A multi-criteria approach for hospital capacity analysis

• A multi-objective approach was devised to analyze a hospital's capacity to do work.
• This approach facilitates a sensitivity analysis of the patient case mix.
• The multi-objective optimization model was solved by the epsilon constraint method.
• To identify the best solution, a separable programming approach was developed.
• Multiple optimal solutions are obtained via an iterative solution approach.

Hospitals are critical elements of health care systems and analyzing their capacity and productivity is a very important topic. To perform a system wide analysis of public hospital resources and capacity, a multi-objective optimization (MOO) approach has been proposed. This approach identifies the theoretical capacity of the entire hospital and facilitates a sensitivity analysis, for example of the patient case mix (PCM). It is necessary because the competition for hospital resources, for example between different patient types and hospital units, is highly influential on the hospitals productivity. The MOO approach has been extensively tested on a real life case study and significant worth is shown. In this MOO approach, the epsilon constraint method (ECM) has been utilized. However, for solving real life applications, with a large number of competing objectives, it was necessary to devise new and improved algorithms. In addition, to identify the best solution, a separable programming approach was developed. Multiple optimal solutions are also obtained via the iterative refinement and re-solution of the model.