Using the CIPP Evaluation Model to Examine a Bachelor of Science in Health Systems Management Program

The purpose of this formative evaluation was to explore the effectiveness of a Bachelor of Science in Health Systems Management (BS HSMT) program in supporting student success through gathering information that led to recommendations for program improvement. The evaluation setting was a public university in the southeastern United States that began enrolling students in the BS HSMT in the fall semester 2017. The BS HSMT was developed to meet the local workforce need for professionals trained in health management and to offer a non-clinical bachelor’s degree for students not competitive or not admitted to their first-choice selective major (described in the evaluation as involuntary major-reselection). The evaluation was guided by Daniel Stufflebeam’s decision-oriented CIPP Evaluation Model including the use of a logic model and strong input from the program stakeholders throughout the evaluation. Data were collected from current students and alumni through an online survey (n = 118) and interviews (n = 6). Data were analyzed using Qualtrics XM, SPSS 26, and MAXQDA 2020. The evaluation questions explored barriers to student success, programmatic strategies to support student success, and the extent the COVID-19 pandemic exacerbated barriers for students. Overall, findings of the evaluation indicated that students and alumni have positive experiences in the program. Barriers identified include poor experiences with faculty or staff, class scheduling, outside responsibilities, issues with poor advising, and large class size. Programmatic strategies to support student success indicated a strong interest in career preparation including internships. Additional strategies included listening to students, offering more classes in the major, and strong faculty and staff support. Lastly, the evaluation found half of students reported the coronavirus pandemic had a negative effect on their experience, with additional barriers including financial problems, looking for employment, trying to take care of family, and having to work more. Findings from the data collection led to ten recommendations for program improvements