Using data to optimize surgery rooms
Predictive analytics
Challenge
Getting maximum efficiency from the use of available resources is vital for any organization, but it is certainly even more so for a large hospital, where the number of services provided has a direct impact on the health and lives of patients and their families.
Background
Given a certain number of operating theaters available and a certain number of surgeries to be performed in a determined period of time, how can we optimize their use and increase the number of surgeries performed, maximizing all resources available, such as personnel and equipment?
For a large hospital, any improvement in terms of productivity means not only enormous economic savings for the facility, but also and above all the possibility of taking care of the health of its patients more quickly and efficiently. Reducing waiting lists for surgery by always working in maximum safety is certainly one of the crucial factors for an organization whose main task is to offer excellent services in the health sector.
Solution
We employed advanced data predictive analytics that moves through the operations and supply chain cycle and capture a complex network of interactions and connections, unveiling more granular and real-time planning process insights.
Altruistic modelled and analysed a large, disaggregated panel of data from historical data, intervention times and other data made available by the facility, crossing the information with staff shifting and created an algorithm capable of optimally planning the assignment of interventions to the hospital operating rooms.
This made it possible, at the end of the project, to perform 50% more surgeries on patients with the same resources employed.
Results
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