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Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data

Author

Listed:
  • Tomasallo, C.D.
  • Hanrahan, L.P.
  • Tandias, A.
  • Chang, T.S.
  • Cowan, K.J.
  • Guilbert, T.W.

Abstract

Objectives: We compared a statewide telephone health survey with electronic health record (EHR) data from a large Wisconsin health system to estimate asthma prevalence in Wisconsin. Methods: We developed frequency tables and logistic regression models using Wisconsin Behavioral Risk Factor Surveillance System and University of Wisconsin primary care clinic data. We compared adjusted odds ratios (AORs) from each model. Results: Between 2007 and 2009, the EHR database contained 376 000 patients (30 000 with asthma), and 23 000 (1850 with asthma) responded to the Behavioral Risk Factor Surveillance System telephone survey. AORs for asthma were similar in magnitude and direction for the majority of covariates, including gender, age, and race/ethnicity, between survey and EHR models. The EHR data had greater statistical power to detect associations than did survey data, especially in pediatric and ethnic populations, because of larger sample sizes. Conclusions: EHRs can be used to estimate asthma prevalence in Wisconsin adults and children. EHR data may improve public health chronic disease surveillance using high-quality data at the local level to better identify areas of disparity and risk factors and guide education and health care interventions.

Suggested Citation

  • Tomasallo, C.D. & Hanrahan, L.P. & Tandias, A. & Chang, T.S. & Cowan, K.J. & Guilbert, T.W., 2014. "Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data," American Journal of Public Health, American Public Health Association, vol. 104(1), pages 65-73.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2013.301396_7
    DOI: 10.2105/AJPH.2013.301396
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    Cited by:

    1. 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).

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