Medicine, Preventive

Chronic Diseases are the major cause of mortality around the world, accounting for 7 out of 10 deaths each year in the United States. Because of its adverse effect on the quality of life, it has become a major problem globally. Health care costs involved in managing these diseases are also very high. In this thesis, we will focus on two major chronic diseases Asthma and Diabetes, which are among the leading causes of mortality around the globe. It involves design and development of a predictive analytics based decision support system which uses five supervised machine learning algorithm to predict the occurrence of Asthma and Diabetes. This system helps in controlling the disease well in advance by selecting its best indicators and providing necessary feedback.

Wellness and healthy life are the most common concerns for an individual to lead a happy life. A web-based approach known as Wellness Scoring is being developed taking into people’s concerns for their health issues. In this approach, four different classifiers are being investigated to predict the wellness. In this thesis, we investigated four different classifiers (a probabilistic graphical model, simple probabilistic classifier, probabilistic statistical classification and an artificial neural network) to predict the wellness outcome. An approach to calculate wellness score is also addressed. All these classifiers are trained on real data, hence giving more accurate results. With this solution, there is a better way of keeping track of an individuals’ health. In this thesis, we present the design and development of such a system and evaluate the performance of the classifiers and design considerations to maximize the end user experience with the application. A user experience model capable of predicting the wellness score for a given set of risk factors is developed.

This research focuses on obesity and other major risk factors for chronic diseases
such as Type II Diabetes Mellitus, Heart Disease, and Stroke. Worksite wellness
programs have been successful in this realm of health promotion and disease prevention
for heart disease and stroke, but their effectiveness in treating diabetes has been uncertain
partially due to poor patient compliance, lack of stress reduction strategies, poor diet and
lack of persuasive health education on the risk of being obese. Published peer-reviewed
articles were reviewed, coded and analyzed to determine best practices, using a modified
systematic review approach. The findings from these studies yield results that were used
to develop a new employer-sponsored wellness program that is in accordance with the
recently passed Affordable Care Act.