MENDS: A Scalable Model of Leveraging Electronic Health Record Data for National Chronic Disease Surveillance
The Multi-State EHR-Based Network for Disease Surveillance (MENDS) presents a scalable model for implementing national chronic disease surveillance leveraging electronic health record (EHR) data on broadly distributed large populations in a timely, automated, and sustainable manner.
Traditional public health surveillance methods for non-reportable chronic conditions (eg, population-based surveys) can be largely manual and labor intensive, include limited clinical detail, or be subject to extended delays between data acquisition and dissemination. While traditional surveillance is useful, EHRs have the potential to modernize surveillance by providing clinically detailed data on broadly distributed large populations in a timely, automated, and sustainable manner.
Unlocking the power of EHR data for chronic disease surveillance can provide actionable insights into the geographic patterns and temporal trends of disease. However, timely surveillance data with broad population coverage requires scalable systems. The Multi-State EHR-Based Network for Disease Surveillance (MENDS) presents a scalable distributed network model for implementing national chronic disease surveillance that leverages EHR data. This paper describes lessons learned from the MENDS demonstration project that have shaped implementation and can help inform how others work with EHR data to develop distributed networks for surveillance.
The Multi-State EHR-Based Network for Disease Surveillance (MENDS)
MENDS is a chronic disease surveillance model that leverages clinically detailed EHR data of large, diverse populations to generate prevalence estimates of chronic disease and its risk factors. MENDS aims to be a timely, automated chronic disease surveillance system for monitoring trends, informing policies, planning programs, and evaluating outcomes.
MENDS implementation comprises six key areas: governance, partnerships, technical infrastructure and support, chronic disease algorithms and validation, weighting and modeling, and workforce education for public health data users. Data contributors and authorized data users (eg, state and local health departments) receive focused information, training, and technical assistance on MENDS and the use of EHR data for chronic disease surveillance, including query and visualization software guidance.
During the piloting phase, several modifications to MENDS implementation were made in response to both expected and unexpected challenges. These adjustments included:
- Rethinking the partner site recruitment approach
Because few state health departments had direct access to the necessary EHR-based data, MENDS shifted to recruiting data contributors for efficiency and scale – specifically large data aggregators with multiple clinical partners – that could approve the sharing of data and bring health departments in as data users to support surveillance activities.
- Instituting a discovery process
Several partner sites were unable to meet the technical or data requirements; thus, MENDS enhanced the candidate recruitment process to include an assessment of interest, readiness, and capacity to meet core requirements that now incorporates appropriate hardware specifications and a data confirmation investigation.
- Strengthening a new type of information partnership to share data for public health
Noting that this was the first time several data contributors had participated in public health surveillance project, MENDS shared information with partners on the public health surveillance landscape, the systems that collect EHR data, and how those systems work with our software tools.
- Fostering governance flexibility to meet partner site needs beyond the network
To accommodate the varied policy, governance structures, and compliance requirements of partner sites, MENDS established a flexible governance approach, also strengthening data security controls to protect against unauthorized use and release and allowing sites to develop customized data security plans for their site-specific environments.
- Aligning a phased algorithm validation effort to capacity
To better communicate the multistage validation approach for verifying codes, documentation was added to describe the process during technical implementation, prioritize indicators, and support sites in validating one indicator at a time, allowing them to staff the effort more easily.
- Improving efficiency through HL7® Fast Healthcare Interoperability Resources (FHIR®) standards
Managing the variation in data contributors’ source data formats was a resource-heavy and time-intensive effort; implementing the Bulk Data Access Application Programming Interface (API) is intended to simplify the provision of data to MENDS, reducing the burden and streamlining the process of bringing on new partners.
Why this is important:
Modernizing surveillance using EHR data has the potential to be timely, actionable, and sustainable, producing reliable estimates at different geographic levels that can complement existing chronic disease surveillance methods. These activities strengthen infrastructure that can be leveraged across priorities and conditions and have wide public health applicability. As a demonstration project for building an EHR-based chronic disease surveillance model, MENDS has yielded promising implementation strategies and preliminary local prevalence estimates.
Read our paper in the Journal of Public Health Management and Practice to learn more about MENDS:
- Leveraging Electronic Health Record Data for Timely Chronic Disease Surveillance: The Multi-State EHR-Based Network for Disease
Related articles and links:
- Birkhead GS, Klompas M, Shah NR. Uses of electronic health records for public health surveillance to advance public health. Annu Rev Public Health. 2015;36: 345–59.
- Data Modernization Initiative | CDC
- Kraus EK, 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 March/April;28(2):203-206.
- MENDS | NACDD
- Public Health Data Modernization Executive Summary
- Public Health Surveillance and Data—Public Health Surveillance at CDC
- Surveillance Systems: Using Surveillance Systems to Prevent and Control Chronic Diseases
Katherine H. Hohman, DrPH, MPH is an Associate Director of Public Health Practice at the National Association of Chronic Disease Directors (NACDD). Her work is focused on modernizing public health chronic disease surveillance. Since joining NACDD, Kate has been providing leadership to the Multi-State EHR-Based Network for Disease Surveillance (MENDS) project.
Amanda K. Martinez, MPH, MSN, RN is a Consultant to NACDD. Her public health and health care experience have largely focused on program design and leadership, administration, and evaluation. In her current role, Amanda supports MENDS project management and implementation of select activities.