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Forecasting Models to Predict EQ-5D Model Indicators for Population Health Improvement

Pathak, Amit
http://orcid.org/0000-0002-9385-9185
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1480959312370497

Abstract Details

2016, Master of Science (MS), Ohio University, Industrial and Systems Engineering (Engineering and Technology).
The healthcare sector possesses big issues needing to be addressed in a number of nations including the United States. Problems within and effecting healthcare arena are complex as they are interdependent on several factors. It. To cope this situation and find solutions, best of predictions backed by data for effective decision making are required. Even though predictions are made, it takes extreme cautiousness to make claims for policy inaction. The EuroQol five Dimension (EQ-5D) questionnaire developed by the Euro-Qol group is one of the most widespread used tools assessing the generic health status of a population using 5 dimensions namely mobility, self-care, usual activities, pain/discomfort and anxiety/depression. This thesis develops a methodology to create forecasting models to predict these EQ-5D model indicators using chosen 65 indicators, capable of defining population health, from the World Bank, World Health Organization and the United Nations Development Programme databases. The thesis provides the capability to gauge an insight into the well-being at individual levels of population by maneuvering the macroscopic factors. The analysis involves data from 12 countries namely Argentina, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Slovenia, Spain and United States, for both sexes with ages ranging from 18 to 75+. The models are created using Artificial Neural Networks (ANN) and are contrasted with statistical models. It is observed that the ANN model with all 65 indicators performed the best and the age group of 75+ was found to be the most correlated with EQ-5D dimensions. Conclusively the research also provides with the countries and indicators that need the most attention to improve the corresponding EQ-5D parameter. This thesis aims at fostering better policy making for increasing well-being of populations by understanding the impact of predominating factors affecting population health.
Gary Weckman (Advisor)
Diana Schwerha (Committee Member)
Tao Yuan (Committee Member)
Andy Snow (Committee Member)
280 p.
Aging; Artificial Intelligence; Behavioral Psychology; Behavioral Sciences; Behaviorial Sciences; Cognitive Psychology; Demographics; Demography; Developmental Psychology; Economics; Educational Tests and Measurements; Evolution and Development; Finance; Gender Studies; Health; Health Care; Health Care Management; Health Sciences; Higher Education; Industrial Engineering; Information Science; Information Systems; Information Technology; Literacy; Mental Health; Public Health; Public Policy; Sanitation; Social Psychology; Social Research; Statistics; Sustainability
Population Health; EQ-5D; Forecasting; Policy; Artificial Neural Networks; Statistics; Healthcare; Visualize; Data; Decision; World Bank,World Health Organization; WHO; United Nations Development Programme; UNDP; Indicator; Regression; Exploratory; Principal Components

Recommended Citations

Citations

  • Pathak, A. (2016). Forecasting Models to Predict EQ-5D Model Indicators for Population Health Improvement [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1480959312370497

    APA Style (7th edition)

  • Pathak, Amit. Forecasting Models to Predict EQ-5D Model Indicators for Population Health Improvement. 2016. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1480959312370497.

    MLA Style (8th edition)

  • Pathak, Amit. "Forecasting Models to Predict EQ-5D Model Indicators for Population Health Improvement." Master's thesis, Ohio University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1480959312370497

    Chicago Manual of Style (17th edition)

ohiou1480959312370497
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This open access ETD is published by Ohio University and OhioLINK.