AI Article Synopsis

  • The Colorado BMI Monitoring System was created to analyze obesity trends in the Denver area by looking at data from various health care and governmental organizations.
  • Data on height and weight were gathered from electronic health records of multiple health care sites between 2013 and 2015, leading to the mapping of obesity prevalence rates by census tract.
  • The findings showed that children had higher obesity rates than adults in specific areas, particularly around the central metropolitan region, highlighting the potential for EHR integration in public health research despite challenges like privacy and data consistency.

Article Abstract

Objectives: The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations.

Materials And Methods: We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region.

Results: We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region.

Practice Implications: The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036605PMC
http://dx.doi.org/10.1177/0033354920904078DOI Listing

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