Optimisation in healthcare operations

• Main Author: Leung, Kam San.
• Other Authors: Tai Kang
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Industrial engineering::Operations research
• Online Access: http://hdl.handle.net/10356/39374
• Institution: Nanyang Technological University

The healthcare industry has expanded rapidly over the past decade, and this trend is projected to continue, particularly in Singapore, where the government invests heavily into the bioscience industry and an aging population is developing. This expansion will cause operational problems to become more complex than ever. As such, it is necessary to look for optimisation methods that could streamline these processes to avoid a fall in efficiency. The objectives of this report are to identify some of the key problems in healthcare operations that can be improved by optimisation techniques, and to develop a tool for optimising operating room schedules. Literature reviews on journal papers were made to study the descriptions of the healthcare operation problems. Of which, the problems of blood products inventory management, scheduling of pick-up and delivery tasks, hospital evacuations planning, optimal staffing in emergency department, nurse scheduling and operating room scheduling were highlighted. Specifically for the problem of operating room scheduling, various literatures were reviewed to understand the commonly used terms in operating room scheduling, the work process of a typical operating room, the common strategies employed to tackle the problem and performance indexes to evaluate operating room efficiency. In order to develop a tool, a mathematical model proposed by Jebali A., which consists of solving an assignment problem and a sequencing problem, is slightly modified and implemented onto Microsoft Excel. The Frontline System Solver is used to provide the optimisation algorithms to search for an optimal operating room schedule. The developed tool is then tested for its reliability in terms of the optimality of the output and against a key performance index, utilisation rate. It is shown that the output for each of the two steps involved is indeed the optimal as specified by the objective function, while the test against utilisation is inconclusive due to the use of randomly generated data instead of real patients’ data. In addition, the theories for solving continuous optimisation problem were provided to offer an insight to the reader on the mathematics to optimisation.