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A Governance Framework to Integrate Longitudinal Clinical and Community Data in a Distributed Data Network: The

Emily M Kraus1, Kenneth A Scott, Rachel Zucker

  • 1Obesity Prevention and Control Branch, Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion (Drs King, Kraus, and Goodman), and Center for Surveillance Epidemiology and Laboratory Services (Ms Garrett), Centers for Disease Control and Prevention, Atlanta, Georgia; Public Health Informatics Institute, Decatur, Georgia (Dr Kraus); Denver Public Health, Denver, Colorado (Drs Davidson and Scott); Departments of Epidemiology (Dr Scott) and Biostatistics and Informatics (Dr Davidson), Colorado School of Public Health, Aurora, Colorado; Adult & Child Consortium for Health Outcomes Research & Delivery Science (Ms Zucker), and Department of Pediatrics, Section of Nutrition (Dr Haemer), University of Colorado Anschutz Medical Campus, Aurora, Colorado; Health Technical Center, The MITRE Corporation, McLean, Virginia (Dr Heisey-Grove); Institute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado (Dr Daley); Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts (Dr Block); Louisiana Public Health Institute, New Orleans, Louisiana (Dr Carton); United States Public Health Service, Washington, District of Columbia (Dr Goodman); Research Informatics & Advanced Analytics, Analytics Resource Center, and Children's Hospital Colorado, Aurora, Colorado (Ms Deakyne Davies).

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Summary

A new governance framework successfully integrated community and clinical data for childhood obesity research. This strategy built trust and enabled efficient data sharing, informing future collaborative health initiatives.

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Area of Science:

  • Public Health Research
  • Data Science
  • Health Informatics

Background:

  • Childhood obesity research requires integrating diverse data sources.
  • Existing data networks often lack community-based organization data.
  • Harmonizing clinical and community data presents significant challenges.

Purpose of the Study:

  • To develop and implement a governance framework for integrating community-based organization data with electronic health records.
  • To support childhood obesity research by creating a distributed health data network (DHDN) with longitudinal patient records.
  • To establish policies and procedures for secure and compliant data sharing between disparate systems.

Main Methods:

  • The Childhood Obesity Data Initiative (CODI) expanded an existing DHDN to include community-generated data.
  • A governance work group developed specific data use and exchange policies.
  • A Master Sharing and Use Agreement (MSUA) and Memorandum of Understanding were drafted and executed.
  • A multiparty infrastructure protocol was approved by the IRB to streamline research applications.

Main Results:

  • A clinical-community governance strategy was implemented, fostering trust and enabling efficient data exchange.
  • Governance capacity was assessed, and regulatory/organizational obstacles were identified and addressed.
  • Linked longitudinal records of clinical and community-derived childhood obesity data were created.
  • IRB approval expedited future research by simplifying application processes.

Conclusions:

  • The CODI governance strategy successfully facilitated data integration and exchange between clinical and community organizations.
  • The developed governance framework and documents can serve as a model for similar data harmonization efforts.
  • Building trust and addressing governance gaps are crucial for effective collaborative health research.