Data Mining for Health Care Professionals: MBA Course Projects Resulting in Hospital Improvements

Data Mining for Health Care Professionals: MBA Course Projects Resulting in Hospital Improvements

Alan Olinsky (Bryant University, USA) and Phyllis A. Schumacher (Bryant University, USA)
DOI: 10.4018/978-1-4666-0279-3.ch010

Abstract

In this paper, the authors discuss a data mining course that was offered for a cohort of health care professionals employed by a hospital consortium as an elective in a synchronous online MBA program. The students learned to use data mining to analyze data on two platforms, Enterprise Miner, SAS (2008) and XLMiner (an EXCEL add-in). The final assignment for the semester was for the students to analyze a data set from their place of employment. This paper describes the projects and resulting benefits to the companies for which the students worked.
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Background

A synchronous online MBA program was offered to a cohort of health care professionals employed by several hospitals in neighboring towns, which are organized into a consortium with a common Board of Directors and officers. The students had diverse backgrounds and were employed in different departments in their organizations. There were several doctors and nurses, a physical therapist, human resources employees, business office employees, directors, administrators and staff. One member of the class was the Vice-President of Information Technology, who turned out to be an invaluable resource for any technology issues which arose in the program. The members of the class were assigned to groups of four or five which included diverse representation. These groups were to remain intact for all courses in the program and for extra required components of the program such as work camps and simulation week-ends. For the most part, the groups did remain intact, but some minor reassignments were made during the course of the program. The students developed strong allegiances in these groups which resulted in some significant group projects produced in various courses in the program.

The program was a traditional MBA program in which the curriculum included required basic core courses in statistics, economics, management, marketing, and accounting, as well as advanced business requirements and several electives. The students had to agree on which elective courses they would take. They voted to select these electives from several offered by MBA faculty each semester. The class voted on the choice and all students then took the same elective. One of the core courses was a statistics course, which covered both basic and intermediate topics, including descriptive statistics, inference, linear and multiple regression and analysis of variance. This course was team-taught by the authors. The students were assigned real-data cases to analyze and found the material very useful in their work. A data mining elective was offered by one of the authors as one of several upper level electives from which the students could select. The students had enjoyed the statistics course and found it very useful to their work and so they chose the data mining course from among a group of electives offered.

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