Reidar Hagtvedt

Reidar Hagtvedt

Lecturer in Business Statistics

Alberta School of Business

Accounting, Operations and Information Systems

Research

The focus of my research is healthcare operations management, although I also pursue any quantitative research question that I find intriguing. Currently, I am most interested in issues relating to healthcare-associated infections, including pathogen flows, the psychology of hand-hygiene compliance, and aligning incentives in a game theoretic setting. Game theory has also been the primary approach I have used to study ambulance diversions. In addition to such standard economic tools, I like to apply a variety of tools to best model any given phenomenon, including stochastics, optimization, optimal control, simulation, and network models.

Complementing the modeling aspect of healthcare operations management, I spend considerable time with healthcare professionals in order to gather ideas and data, and to ensure the research problems are significant. I have on-going empirical projects with two groups at the University of Alberta Hospital, as well as other hospitals in Alberta and the US. I have been involved with establishing the Centre for Effective Business Management of Addiction Treatment at the Alberta School of Business, and we are initiating work on the bottlenecks hindering methadone treatment for opiate dependency. My overall goal is to contribute to the body of knowledge that can make healthcare provision more rational, effective, and efficient, combining management science modeling techniques with statistical analysis of real-world data.


Teaching

I teach data analysis and modeling, with a heavy emphasis on business statistics, at the MBA level. The primary difficulty students have at this level is making data analysis relevant to themselves and their careers, as well as understanding basic probability theory and the fundamental logic of inferential statistics. To tie the course into the real world, we have a structured discussion of articles, so that students can find the strengths and weaknesses of data analysis, and how they may relate such information to decisions they will be expected to make. The class has multiple problem sets to make sure students get ample training, and a hand-written, comprehensive, and challenging final exam. The key goal of the course is to provide students with the foundation required to succeed in the MBA program, and to become informed producers and consumers of statistics in their subsequent careers.

Synergy Between Research and Teaching

Since I teach statistics, it is easy to use examples from my research to illustrate problems with hypothesis testing, confidence intervals, or other inferential statistics. Conversely, students will sometimes provide ideas for me to test, or feedback about how they regard certain issues, which will then spark new research questions. More directly, as part of a team of three, I developed VBA modules to help teach statistics, tested the tools with the help of the classes, and published the results in three pedagogical papers.