Bupa Cromwell Hospital utilizes MedModel Process Simulation Software

MedModel process simulation software used by Bupa Cromwell Hospital to achieve major growth plans, cut waiting times and improve patient experience
Bupa Cromwell Hospital, Bupa’s flagship hospital in the United Kingdom, has a mission to become London’s most advanced private hospital and to grow the business by 60% in just three years. Discrete Event Simulation Software specialists, Production Modelling, were selected to help in two ways. First, to assess the feasibility of the hospital’s proposed redesign of its front-of-house facilities. Secondly, to identify best queuing logistics and staffing levels to accommodate an exponential growth in patient throughput. The final outcome was a solution that will deliver shorter waiting times for 60% more traffic, without employing any extra personnel front-of-house.

Bupa Cromwell Hospital – and the challenge it set itself

Bupa Cromwell Hospital is a world class private hospital with around 400 consultants, many from London’s teaching hospitals. Discerning patients from around the world expect the very highest standards, and that applies from the moment they cross the threshold.
Like many prestigious organizations, the hospital has an imposing monolithic reception area complete with marble reception desk, where all the greeting, registration and initial administration is performed. When the hospital embarked on a major redevelopment program, they took the opportunity to re-evaluate the whole welcome and registration process; the aim being to remove barriers, improve the patient experience, accommodate significantly more patients and contain staffing costs. All this against a backdrop of doubt as to whether current business processes could cope.
Given the scale of change and the scale of investment, management needed a proven way to quantify the implications and feasibility in the light of planned growth in volumes.

Complexity and the role of process simulation software

What was needed was a discrete event process simulation model that could isolate variables, analyze alternatives and to arrive at the optimum solution before construction began. This would mean sampling a distribution of real-life data and recognizing inter-dependencies and shared resources between departments. The model would have to provide a realistic simulation, taking the current-state scenario, applying randomness and arriving at an ideal future-state scenario. And for stakeholder buy-in, it should ideally be capable of creating an easily assimilated visualization of movements and bottlenecks – both current and future state.
The task would be highly complex, involving different types of patient; in-patients, out-patients, scheduled in-patient reassessment and out-patient walk-ins. Each moves in a different way, with its own pattern of waiting times at registration and appointments. Patients may also bring family or friends to accompany them, all of whom have to be accommodated. Once moved from front-of-house, patients again take different routes, possibly to a nurse, an appointment or a room for overnight stay.
The model would have to recognize separate roles, including porters, nurses, and financial administration, as well as reception staff. To complicate the issue further, in practice there was an element of job sharing depending on which roles are busy and when, plus special rosters for night cover. All of which would have to be superimposed onto a blueprint drawing of the existing and planned front-of-house facilities.

A process simulation solution from Production Modelling

Bupa Cromwell Hospital turned to Production Modelling to manage the project using the MedModel process simulation software. Stuart Black, Chief Business Architect, explains, “We selected Production Modelling first because they are recognized by ProModel and secondly because they had already gained experience with hospital-based projects. It was soon apparent we had made the right choice as they immediately understood the challenges and were able to converse with us using terms we understood.”
Production Modelling began by running a workshop to establish the relevant data and inter-dependencies. After a couple of iterations, they were able to report back with an accurate model of current processes, routes, pinch points, decision points, queuing and waiting patterns. Stuart believes this was an important part of gaining credibility with stakeholders, who quickly recognized the validity of the model, before work started on future processes. “Any business change practitioner will agree on the importance of early buy-in,” says Stuart. “We were able to use the simulation animations, superimposed onto blueprints of the front-of-house areas, showing how patients moved through the model and the number of patients in each area at different times of the day. This was incredibly effective. Of course, however effective visualization may have been as a communications tool, all decision making was supported by a wealth of analyses.

The outcomes

Work first began in March 2012 and by July the whole project was complete and the results have been spectacular. The simulation demonstrated that if the current physical layout and processes were left unchanged, and staff levels unaltered, average queuing and waiting time would increase from ten minutes to 87 minutes, assuming a 60% increase in volume of patients. By adopting the new layout and processes, average queuing and waiting time would actually decrease to just eight minutes, without any change in staff levels (fig 1).

Fig 1

Similarly, the planned 60% growth in patient volumes would result in queue length increasing from 35 to 261 patients if the current layout and processes remained unchanged. Adopting the proposed floorplan and processes, while retaining the same staff levels, would achieve a reduction in queue levels from the current 35 to 14 patients - despite an increase of 60% in patient traffic (fig 2).

Fig 2

Last word goes to Stuart: “We are delighted with the project, the results, and the professional support we have received from Production Modelling. This has been a fascinating and very valuable undertaking that we could never have hoped to achieve without expert guidance.”