Journal of Industrial Engineering and Management (Dec 2010)

Evaluation of industrial engineering students’ competencies for process improvement in hospitals

  • Lukasz Maciej Mazur,
  • Shi-Jie (Gary) Chen

DOI
https://doi.org/10.3926/jiem..v3n3.p603-628
Journal volume & issue
Vol. 3, no. 3
pp. 603 – 628

Abstract

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The failures to properly educate students about process improvement can be seen as major factor leading to increased risks of patient safety and increased wastes in hospital settings. The purpose of this research was two-fold: 1) to identify characteristics that explain the efficacy of Plan-Do-Study-Act (PDSA) based-tools while used by Industrial Engineering (IE) students on multidisciplinary teams in hospital; 2) to identify competencies needed by IEs for effective process improvement in hospital using PDSA based-tools. Exploratory mixed method design approach with survey study, unstructured interviews, and focus group discussions was used to collect the data. A regression analysis was used to identify PDSA based-tool characteristics perceived by IE students as instrumental for process improvement. Next, the abductive inference was applied to analyze qualitative data in order to investigate competencies needed for effective process improvement using PDSA based-tools.Using regression analysis, we found the brainstorming via visualization, recognizing root-cause(s) of the problem and selecting improvement measures via linking the process flow with task(s) characteristics to be the significant characteristics. From qualitative data analysis, we learned that IE students strived in technical analysis but lacked competencies in analyzing qualitative data needed for change implementation efforts. There is increasing evidence that success in achieving process improvement goals is at least partially attributable to implementation processes and contexts and not just to the nature of the technical solution. Therefore, IE students interested in working in hospitals must develop new competencies related to qualitative data analysis to manage change initiatives.

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