The research objective of this Faculty Early Career Development (CAREER) project is to develop new operations research (OR) models and methods to advance the science of health care delivery for life-threatening chronic diseases such as cancer, diabetes, and cardiovascular disease. Recent advances in medical treatment have resulted in a longer lifespan for many Americans. At the same time the patient population is growing more complex, with multiple chronic diseases, competing risks of health complications, and medication conflicts. As a result, medical decisions are becoming harder because what helps one patient or condition may harm another. Chronic disease screening and medical treatment decisions combine large state spaces that define patient health characteristics, such as clinical risk factors and medication histories, with uncertainty in future health outcomes due to differences among patients in genetic, environmental, and other factors. Decisions about treatment and screening take place over long periods (sometimes decades) under constraints due to medication conflicts. As a result, the stochastic and sequential decision making process gives rise to computational optimization problems that are often unsolvable with state-of-the-art algorithms and computing resources. However, these problems have promising structural properties that can be exploited to achieve meaningful theoretical insights and computationally tractable stochastic optimization methods.

Advancing the understanding of chronic care delivery has the potential to improve the quality of life for a large and growing proportion of the US population. The translation of discoveries based on this research has the potential to improve the efficiency and effectiveness of national screening and treatment policies. Results of this research will be disseminated to the medical community, the engineering research community, and incorporated into educational materials ranging from high school to doctoral studies.

Project Report

This NSF CAREER proposal had three main goals. The first was to develop new operations research models and methods to advance the science of health care delivery for life threatening chronic diseases and to improve patient access to health services. The second was to contribute to the education of a new generation of health systems engineers so that they can advance and apply operations research methods to improve efficiency and effectiveness of the U.S. health care system. The third was to disseminate discoveries from this project to the operations research and medical communities. The research team that carried out this work was comprised of researchers with expertise in engineering, including undergraduate and graduate students, and collaborators in the fields of medicine and health services research. To achieve our first goal, we created new engineering-based quantitative models that can be used to improve healthcare delivery in settings that provide health services for chronic disease screening and treatment. These models predict the outcomes of chronic disease screening and treatment strategies and resource allocation decisions on patient health outcomes and medical costs. The specific context of the work was prevention and treatment of cancer but the approaches are generalizable to other diseases and other contexts. We used clinical data and data abstracted from the medical literature to fit and validate our models. We designed new algorithmic methods for addressing the computationally challenging nature of the mathematical models we developed. We then used these models as the basis for investigation of optimal policies for choosing when to start and stop screening patients, how frequently to screen patients, what treatment options to select for patients once a disease is diagnosed, and how to individualize screening and treatment decisions based on distinguishing risk factors. We also investigated ways to improve patient access to health services and lower the cost of healthcare delivery. To achieve our second goal, the project included undergraduate and graduate students as part of the research team. Five PhD students completed their dissertations on topics within the scope of this project and they are now working in academic and industry research positions in the United States. As part of their research these students regularly visited academic medical centers and worked closely with clinicians and other medical experts. In addition to PhD students, two Master’s students completed Masters Theses, and six undergraduate students were engaged in research experiences, providing them the opportunity for exposure to multidisciplinary research and to publish scientific articles and attend professional conferences to present their work. To achieve our third goal, work from this project was published in archival journal articles in both the medical field and the engineering field. In total, seventeen articles were published based on research discoveries from this project. Additionally, several book chapters and scientific reports were written to disseminate the outcomes of this project. The findings were also presented at scientific meetings, including engineering and medical conferences, and through invited seminars at universities throughout the United States and abroad. Press releases and a short video about the research projects funded under this grant were developed to communicate discoveries to the public. This project has made a contribution the development of human resources in the Science, Technology, Engineering, and Mathematics (STEM) field by providing fund to undergraduate and graduate students to engage in research as part of university degree programs. Research related to this project has also been integrated into university courses and into a high school mathematics textbook developed for an NSF sponsored project called MINDSET.

Project Start
Project End
Budget Start
2012-06-30
Budget End
2014-12-31
Support Year
Fiscal Year
2012
Total Cost
$314,474
Indirect Cost
Name
Regents of the University of Michigan - Ann Arbor
Department
Type
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109