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optimization is a great tool for healthcare

by Laura McLay on June 25th, 2013

Many of the healthcare talks I have attended rely on optimize to allocate scarce resources or to match patients to healthcare resources. It’s worth pointing out that data-driven healthcare analytics doesn’t always imply statistics or simulation. Optimization is a great tool in the analytics toolbox. The optimization models I’ve seen in talks so far are mostly deterministic discrete optimization models (it’s worth pointing out that there are other flavors of optimization). The optimization models:

  • Locate resources (ambulances, clinics, etc.)
  • Assign spatially located patients to medical facilities
  • Route vehicles to optimally deliver healthcare resources
  • “Cover” patients with medical procedures ot healthcare access points
  • Schedule patients, appointments, doctors, and nurses
  • Determine the best mix of procedures to implement

As an optimizer, it has been great to see so many talks that apply optimization to healthcare problems. This conference helps to make the case that there is more to analytics than statistics.

2 Comments
  1. Yongjia Song permalink

    Is there any tutorials that describe how optimization is applied in the field of health care? What is special about health care than other fields where optimization has already been a popular tool?

  2. Yongjia, data-rich areas like healthcare are associated with analytics. For many analytics = statistics and maybe machine learning (but not optimization). It’s too bad that for many, analytics is synonymous with statistics. The crowd at the conference is pretty savvy, and it’s refreshing to see optimization buy-in.

    As for tutorials, check out what the HAS section of INFORMS has to offer (including past workshops, OR Tutorials from INFORMS Annual Meetings) and interesting papers.

    JP Puget has an entire blog about optimization being a well kept secret