This is Chapter 15 of 50 in a summary of the textbook Handbook of Healthcare Delivery Systems. Go to the series index here. Listen on YouTube Playlist, or search your podcast app: Gregory Schmidt
Chapter 15 Summary
An Introduction to Optimization Models and Applications in Healthcare Delivery Systems
Chapter Authors
Wenhua Cao - University of Houston
Gino J. Lim - University of Houston
Some Commentary
This chapter gets into a fair bit of mathematical modelling. I’m not the right person to teach that, and will skip over those sections; therefore, this will be a very brief summary.
1. Optimization
The chapter sources the early days of “optimization” to World War II military logistics. It involves maximizing or minimizing a set of variables, given particular constraints.
The process of optimization has three components: (1) modelling the problem, (2) solving the model, (3) post-optimization analysis.
2. Optimization in Healthcare
An example is the nurse shift optimization problem. It involves the competing goals of “maximizing the service level, minimizing the cost, and maximizing the nurse preferences of shifts, and so on”
Other examples listed include
medical waste collection
medical facility locations
medical facility capacity planning
inpatient and outpatient patient scheduling
disease prediction
radiotherapy planning
3. Mathematical Models
The text discusses the following models
linear programing models
mixed integer programming models
nonlinear programming models
stochastic programming models
multi-objective optimization
Solution Algorithms: simplex method; branch and bound: meta-heuristic local search, simulated annealing, genetic algorithm
