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State & local chronic disease surveillance using electronic health record systems

Author

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  • Klompas, M.
  • Cocoros, N.M.
  • Menchaca, J.T.
  • Erani, D.
  • Hafer, E.
  • Herrick, B.
  • Josephson, M.
  • Lee, M.
  • Weiss, M.D.P.
  • Zambarano, B.
  • Eberhardt, K.R.
  • Malenfant, J.
  • Nasuti, L.
  • Land, T.

Abstract

Objectives. To assess the feasibility of chronic disease surveillance using distributed analysis of electronic health records and to compare results with Behavioral Risk Factor Surveillance System (BRFSS) state and small-Area estimates. Methods. We queried the electronic health records of 3 independent Massachusettsbased practice groups using a distributed analysis tool called MDPHnet to measure the prevalence of diabetes, asthma, smoking, hypertension, and obesity in adults for the state and 13 cities. We adjusted observed rates for age, gender, and race/ethnicity relative to census data and compared them with BRFSS state and small-Area estimates. Results.The MDPHnet population under surveillance included 1 073 545 adults (21.8% of the state adult population). MDPHnet and BRFSS state-level estimates were similar: 9.4% versus 9.7% for diabetes, 10.0% versus 12.0% for asthma, 13.5% versus 14.7% for smoking, 26.3% versus 29.6% for hypertension, and 22.8% versus 23.8% for obesity. Correlation coefficients for MDPHnet versus BRFSS small-Area estimates ranged from 0.890 for diabetes to 0.646 for obesity. Conclusions. Chronic disease surveillance using electronic health record data is feasible and generates estimates comparable with BRFSS state and small-Area estimates.

Suggested Citation

  • Klompas, M. & Cocoros, N.M. & Menchaca, J.T. & Erani, D. & Hafer, E. & Herrick, B. & Josephson, M. & Lee, M. & Weiss, M.D.P. & Zambarano, B. & Eberhardt, K.R. & Malenfant, J. & Nasuti, L. & Land, T., 2017. "State & local chronic disease surveillance using electronic health record systems," American Journal of Public Health, American Public Health Association, vol. 107(9), pages 1406-1412.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2017.303874_4
    DOI: 10.2105/AJPH.2017.303874
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    Cited by:

    1. Aishwarya Venkat & Tania M. Alarcon Falconi & Melissa Cruz & Meghan A. Hartwick & Shalini Anandan & Naveen Kumar & Honorine Ward & Balaji Veeraraghavan & Elena N. Naumova, 2019. "Spatiotemporal Patterns of Cholera Hospitalization in Vellore, India," IJERPH, MDPI, vol. 16(21), pages 1-14, November.
    2. Stolte, Allison & Merli, M. Giovanna & Hurst, Jillian H. & Liu, Yaxing & Wood, Charles T. & Goldstein, Benjamin A., 2022. "Using Electronic Health Records to understand the population of local children captured in a large health system in Durham County, NC, USA, and implications for population health research," Social Science & Medicine, Elsevier, vol. 296(C).
    3. Mikyong Shin & Charles Hawley & Heather Strosnider, 2021. "Common and Unique Barriers to the Exchange of Administrative Healthcare Data in Environmental Public Health Tracking Program," IJERPH, MDPI, vol. 18(8), pages 1-10, April.

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