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. 2023 Dec 22;31(1):165-173.
doi: 10.1093/jamia/ocad194.

The role of health system penetration rate in estimating the prevalence of type 1 diabetes in children and adolescents using electronic health records

Piaopiao Li  1   2 , Tianchen Lyu  3 , Khalid Alkhuzam  1 , Eliot Spector  3 , William T Donahoo  4 , Sarah Bost  3 , Yonghui Wu  3 , William R Hogan  3 , Mattia Prosperi  5 , Desmond A Schatz  6 , Mark A Atkinson  7 , Michael J Haller  6 , Elizabeth A Shenkman  3 , Yi Guo  3 , Jiang Bian  3 , Hui Shao  1   2   8   9
Affiliations

The role of health system penetration rate in estimating the prevalence of type 1 diabetes in children and adolescents using electronic health records

Piaopiao Li et al. J Am Med Inform Assoc. .

Abstract

Objective: Having sufficient population coverage from the electronic health records (EHRs)-connected health system is essential for building a comprehensive EHR-based diabetes surveillance system. This study aimed to establish an EHR-based type 1 diabetes (T1D) surveillance system for children and adolescents across racial and ethnic groups by identifying the minimum population coverage from EHR-connected health systems to accurately estimate T1D prevalence.

Materials and methods: We conducted a retrospective, cross-sectional analysis involving children and adolescents <20 years old identified from the OneFlorida+ Clinical Research Network (2018-2020). T1D cases were identified using a previously validated computable phenotyping algorithm. The T1D prevalence for each ZIP Code Tabulation Area (ZCTA, 5 digits), defined as the number of T1D cases divided by the total number of residents in the corresponding ZCTA, was calculated. Population coverage for each ZCTA was measured using observed health system penetration rates (HSPR), which was calculated as the ratio of residents in the corresponding ZTCA and captured by OneFlorida+ to the overall population in the same ZCTA reported by the Census. We used a recursive partitioning algorithm to identify the minimum required observed HSPR to estimate T1D prevalence and compare our estimate with the reported T1D prevalence from the SEARCH study.

Results: Observed HSPRs of 55%, 55%, and 60% were identified as the minimum thresholds for the non-Hispanic White, non-Hispanic Black, and Hispanic populations. The estimated T1D prevalence for non-Hispanic White and non-Hispanic Black were 2.87 and 2.29 per 1000 youth, which are comparable to the reference study's estimation. The estimated prevalence of T1D for Hispanics (2.76 per 1000 youth) was higher than the reference study's estimation (1.48-1.64 per 1000 youth). The standardized T1D prevalence in the overall Florida population was 2.81 per 1000 youth in 2019.

Conclusion: Our study provides a method to estimate T1D prevalence in children and adolescents using EHRs and reports the estimated HSPRs and prevalence of T1D for different race and ethnicity groups to facilitate EHR-based diabetes surveillance.

Keywords: children and adolescent; disease surveillance; electronic health records; health system penetration rate; prevalence; type 1 diabetes.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
Estimation of the minimum observed health system penetration rate and prevalence of type 1 diabetes. Abbreviations: SEARCH, SEARCH for Diabetes in Youth Study, a national multi-center study aimed at understanding diabetes among children and young adults in the United States; T1D, type 1 diabetes; dots, estimated prevalence of T1D in areas with the corresponding observed health system penetration rate; blue line, regression line between prevalence of T1D and the observed health system penetration rate; shaded area, 95% confidence interval of the fitted values of the regression line.
Figure 2.
Figure 2.
Comparison of the prevalence of type 1 diabetes between our study estimation and estimation from the SEARCH reference study. Abbreviations: NHW, non-Hispanic White; NHB, non-Hispanic Black; CI, confidence interval; SEARCH reference study, study conducted by SEARCH team (JAMA 2021;326(8):717-727. doi:10.1001/jama.2021.11165).
Figure 3.
Figure 3.
Geographical heatmap for the prevalence of type 1 diabetes in Florida in 2019.
See this image and copyright information in PMC

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