AuthorAllman, Violeta Suzara
AdvisorDavis, Mary Patricia
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
EmbargoRelease after 04/23/2021
AbstractThis study utilizes historic chronic disease and employment data from the University of Michigan Health and Retirement Study (HRS) to specify a multivariate regression model for forecasting the impact of specific chronic diseases on work life. The purpose of the study is to create a new model for forecasting chronic disease-adjusted work life years, which is a measure of disease burden due to chronic disease. The ability to work may be considered a proxy for quality of life, as it is a means by which a person preserves their financial independence and maintains their financial capacity for self-care. This forecasting model is germane to advanced nursing practice, as it provides practitioners a tool to measure patients’ ability to work given various scenarios of chronic disease – many of which, are preventable. This tool may be useful for motivating patients to adopt healthy lifxestyle behaviors such as smoking cessation, weight loss, exercise, and adopting healthy eating habits so they may change chronic disease trajectories and preserve their ability to work and financially provide for themselves and their families. This advocacy and promotion of patient health through self-care is a cornerstone of advanced nursing practice (Thrasher, 2002). Furthermore, this tool may also be useful for calculating or forecasting disease burden in terms of an individual’s attenuated work years or lost productivity. On a larger scale, this tool may be used to calculate lost labor force participation of a population or group of individuals. These statistics may be used as quality improvement measures, economic forecasting data, or for justifying healthcare policy changes or for the allocation of healthcare resources.
Degree ProgramGraduate College