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Abstract
The treatment of chronic diseases consumes 86% of U.S. healthcare costs, and yet the U.S. lags in patient outcomes for chronic diseases compared with other industrialized nations that spend far less per capita on healthcare. Initiatives intended to stem the rapid increase in healthcare costs, such as the 2009 Affordable Care Act (ACA), have not resulted in meaningful improvements to population-level health outcomes or to reductions in per capita costs. We build on prior healthcare research to develop an A-B-C framework, which suggests that chronic diseases with the highest potential for disease state management are those with high (A)voidable costs, available (B)iomarkers to monitor the patient’s status, and a strong (C)linical understanding to manage the disease. We apply the framework using data on diabetic patients from the U.S. state of Vermont Blueprint for Health (VBH) initiative, which included a significant implementation of information technology (IT) and data analytics.
Recommended Citation
Thompson, Steve; Whitaker, Jonathan; Atanasov, Vladimir; and Kohli, Rajiv, "Can We Quantify the Benefits of IT-Enabled Chronic Disease Management?" (2020). AMCIS 2020 Proceedings. 23.
https://aisel.aisnet.org/amcis2020/healthcare_it/healthcare_it/23
Can We Quantify the Benefits of IT-Enabled Chronic Disease Management?
The treatment of chronic diseases consumes 86% of U.S. healthcare costs, and yet the U.S. lags in patient outcomes for chronic diseases compared with other industrialized nations that spend far less per capita on healthcare. Initiatives intended to stem the rapid increase in healthcare costs, such as the 2009 Affordable Care Act (ACA), have not resulted in meaningful improvements to population-level health outcomes or to reductions in per capita costs. We build on prior healthcare research to develop an A-B-C framework, which suggests that chronic diseases with the highest potential for disease state management are those with high (A)voidable costs, available (B)iomarkers to monitor the patient’s status, and a strong (C)linical understanding to manage the disease. We apply the framework using data on diabetic patients from the U.S. state of Vermont Blueprint for Health (VBH) initiative, which included a significant implementation of information technology (IT) and data analytics.
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