Li, W., Zhang, M., Chen, J., et al. Weighted EHR-based prevalence estimates for hypertension at the state and local levels in Louisiana. BMC Public Health. 2025;25:432.

Advancing chronic disease data modernization enhancements to meet current and future public health challenges. Prev Chronic Dis. 2024. Collection also includes guest editorial:

• Turner K, Hohman KH. Demonstrated progress and future promise of chronic disease data modernization. Prev Chronic Dis. 2024; 21:240396.

Hohman KH, Klompas M, Zambarano B, Wall HK, Jackson SL, Kraus EM. Validation of Multi-State EHR-Based Network for Disease Surveillance (MENDS) data and implications for improving data quality and representativeness. Prev Chronic Dis. 2024;21:230409.

Essaid S, Andre J, Brooks IM, et al. MENDS-on-FHIR: Leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance. JAMIA Open. 2024;7(2):ooae045.

Kraus EM, Saintus L, Martinez AK, et al. Fostering governance and information partnerships for chronic disease surveillance: The Multi-State EHR-Based Network for Disease Surveillance. J Public Health Manag Pract. 2024;30(2):244-254.

• JPHMP Direct related blog post: On MENDS: Governance framework facilitates information sharing for chronic disease surveillance

Hohman KH, Zambarano B, Klompas M, et al. Development of a hypertension electronic phenotype for chronic disease surveillance in electronic health records: Key analytic decisions and their effects. Prev Chronic Dis. 2023;20:230026.

Hohman KH, Martinez AK, Klompas M, et al. Leveraging electronic health record data for timely chronic disease surveillance: The Multi-State EHR-Based Network for Disease Surveillance. J Public Health Manag Pract. 2023;29(2):162-173.

• JPHMP Direct related blog post: MENDS: A scalable model of leveraging electronic health record data for national chronic disease surveillance

Nasuti L, Andrews B, Li W, Wiltz J, Hohman KH, Patanian M. Using latent class analysis to inform the design of an EHR-based national chronic disease surveillance model. Chronic Illn. May 2022.

Kraus EM, Brand B, Hohman KH, Baker EL. New directions in public health surveillance: Using electronic health records to monitor chronic disease. J Public Health Manag Pract. 2022;28(2):203-206.

Cocoros NM, Kirby C, Zambarano B, et al. RiskScape: A data visualization and aggregation platform for public health surveillance using routine electronic health record data. Am J Public Health. 2021 Feb;111(2):269-276.

Cocoros NM, Ochoa A, Eberhardt K, Zambarano B, Klompas M. Denominators Matter: Understanding Medical Encounter Frequency and Its Impact on Surveillance Estimates Using EHR Data. eGEMS. 2019 July;7(1).

Klompas M, Cocoros NM, Menchaca JT, et al. State and local chronic disease surveillance using electronic health record systems. Am J Public Health. 2017;107(9):1406-1412.

Vogel J, Brown JS, Land T, Platt R, & Klompas M. MDPHnet: Secure, distributed sharing of electronic health record data for public health surveillance, evaluation, and planning. Am J Public Health. 2014;104(12):2265–2270.

Klompas M, McVetta J, Lazarus R, et al. Integrating clinical practice and public health surveillance using electronic medical record systems. Am J Prev Med. 2012;42(6 Suppl 2):S154-62.No