A decision model to support theatre allocation for non-elective patients in a private hospital

Abstract

The unforeseen arrival of patients in need of non-elective surgeries may cause a thoroughly planned operating theatre schedule to change with each arrival. This may have an influence on efficiency, utilization and waiting time between surgeries. The purpose of the study is to offer a solution to this problem by determining which allocation policy for patients in need of non-elective surgery will be best suited for this private hospital. The policy should ensure a balance between scheduling patients for elective surgery and responding to the arrival of patients in need of non-elective surgery, and should contribute towards the utilization of the operating theatres. Operating theatre planning can be a very complex process because many stakeholders are involved and due to the influence of variability on the output of performance measures, such as financial indicators, waiting times, throughput and utilization In order to solve this problem, the objectives of the study are as follows: firstly to investigate the current allocation policy for patients in need of non-elective surgery used in this private hospital and secondly to explore and extract the standards, rules and regulations that should be taken into consideration when designing a theatre schedule. Finally the study wants to propose an allocation policy for patients in need of non-elective surgery to ensure the highest scheduling efficiency, the best resource utilization and minimized waiting time between surgeries. The use of simulation in healthcare is becoming a very popular trend. Simulation models can be valuable when it comes to the observation of the performance measures of different systems and sub-systems within healthcare. It can also be beneficial as a decision support tool and a planning tool. A simulation model was developed based on the flexibility policy currently used by the hospital to determine the utilization of the operating theatres. After the model was verified, it was used as decision model to evaluate different policies, such as the dedicated and hybrid policy. Various scenarios were tested for their effect on the key performance indicators. This enabled the researcher to determine which theatre allocation policy for arriving patients in need of non-elective surgery would be best suited to this hospital. The cumulative utilization of the flexibility policy is compared to the dedicated policy and the hybrid policy for the month of July (2 July — 31 July). Based on the results, it is recommended that the hospital consider implementing the hybrid policy as it will help to ensure a balance between scheduling elective patients and responding to the arrival of non-elective patients, and will contribute to the utilization of the operating theatres.