This project-based capstone integrative seminar focuses on the concepts and techniques of successful health care management practices. It analyzes the process of developing and executing strategies designed to optimize a health care organization and its management. Students apply their knowledge of health care systems, policy, financing, and information systems to a course project. The project integrates essential knowledge from the degree program at both the practical and the theoretical levels while fulfilling the student's own field of professional interest. Prior to capstone enrollment, students are expected to complete the majority of their required major courses. Students should consult with their advisor regarding specific major courses that may be completed with their capstone. NOTE: Students who were admitted to the college before Fall 2019 and have remained active in their original catalog year are not required to take IDIS 601.

The course examines the political, legal, economic and fiscal components that impact and influence health care delivery systems. A focus within the course will be on developing and managing innovations that improve the value of health care. Management challenges and barriers to implementing change within the system will also be examined.

This integrative course is the culminating course in the Master of Science in Health Care Management. All other required coursework must have been completed prior to receiving approval to register for this course. Students during the capstone experience will integrate health care management competencies, and acquired knowledge and skills that combine health care perspectives, theories, skills, and tools in an applied format. Final products include a comprehensive project that incorporates strategic and organizational components designed specific to health care systems. After documenting the above, students will discuss and defend their project orally.

This course covers using Python as a programming language to write, implement, and design programs that are relevant to various aspects of programming in a health setting. After completion of this course, students should be comfortable with the basic data structures in Python and R (including arrays, dictionaries and dataframes), conditional logic and iterators, writing Python and R functions, and using Python libraries to read external data and perform data manipulations and data analysis.