Development and Validation of the US Diabetes, Obesity, Cardiovascular Disease Microsimulation (DOC-M) Model: Health Disparity and Economic Impact Model.

Background: Few simulation models have incorporated the interplay of diabetes, obesity, and cardiovascular disease (CVD); their upstream lifestyle and biological risk factors; and their downstream effects on health disparities and economic consequences. Methods: We developed and validated a US Diabe...

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Publicado en:Medical Decision Making Vol. 43; no. 7/8; pp. 930 - 949
Autores principales: Kim, David D., Wang, Lu, Lauren, Brianna N., Liu, Junxiu, Marklund, Matti, Lee, Yujin, Micha, Renata, Mozaffarian, Dariush, Wong, John B.
Formato: algorithm equations & formulas research tables/charts Journal Article
Publicado: Sage Publications Inc. Oct/Nov2023
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct/Nov2023
      vid: 43
      iid: 7/8
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        atl: Development and Validation of the US Diabetes, Obesity, Cardiovascular Disease Microsimulation (DOC-M) Model: Health Disparity and Economic Impact Model.
      aug:
        au:
          Kim, David D.
          Wang, Lu
          Lauren, Brianna N.
          Liu, Junxiu
          Marklund, Matti
          Lee, Yujin
          Micha, Renata
          Mozaffarian, Dariush
          Wong, John B.
        affil: Section of Hospital Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
      sug:
        subj:
          Instrument Construction
          Instrument Validation
          Diabetes Mellitus Risk Factors
          Obesity Risk Factors
          Cardiovascular Risk Factors Risk Factors
          Healthcare Disparities
          Simulations
          Life Style
          Economic Factors
          Diabetes Mellitus Risk Factors
          Risk Assessment
          Models, Statistical
          Human
          United States
          Funding Source
          Validation Studies
          Ethnic Groups
          Individualized Medicine
          Health Care Costs
          Prediction Models
          Cost Benefit Analysis
          Calibration
      ab: Background: Few simulation models have incorporated the interplay of diabetes, obesity, and cardiovascular disease (CVD); their upstream lifestyle and biological risk factors; and their downstream effects on health disparities and economic consequences. Methods: We developed and validated a US Diabetes, Obesity, Cardiovascular Disease Microsimulation (DOC-M) model that incorporates demographic, clinical, and lifestyle risk factors to jointly predict overall and racial-ethnic groups-specific obesity, diabetes, CVD, and cause-specific mortality for the US adult population aged 40 to 79 y at baseline. An individualized health care cost prediction model was further developed and integrated. This model incorporates nationally representative data on baseline demographics, lifestyle, health, and cause-specific mortality; dynamic changes in modifiable risk factors over time; and parameter uncertainty using probabilistic distributions. Validation analyses included assessment of 1) population-level risk calibration and 2) individual-level risk discrimination. To illustrate the application of the DOC-M model, we evaluated the long-term cost-effectiveness of a national produce prescription program. Results: Comparing the 15-y model-predicted population risk of primary outcomes among the 2001–2002 National Health and Nutrition Examination Survey (NHANES) cohort with the observed prevalence from age-matched cross-sectional 2003–2016 NHANES cohorts, calibration performance was strong based on observed-to-expected ratio and calibration plot analysis. In most cases, Brier scores fell below 0.0004, indicating a low overall prediction error. Using the Multi-Ethnic Study of Atherosclerosis cohorts, the c-statistics for assessing individual-level risk discrimination were 0.85 to 0.88 for diabetes, 0.93 to 0.95 for obesity, 0.74 to 0.76 for CVD history, and 0.78 to 0.81 for all-cause mortality, both overall and in three racial-ethnic groups. Open-source code for the model was posted at https://github.com/food-price/DOC-M-Model-Development-and-Validation. Conclusions: The validated DOC-M model can be used to examine health, equity, and the economic impact of health policies and interventions on behavioral and clinical risk factors for obesity, diabetes, and CVD. Highlights: We developed a novel microsimula'tion model for obesity, diabetes, and CVD, which intersect together and – critically for prevention and treatment interventions – share common lifestyle, biologic, and demographic risk factors. Validation analyses, including assessment of (1) population-level risk calibration and (2) individual-level risk discrimination, showed strong performance across the overall population and three major racial-ethnic groups for 6 outcomes (obesity, diabetes, CVD, and all-cause mortality, CVD- and DM-cause mortality) This paper provides a thorough explanation and documentation of the development and validation process of a novel microsimulation model, along with the open-source code (https://github.com/food-price/ DOCM_validation) for public use, to serve as a guide for future simulation model assessments, validation, and implementation.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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