A process to deduplicate individuals for regional chronic disease prevalence estimates using a distributed data network of electronic health records

• Main Authors: Kenneth A. Scott (Author), Sara Deakyne Davies (Author), Rachel Zucker (Author), Toan Ong (Author), Emily McCormick Kraus (Author), Michael G Kahn (Author), Jessica Bondy (Author), Matt F. Daley (Author), Kate Horle (Author), Emily Bacon (Author), Lisa Schilling (Author), Tessa Crume (Author), Romana Hasnain‐Wynia (Author), Seth Foldy (Author), Gregory Budney (Author), Arthur J. Davidson (Author)
• Format: Book
• Published: Wiley, 2022-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract Introduction Learning health systems can help estimate chronic disease prevalence through distributed data networks (DDNs). Concerns remain about bias introduced to DDN prevalence estimates when individuals seeking care across systems are counted multiple times. This paper describes a proce...