Application of an Online Reference for Reviewing<br>Basic Statistical Principles of Operating Room Managemen


Authors: 
Franklin Dexter, Danielle Masursky, Ruth E. Wachtel, and Nancy A. Nussmeier
Volume: 
18(3)
Pages: 
online
Year: 
2010
Publisher: 
Journal of Statistics education
URL: 
http://www.amstat.org/publications/jse/v18n3/dexter.pdf
Abstract: 

Operating room (OR) management differs from clinical anesthesia in that statistical literacy<br><br>is needed daily to make good decisions. Two of the authors teach a course in operations research<br><br>for surgical services to anesthesiologists, anesthesia residents, OR nursing directors, hospital<br><br>administration students, and analysts to provide them with the knowledge to make evidencebased management decisions. Some of these students do not remember enough of their basic<br><br>statistics class(es) to understand the principles presented. We performed a systematic, qualitative<br><br>survey of previous experimental and quasi-experimental studies of the impact of a computer on<br><br>student learning of the basic statistical topics that form a prerequisite to the management course.<br><br>Computer-assisted instruction enhanced student learning of the basic statistical topics.<br><br>We created slides containing both hyperlinks to specific pages of Rice University's introductorylevel free web-based "Online Statistics Book" and OR management examples to provide contex<br>for the material. The website is effective at teaching the material because it directs students<br><br>to test their predictions, which has been shown to enhance learning. Once students have<br><br>completed the statistics review, they have sufficient background to learn the material in the<br><br>OR management course. The students use an interactive Excel spreadsheet dealing with OR<br><br>management topics to provide additional computer-assisted instruction

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education