Resource management in hospital surgeries

One of the leading hospitals in the USA, the UCLA Ronald Reagan Medical Centre in Los Angeles, has used operational research to effectively manage costs at its operating room suites, saving millions of dollars a year.

The outside of the UCLA Ronald Reagan building.
Photograph of surgery in theatre

The Problem

The Operational Services Department (OSD) at the UCLA Ronald Reagan Medical Centre in California, USA, serves around 27,000 patients annually by conducting around 2,700 types of elective and emergency surgery across 12 specialities.

This department assigns to each surgery an operating room, an anaesthesiologist, a nursing team and the requisite surgical materials. The department also determines the sequence of surgeries and the scheduled times. The department aims to minimise the resource usage and overtime costs, requiring a significant amount of time devoted to making these resource management decisions. Complexity arises because of four primary reasons:

  1. Operating rooms are expensive and in short supply.
  2. Surgical procedures are often very specialised.
  3. The duration of surgical procedures are very difficult to predict.
  4. The scale of large hospitals makes simultaneous scheduling of multiple resources a computationally challenging task.

Some specialities, such as plastics, ENT, urology, can use any of the operating rooms, but for others, such as vascular, neuro, and liver, only three or fewer operating rooms are available. Rooms have fixed costs for staffing, equipment and cleaning, and overtime costs which are incurred for nurses and technicians if the rooms are required to be open beyond 3pm. There are three shifts or equal duration, with regular working hours of eight hours. Staff who are required to be on call are informed on the previous day. Consequently, the planning horizon is a single day, and overtime costs are about 33% of revenues.

The Solution

With 85% of the OSD’s revenues in the elective procedures, the OR team focussed on elective surgery, which can be scheduled to start between 7am and 3pm. The previous system for decision-making did not consider two important points: first, it did not consider uncertainty in surgical durations; secondly, it did not consider that most anaesthesiologists and rooms can perform more than one speciality – thus it did not exploit the flexibility in the resources.

A Decision Support System (DSS) was implemented to minimise daily expected resource usage and overtime costs. The core of the system was a large-scale, two-stage mixed-integer stochastic dynamic program with recourse, which solved the problem with data-driven optimisation. The resulting model was better able to make use of flexibility in the resources.

Better combinations of operating room capabilities and anaesthesiologist specialisms led to an increased use of staff within the shift, a reduction in overtime costs and a higher number of daily surgeries that could be achieved in the same resources. A system for allowing surgeries to extend past 3pm was identified, which also reduced costs and uncertainty. Better estimations for how long surgeries take also enabled the model to make the best use of resources by matching longer, less certain surgeries with shorter, more certain surgeries.

The Value

The system has successfully incorporated the flexibility in the resources and uncertainty in surgical durations, and explicitly trades off resource usage and overtime costs. It has increased the average daily utilisation of the anaesthesiologists by 3.5% and of the operating rooms by 3.8%, leading to average daily cost savings of around 7%, estimated to save $2.2 million on an annual basis.

Furthermore, insights based on this model have significantly influenced decision-making in the Operating Services Department, and prompted management to investigate other problems in the department using structured and rigorous OR-based methodologies.

Full article available in Impact Magazine, Autumn 2017: ‘Managing the Operating Room Suite at UCLA Ronald Reagan Medical Centre’ pp31-35