 12-point Times New Roman (or 11- point Calibri) excluding the Cover and Reference pages should be submitted by Tuesday mid-night.

Minimum 2 credible sources should be used to support your conclusions.

Follow APA 7.

Ensure that your references include recent publications to reflect current developments in healthcare data management.

Sample Answer Content

For a federal-level database, the Centers for Disease Control and Prevention’s National Center for Health Statistics offers vital statistics and survey data on population health trends.

At the state level, California’s Health and Human Services Open Data Portal provides datasets on Medicaid enrollment and hospital discharges, differing in granularity from federal sources.

A county example like New York City’s EpiQuery system allows querying of community health profiles, owned by local health departments for targeted public health interventions.

Recommendations include integrating AI tools for better data processing in all levels to address common shortcomings like outdated interfaces.

References

• Annis, A., Reaves, C., Sender, J. and Bumpus, S. (2023) ‘Health-Related Data Sources Accessible to Health Researchers From the US Government: Mapping Review’, Journal of Medical Internet Research, 25, p. e43802. Available at: https://doi.org/10.2196/43802 (Accessed: 12 January 2026).
• Hamad, R., Lyman, K.A., Lin, F., Modrow, M.F., Ozluk, P., Azar, K.M.J., Goodin, A., Isasi, C.R., Kitzman, H.E., Knight, S.J., Marcus, G.M., McMahill-Walraven, C.N., Meissner, P., Nair, V., O’Brien, E.C., Olgin, J.E., Peyser, N.D., Sylwestrzak, G., Williams, N., Pletcher, M.J. and Carton, T. (2022) ‘The U.S. COVID-19 County Policy Database: a novel resource to support pandemic-related research’, BMC Public Health, 22, p. 1882. Available at: https://doi.org/10.1186/s12889-022-14132-6 (Accessed: 12 January 2026).
• McNeill, M. (2022) ‘Health Care Database Comparisons by State’, Delaware Journal of Public Health, 8(5), pp. 212–214. Available at: https://doi.org/10.32481/djph.2022.12.045 (Accessed: 12 January 2026).
• Williams, C., Skrip, L.A., Adams, S.A. and Vermund, S.H. (2024) ‘Examining County-Level Associations between Federally Qualified Health Centers and Sexually Transmitted Infections: A Political Ecology of Health Framework’, Healthcare, 12(3), p. 295. Available at: https://doi.org/10.3390/healthcare12030295 (Accessed: 12 January 2026).