Browsing by Author "Yashkin, AP"

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    SCREENING FOR A CHRONIC DISEASE: A MULTIPLE STAGE DURATION MODEL WITH PARTIAL OBSERVABILITY
    (International Economic Review, 2016-08-01) Mroz, TA; Picone, G; Sloan, F; Yashkin, AP
    © (2016) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research AssociationWe estimate a dynamic multistage duration model to investigate how early detection of diabetes can delay the onset of lower extremity complications and death. We allow for partial observability of the disease stage, unmeasured heterogeneity, and endogenous timing of diabetes screening. Timely diagnosis appears important. We evaluate the effectiveness of two potential policies to reduce the monetary costs of frequent screening in terms of lost longevity. Compared to the status quo, the more restrictive policy yields an implicit value for an additional year of life of about $50,000, whereas the less restrictive policy implies a value of about $120,000.
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    Theory of partitioning of disease prevalence and mortality in observational data.
    (Theor Popul Biol, 2017-04) Akushevich, I; Yashkin, AP; Kravchenko, J; Fang, F; Arbeev, K; Sloan, F; Yashin, AI
    In this study, we present a new theory of partitioning of disease prevalence and incidence-based mortality and demonstrate how this theory practically works for analyses of Medicare data. In the theory, the prevalence of a disease and incidence-based mortality are modeled in terms of disease incidence and survival after diagnosis supplemented by information on disease prevalence at the initial age and year available in a dataset. Partitioning of the trends of prevalence and mortality is calculated with minimal assumptions. The resulting expressions for the components of the trends are given by continuous functions of data. The estimator is consistent and stable. The developed methodology is applied for data on type 2 diabetes using individual records from a nationally representative 5% sample of Medicare beneficiaries age 65+. Numerical estimates show excellent concordance between empirical estimates and theoretical predictions. Evaluated partitioning model showed that both prevalence and mortality increase with time. The primary driving factors of the observed prevalence increase are improved survival and increased prevalence at age 65. The increase in diabetes-related mortality is driven by increased prevalence and unobserved trends in time-periods and age-groups outside of the range of the data used in the study. Finally, the properties of the new estimator, possible statistical and systematical uncertainties, and future practical applications of this methodology in epidemiology, demography, public health and health forecasting are discussed.
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    TRENDS IN DIABETES MELLITUS AND RELATED HEALTH OUTCOMES 1991-2013: ACHIEVEMENTS AND CHALLENGES
    (GERONTOLOGIST, 2016-11) Yashkin, AP; Akushevich, I; Fang, F; Yashin, AI