Deploying the REACHnet Multi-State EHR-Based Network for Disease Surveillance (MENDS) node: lessons learned and tools utilized

Abstract

Abstract Objectives We provide an overview of the transformation of REACHnet’s research-quality electronic health records (EHR) dataset into the Multi-State EHR-Based Network for Disease Surveillance (MENDS) dataset to support chronic disease surveillance. Materials and Methods We highlight important governance and regulatory processes, infrastructure implementations, and partnerships that enabled this work, as well as the challenges faced. Results REACHnet transformed clinical data from health systems in Louisiana and Texas into surveillance-ready datasets accessible to public health departments in Louisiana and Texas and the National Association of Chronic Disease Directors (NACDD). Discussion Transforming reliably sourced and curated clinical data into a dataset that can be used by public health professionals for epidemiological surveillance activities required the development of governance, regulatory, and technical approaches that considered the priorities of all stakeholders. This work summarizes the challenges, opportunities, and approaches taken to develop a reliable and relatively low-latency dataset to support epidemiological studies by public health professionals. Conclusion Our work underscores the importance of reliably sourced, standardized EHR data for chronic disease surveillance to inform public health policy and decision-making.