Integrating Clinical and Community Data: A Framework to Link Patients and Share Data with Clinical, Community, and Public Health Partners
Integrating longitudinal data from community-based organizations with electronic health record information can improve data accessibility and use to understanding health. Lessons learned from the Childhood Obesity Data Initiative.
The September study in the Morbidity and Mortality Weekly Report (MMWR) reveals that many US children gained more weight than expected during the pandemic, which highlights the importance of addressing children’s health challenges. Community organizations play a key role in healthy childhood weight by providing access to healthy foods and opportunities for physical activity; however, information about how children and families participate in community programs and access community supports is difficult to access and rarely incorporated in research and surveillance. Integrating longitudinal data from community-based organizations with electronic health record information can improve data accessibility and use to understanding health. The Childhood Obesity Data Initiative (CODI) provides a framework to collaboratively develop a distributed network infrastructure that links deidentified patient records to community data with a goal to enhance data capacity for research, public health surveillance, program evaluation, and participant tracking.
Between 2018–2020, the Centers for Disease Control and Prevention supported a pilot CODI implementation with three health care systems and two community partners in the greater Denver Metro Area. CODI uses privacy preserving record linkage (PPRL) to harmonize data across organizations for a single patient; PPRL was selected for record linkage because it provides governance advantages and allows organization to retain control over personally identifiable information. The CODI technical architecture was integrated into an existing regional distributed network (the Colorado Health Observation Regional Data Service or CHORDS). Leveraging an existing distributed network offered substantial efficiency during implementation: partnerships had already been established, processes were defined, and stakeholders were experienced with distributed architecture and record linkage concepts.
CODI’s implementation of rapid innovation was successful but not without challenges. CODI prioritizes both partnerships and innovation, and lessons learned on both fronts during this pilot are captured in two publications published ahead of print in the Journal of Public Health Management and Practice (JPHMP).
- The Childhood Obesity Data Initiative: A Case Study in Implementing Clinical-Community Infrastructure Enhancements to Support Health Services Research and Public Health
- A Governance Framework to Integrate Longitudinal Clinical and Community Data in a Distributed Data Network: The Childhood Obesity Data Initiative
Collaborative engagement of stakeholders early and often was critical to ensure an understanding of the project objectives, current state of technological capacity, approved data use, and the desired future state of CODI architecture. A governance framework that protects individual privacy, accommodates organizational data stewardship requirements, and complies with laws and regulations was developed and carried out to support the harmonization of data from disparate clinical and community information systems.
CODI brings together local people (individuals and organizations), processes (data assessments, data sharing, and governance) and technology (record linkage, data models, analytic tools) to create a local infrastructure that supports community efforts to achieve data-driven approaches to improve health and achieve health equity. This infrastructure is intended to be locally owned and sustained to support its community. CODI in Colorado has been sustained through the CHORDS network, and a second CODI site in the North Carolina Triangle Region has begun. From 2020 to 2022, both sites will add critical information on adults, additional chronic diseases, COVID-19, social determinants of health, and household linkages. For more information and technical assistance to implement CODI in your community, please contact firstname.lastname@example.org.
- Developing a Regional Distributed Data Network for Surveillance of Chronic Health Conditions: The Colorado Health Observation Regional Data Service
Dr. Raymond J. King is the Senior Advisor for Informatics in the Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC). He has 20 years of experience at CDC with an interest in informatics, spatial epidemiology, and a systems approach to understanding the distribution and determinants of health and disease and the development of multisector solutions for population health prevention and control. Ray is a graduate of CDC’s Public Health Informatics Fellowship and Emerging Infectious Diseases Fellowship. He received a PhD in Epidemiology and MSc in the Control of Infectious Diseases from the London School of Hygiene and Tropical Medicine and a BA from Emory University.
Emily Kraus is an informatics consultant with over 15 years of experience working with research, quality improvement, operational, and population health solutions that leverage informatics with a focus on inclusive and participatory governance practices. Emily has a PhD in Health Information Technology from the University of Colorado and a Masters in Public Health from Emory University.
Dr. Alyson Goodman is a board-certified pediatrician and medical epidemiologist in the Division of Nutrition, Physical Activity, & Obesity at CDC, and a Commander in the U.S. Public Health Service Commissioned Corps. She received her MD and MPH from Emory University, completed pediatrics residency training at Boston Children’s Hospital & Boston Medical Center, and a post-doctoral fellowship in applied epidemiology with CDC’s Epidemic Intelligence Service. Dr. Goodman’s role as the Obesity Prevention & Control Branch’s Population Health & Healthcare Unit Lead includes augmenting uptake of evidence-based interventions for child obesity prevention & treatment, and a robust informatics portfolio to improve data capacity for research, surveillance & evaluation as well as clinical & population health decision support. She practices clinical pediatrics weekly at a local community health center.