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Hi!
My name is Phil Troy and I'm a quantitative process and decision support / systems analyst.
In case you are wondering what it means to be a quantitative analyst, if we were living during World War II, there is a good chance I would be using my mathematical skills to help the Allies plan radar deployment during the Battle of Britain so as to minimize casualties and destruction, or otherwise help the war effort. Likewise, if I had been working on Wall Street in the 1990s, you would have probably called me a quant and I would have been using similar mathematical skills to help program traders make more money.
Instead, and I prefer it this way, I help hospitals improve processes using a combination of common sense, software development, prescriptive quantitative analytics, and computer simulation. After a few small computer simulation projects, my first big project at the hospital happened after the hospital stopped cardiac surgeries for around a week because there were no available beds in the Intensive Care Unit. To try to preclude this from happening again, I was asked to build a discrete event simulation model of bed usage in the unit and to use it to determine the number of beds the unit should have. Interestingly, the simulation modelling process I used is actually conceptually similar to that of building a model railroad, and then running trains through the model many different times to see how often the train crashed or had delays, where each time the train would start from different randomly selected places or go at different randomly selected speeds. Perhaps even more interestingly, I actually refused to do the project as requested as it would have involved my performing a subjective analysis of the value of reducing patient delays for cardiac surgeries. Instead I built the simulation model and used it to determine the tradeoffs between additional beds and reduced delays for cardiac surgeries, after which the hospital's CEO used the results of that analysis to inform his decision to increase the number of beds in the unit.
Since then, I have been involved in many other healthcare projects. In one project, I built a simulation to get a better idea of the number of beds needed for different surgical specialities. In another project I conceived and then helped design a web based capability to improve the process surgeons go through to schedule surgeries. To collect data needed for other simulations, I built a system to collect patient arrival, ready to leave time, and actual leave time from the recovery room so that nursing management could address delays in patient departures.
A more recent project was a little more radical. The project started in response to a request to build a computer simulation to determine the number of exam rooms needed for a new pre-surgical screening clinic. This was critical because at the time space availability in the hospital was very limited. As the project evolved, it expanded to determining staffing requirements and to scheduling the arrival time of patients, physicians, and staff, as well as the break and lunch times of the staff, so as to minimize physician idle time, staff overtime, and excessive patient waiting. To the best I can tell, this level of micro-management hasn't otherwise been applied to clinics, even though it has the potential of simultaneously reducing costs and improving patient satisfaction.
In addition to a number of other efforts including helping the hospital's purchasing and logistics departments design new capabilities, helping the quality department comparatively analyze clinic performance, and supervising costing analyses of cataract surgical procedures and laundry operations, I have recently also become increasingly involved in a number of related efforts focused on improving patient flow in the hospital using different mathematical optimization efforts. The first of these ongoing efforts involves mathematical efforts to reduce, or hopefully eliminate, medically unacceptable delays for cancer surgeries, the second of these has been to help a cancer network reduce patient waiting for chemotherapy treatments, and the third is going to involve mathematical efforts to maximize patient flow while minimizing operating costs.
To find out more about my work please visit the rest of my web site, or watch the following video. To find out more about operations research, management science and analytics in general, please visit informs.org.
All the best . . .
Phil