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  • 1
    Online Resource
    Online Resource
    659-P: Long-Term Health Benefit and Economic Return of Time in Range (TIR) Improvement in Individuals with Type 2 Diabetes
    American Diabetes Association ; 2022
    In:  Diabetes Vol. 71, No. Supplement_1 ( 2022-06-01)
    Details
    In: Diabetes, American Diabetes Association, Vol. 71, No. Supplement_1 ( 2022-06-01)
    Abstract: Time in range (TIR) referres to the percentage of time that blood glucose levels stay within a pre-determined range for patients with diabetes. This study used simulation methods to quantify the long-term health benefit and economic return associated with the improvement of TIR in individuals with T2D. Individuals with self-reported T2D were identified from the 2017-2018 National Health and Nutrition Examination Survey as the target population for the simulation. A Markov model with three states (i.e., diabetes, diabetes with a history of cardiovascular disease (CVD) , death) was developed to calculate the 20-year cost, quality-adjusted life-years (QALY) gained, and cardiovascular disease (CVD) risk reduction under four scenarios: TIR & gt;85%, 71-85%, 51-70%, and ≤50%. The risk of CVD and mortality were extracted from literature. CVD and mortality risk reduction associated with TIR improvement, as well as cost and QALY associated with each health state were all extracted from the literature. Costs were standardized to the 2021 US Dollar, and a 3.0% annual discount rate was used. A willingness-to-pay threshold of $50,000/QALY was used to determine cost-effectiveness. Compared with having a TIR & lt;50%, improving the TIR to 51-70% was associated with an increase of 1.14 QALY and 1.20 life years, and a 5.86% relative risk reduction in CVD; improving the TIR to 71-85% was associated with an increase of 1.69 QALY and 1.46 life-years, and a 8.05% relative risk reduction in CVD; improving the TIR to & gt;85% was associated with an increase of 3.QALY and 1.97 life-years, and a 14.89% relative risk reduction in CVD. The annual spending on treatment to improve the TIR from & lt;50% to 51-70%, 71-85%, and & gt;85% should be lower than $2,592, $3,082, and $4,120 respectively to make the treatment cost-effective. Improving TIR can potentially lead to a substantial health benefit. Our study qualified the maximum medical expenses allocated to improve the TIR while keeping the treatment cost-effective. Disclosure K.Alkhuzam: None. L.Shi: None. V.Fonseca: Consultant; Abbott, Asahi Kasei Corporation, Bayer AG, Novo Nordisk, Sanofi, Research Support; Fractyl Health, Inc., Jaguar Gene Therapy, Stock/Shareholder; Abbott, Amgen Inc., BRAVO4Health, Mellitus Health. Y.Zhang: None. J.Guo: None. H.Shao: Board Member; BRAVO4HEALTH, LLC.
    Type of Medium: Online Resource
    ISSN: 0012-1797
    URL: Article
    DOI: 10.2337/db22-659-P
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2022
    detail.hit.zdb_id: 1501252-9
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  • 2
    Online Resource
    Online Resource
    The role of health system penetration rate in estimating the prevalence of type 1 diabetes in children and adolescents using electronic health records
    Oxford University Press (OUP) ; 2023
    In:  Journal of the American Medical Informatics Association ( 2023-10-09)
    Details
    In: Journal of the American Medical Informatics Association, Oxford University Press (OUP), ( 2023-10-09)
    Abstract: 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 & lt;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.
    Type of Medium: Online Resource
    ISSN: 1067-5027 , 1527-974X
    URL: Article
    DOI: 10.1093/jamia/ocad194
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 2018371-9
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  • 3
    Online Resource
    Online Resource
    1262-P: Developing a Computable Phenotype Algorithm for Identification of Children and Adolescents with Diabetes Using Electronic Health Records
    American Diabetes Association ; 2022
    In:  Diabetes Vol. 71, No. Supplement_1 ( 2022-06-01)
    Details
    In: Diabetes, American Diabetes Association, Vol. 71, No. Supplement_1 ( 2022-06-01)
    Abstract: The Assessing the Burden of Diabetes by Type in Children, Adolescents, and Young Adults (DiCAYA) Network, a CDC/NIDDK-funded collaborative, aims to create a multi-site electronic health record (EHR) -based diabetes surveillance system. Foundational to the network's efforts is the development of a computable phenotype (CP) algorithm that can identify cases of diabetes. To advance the mission of the DiCAYA network, University of Florida (UF) Health system researchers developed a pilot CP algorithm for identifying diabetes cases in youth. The CP algorithm was iteratively derived based on structured data from EHRs (UF Health system 2012-2020) . We randomly selected 500 presumed cases among individuals & lt; 18 years old who has (1) HbA1c ≥ 6.5%; or (2) fasting glucose ≥ 126 mg/dL; or (3) random plasma glucose ≥ 200 mg/dL; or (4) diabetes-related diagnosis code from an inpatient or outpatient encounter; or (5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type. Presumed cases without type 1 (T1D) or type 2 (T2D) diabetes diagnosis codes were categorized as nondiabetes or other types. The rest were categorized as T1D if the ratio of T1D codes to the sum of T1D and T2D codes was ≥ 0.5, or otherwise categorized as T2D. Next, we applied a list of diagnoses and procedures that can determine diabetes type (e.g., steroid use suggests induced diabetes) to correct misclassifications from step 1. Among the 500 reviewed cases, 159 and 64 had T1D and T2D. The sensitivity, specificity, and positive predictive values of the CP algorithm were 94%, 98%, and 96% for T1D; 95%, 95%, and 73% for T2D. We developed a highly accurate EHR-based CP for diabetes in youth based on EHR data from UF Health. Consistent with prior studies, T2D was more difficult to identify using these methods. A DiCAYA-wide validation and algorithm refinement process will be conducted. Disclosure P.Li: None. M.Prosperi: None. B.E.Dixon: Advisory Panel; Merck Sharp & Dohme Corp. D.Dabelea: None. L.H.Utidjian: None. T.L.Crume: None. L.Thorpe: None. A.D.Liese: None. D.Schatz: Advisory Panel; Abbott Diabetes, Medtronic. M.A.Atkinson: None. M.J.Haller: Advisory Panel; SAB Biotherapeutics , Consultant; MannKind Corporation, Sanofi. E.Spector: None. E.Shenkman: None. J.Bian: None. Y.Guo: None. H.Shao: Board Member; BRAVO4HEALTH, LLC. M.A.Atkinson: None. K.Alkhuzam: None. R.S.Patel: None. W.T.Donahoo: None. S.Bost: None. T.Lyu: None. Y.Wu: None. W.Hogan: None. Funding CDC/NIDDK U18DP006512
    Type of Medium: Online Resource
    ISSN: 0012-1797
    URL: Article
    DOI: 10.2337/db22-1262-P
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2022
    detail.hit.zdb_id: 1501252-9
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  • 4
    Online Resource
    Online Resource
    56-LB: Racial/Ethnic Differences in the Use of Blood Pressure–Lowering Drugs Associated with Different Risk levels of Type 2 Diabetes among U.S. Adults without Diabetes
    American Diabetes Association ; 2022
    In:  Diabetes Vol. 71, No. Supplement_1 ( 2022-06-01)
    Details
    In: Diabetes, American Diabetes Association, Vol. 71, No. Supplement_1 ( 2022-06-01)
    Abstract: Understanding differences in risk factors can assist in identifying means to reduce racial/ethnic disparities in type 2 diabetes (T2D) prevalence. Different types of blood pressure (BP) lowering drugs are associated with different levels of T2D risk. This study examined the utilization of BP-lowering drugs among US adults aged 18 and over without diabetes with diagnosed hypertension by racial/ethnic group. We used self-report or ICD-10 diagnostic codes to identify our study population using the 2016-2019 Medical Expenditure Panel Survey. The high T2D risk drugs included beta-blockers and diuretics and the low-risk drugs were ACEI and ARBs. We calculated the percentage of high-risk and low-risk drug use in non-Hispanic Black (NHB) , non-Hispanic White (NHW) , Hispanic, and Asian persons. Logistic regression was used to compare the uses of two drug types across different racial/ethnic groups, controlling for demographics, history of cardiovascular and renal diseases, insurance, duration of hypertension, and general health measurements. We have identified 18,283 individuals, with a mean age of 60.7 and 52.4% were females. Compared with NHB, NHW persons (adjusted odds ratio (aOR) :0.90, 95% CI: 0.58-0.98) , Hispanic (aOR:0.62, 95% CI: 0.56-0.70) , and Asian (aOR:0.54, 95% CI: 0.46-0.64) persons were less likely to receive high-risk drugs. Meanwhile, NHW (aOR: 1.19, 95% CI: 1.09-1.29) , Hispanic (aOR:1.14, 95% CI: 1.03-1.27) , and Asian (aOR:1.19, 95% CI: 1.02-1.40) persons were more likely to use low-risk drugs than NHB persons (all p & lt;0.05) . The highest use of high-risk BP-lowering drugs and the lowest use of low-risk BP-lowering drugs by NHB persons could increase their risks of T2D and contribute to disparities in T2D prevalence between NHB and other racial/ethnic groups. Future studies can quantify the effect of the BP-lowering drug choices on T2D disparities. Disclosure H. Shao: Board Member; BRAVO4HEALTH, LLC. K. Alkhuzam: None. J. Guo: None. T. Jiao: None. S. M. Smith: None. P. Zhang: None. E. W. Gregg: None.
    Type of Medium: Online Resource
    ISSN: 0012-1797
    URL: Article
    DOI: 10.2337/db22-56-LB
    Language: English
    Publisher: American Diabetes Association
    Publication Date: 2022
    detail.hit.zdb_id: 1501252-9
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