OBJECTIVE: The National Association of Chronic Disease Directors (NACDD) is a nonprofit organization that supports state and territorial chronic disease prevention and health promotion efforts through capacity building and technical assistance. Each year, NACDD surveys health department leaders who oversee chronic disease prevention and health promotion (hereafter, Chronic Disease Directors). We have previously used the annual survey results to inform strategic planning and resource allocation but have not historically published key findings in the peer-reviewed literature. In this paper, we report on NACDD's 2023 survey outcomes and place those findings into the broader public health policy context. DESIGN: State Chronic Disease Directors completed a survey about their organizational capacity and development needs. Responses were summarized in aggregate and by jurisdiction size. RESULTS: State chronic disease units have varied staffing and responsibilities, but most address diabetes, cardiovascular diseases, and cancer screening and prevention. Chronic Disease Directors generally reported strong or improving capacity in most practice areas but ranked workforce development lower. Staffing increased slightly during 2023 compared with the 2020 baseline (median of 1.3 and 1.1 employees per 100 000 jurisdiction population, respectively). However, Chronic Disease Directors expressed ongoing concerns about turnover, hiring, and training of inexperienced staff, as well as about funding limitations and uncertainty. Looking forward to 2024, many Chronic Disease Directors expressed intentions to focus on supporting their workforce with training and development opportunities and addressing health equity. CONCLUSIONS: During this period of pandemic recovery, turnover, hiring, and training-particularly of the many new public health staff-remain key areas of concern for many chronic disease units. Continued stabilization of public health funding and increased prioritization of organizational capacity development-particularly workforce development, chronic disease data systems, and tools for addressing health equity-could help ensure chronic disease units can better address current and emerging challenges in chronic disease prevention and health promotion.

Objective: The National Association of Chronic Disease Directors (NACDD) is a nonprofit organization that supports state and territorial chronic disease prevention and health promotion efforts through capacity building and technical assistance. Each year, NACDD surveys health department leaders who oversee chronic disease prevention and health promotion (hereafter, Chronic Disease Directors). We have previously used the annual survey results to inform strategic planning and resource allocation but have not historically published key findings in the peer-reviewed literature. In this paper, we report on NACDD’s 2023 survey outcomes and place those findings into the broader public health policy context. Design: State Chronic Disease Directors completed a survey about their organizational capacity and development needs. Responses were summarized in aggregate and by jurisdiction size. Results: State chronic disease units have varied staffing and responsibilities, but most address diabetes, cardiovascular diseases, and cancer screening and prevention. Chronic Disease Directors generally reported strong or improving capacity in most practice areas but ranked workforce development lower. Staffing increased slightly during 2023 compared with the 2020 baseline (median of 1.3 and 1.1 employees per 100 000 jurisdiction population, respectively). However, Chronic Disease Directors expressed ongoing concerns about turnover, hiring, and training of inexperienced staff, as well as about funding limitations and uncertainty. Looking forward to 2024, many Chronic Disease Directors expressed intentions to focus on supporting their workforce with training and development opportunities and addressing health equity. Conclusions: During this period of pandemic recovery, turnover, hiring, and training—particularly of the many new public health staff—remain key areas of concern for many chronic disease units. Continued stabilization of public health funding and increased prioritization of organizational capacity development—particularly workforce development, chronic disease data systems, and tools for addressing health equity—could help ensure chronic disease units can better address current and emerging challenges in chronic disease prevention and health promotion. © 2024 Lippincott Williams and Wilkins. All rights reserved.

INTRODUCTION: Surveillance modernization efforts emphasize the potential use of electronic health record (EHR) data to inform public health surveillance and prevention. However, EHR data streams vary widely in their completeness, accuracy, and representativeness. METHODS: We developed a validation process for the Multi-State EHR-Based Network for Disease Surveillance (MENDS) pilot project to identify and resolve data quality issues that could affect chronic disease prevalence estimates. We examined MENDS validation processes from December 2020 through August 2023 across 5 data-contributing organizations and outlined steps to resolve data quality issues. RESULTS: We identified gaps in the EHR databases of data contributors and in the processes to extract, map, integrate, and analyze their EHR data. Examples of source-data problems included missing data on race and ethnicity and zip codes. Examples of data processing problems included duplicate or missing patient records, lower-than-expected volumes of data, use of multiple fields for a single data type, and implausible values. CONCLUSION: Validation protocols identified critical errors in both EHR source data and in the processes used to transform these data for analysis. Our experience highlights the value and importance of data validation to improve data quality and the accuracy of surveillance estimates that use EHR data. The validation process and lessons learned can be applied broadly to other EHR-based surveillance efforts.

OBJECTIVES: The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven's Fast Healthcare Interoperability Resources (HL7(®) FHIR(®)) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline. MATERIALS AND METHODS: The input data source was a research data warehouse containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON transformation language called Whistle, created FHIR R4 V4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. RESULTS: Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. DISCUSSION: OMOP-to-FHIR transformation results passed validation with less than a 1% non-compliance rate. These standards-compliant FHIR resources provided standardized data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR interface for accessing OMOP data. CONCLUSION: MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-to-FHIR transformations provide an alternative mechanism for sharing OMOP data.

CONTEXT: Electronic health records (EHRs) are an emerging chronic disease surveillance data source and facilitating this data sharing is complex. PROGRAM: Using the experience of the Multi-State EHR-Based Network for Disease Surveillance (MENDS), this article describes implementation of a governance framework that aligns technical, statutory, and organizational requirements to facilitate EHR data sharing for chronic disease surveillance. IMPLEMENTATION: MENDS governance was cocreated with data contributors and health departments representing Texas, New Orleans, Louisiana, Chicago, Washington, and Indiana through engagement from 2020 to 2022. MENDS convened a governance body, executed data-sharing agreements, and developed a master governance document to codify policies and procedures. RESULTS: The MENDS governance committee meets regularly to develop policies and procedures on data use and access, timeliness and quality, validation, representativeness, analytics, security, small cell suppression, software implementation and maintenance, and privacy. Resultant policies are codified in a master governance document. DISCUSSION: The MENDS governance approach resulted in a transparent governance framework that cultivates trust across the network. MENDS's experience highlights the time and resources needed by EHR-based public health surveillance networks to establish effective governance.

INTRODUCTION: Modernizing chronic disease surveillance with electronic health record (EHR) data may provide better data to improve hypertension prevention and control, but no consensus exists for an EHR-based surveillance definition for hypertension. The Multi-State EHR-Based Network for Disease Surveillance (MENDS) pilot surveillance system was used to develop and test an electronic phenotype for hypertension. METHODS: We used MENDS data from 1,671,279 patients in Louisiana to examine the effect of different analytic decisions on estimates of hypertension prevalence. Decisions included 1) whether to restrict surveillance to patients with recent blood pressure measurements, 2) varying the number and recency of encounters to define the population at risk of hypertension, 3) how to define hypertension (diagnosis codes, antihypertensive medication, blood pressure measurements, or combinations of these), and 4) how to handle multiple blood pressure measurements on the same day. Results were compared with independent estimates of hypertension prevalence in Louisiana from the Behavioral Risk Factor Surveillance System (BRFSS). RESULTS: Applying varying criteria resulted in hypertension prevalence estimates ranging from 19.7% to 59.3%. A hypertension surveillance strategy that includes a population with at least 1 clinical encounter with measured blood pressure in the previous 2 years and identifies hypertension using all available data (≥1 diagnosis code, ≥1 antihypertensive medication, and ≥2 elevated blood pressure values ≥140/90 mm Hg on separate days) generated estimates in line with population-based survey data. This definition estimated the crude 2019 hypertension prevalence in the state of Louisiana as 43.4% (age-adjusted, 41.0%), comparable with the crude BRFSS estimate of 39.7% (age adjusted, 37.1%). CONCLUSION: Applying different criteria to define hypertension using EHR data has a large effect on hypertension prevalence estimates. The proposed electronic phenotype generates hypertension prevalence estimates that align with independent estimates from BRFSS.

CONTEXT: Electronic health record (EHR) data can potentially make chronic disease surveillance more timely, actionable, and sustainable. Although use of EHR data can address numerous limitations of traditional surveillance methods, timely surveillance data with broad population coverage require scalable systems. This report describes implementation, challenges, and lessons learned from the Multi-State EHR-Based Network for Disease Surveillance (MENDS) to help inform how others work with EHR data to develop distributed networks for surveillance. PROGRAM: Funded by the Centers for Disease Control and Prevention (CDC), MENDS is a data modernization demonstration project that aims to develop a timely national chronic disease sentinel surveillance system using EHR data. It facilitates partnerships between data contributors (health information exchanges, other data aggregators) and data users (state and local health departments). MENDS uses query and visualization software to track local emerging trends. The program also uses statistical and geospatial methods to generate prevalence estimates of chronic disease risk measures at the national and local levels. Resulting data products are designed to inform public health practice and improve the health of the population. IMPLEMENTATION: MENDS includes 5 partner sites that leverage EHR data from 91 health system and clinic partners and represents approximately 10 million patients across the United States. Key areas of implementation include governance, partnerships, technical infrastructure and support, chronic disease algorithms and validation, weighting and modeling, and workforce education for public health data users. DISCUSSION: MENDS presents a scalable distributed network model for implementing national chronic disease surveillance that leverages EHR data. Priorities as MENDS matures include producing prevalence estimates at various geographic and subpopulation levels, developing enhanced data sharing and interoperability capacity using international data standards, scaling the network to improve coverage nationally and among underrepresented geographic areas and subpopulations, and expanding surveillance of additional chronic disease measures and social determinants of health.

The Multi-state EHR-based Network for Disease Surveillance (MENDS) developed a pilot electronic health record (EHR) surveillance system capable of providing national chronic disease estimates. To strategically engage partner sites, MENDS conducted a latent class analysis (LCA) and grouped states by similarities in socioeconomics, demographics, chronic disease and behavioral risk factor prevalence, health outcomes, and health insurance coverage. Three latent classes of states were identified, which inform the recruitment of additional partner sites in conjunction with additional factors (e.g. partner site capacity and data availability, information technology infrastructure). This methodology can be used to inform other public health surveillance modernization efforts that leverage timely EHR data to address gaps, use existing technology, and advance surveillance.