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An algorithm to automate the balancing of supply-demand and optimize the management of resources in the outpatient department of a hospital

Hospital Universitario del Sureste

The ‘Hospital Universitario del Sureste’, is a public hospital within the Autonomous Community of Madrid in Spain that provides primary and secondary care for around 200.000 people. Its sphere of influence covers both big towns and small rural areas. The whole region has suffered a massive increase in population in recent years (the projected number was around 170.000 by 2025 when the hospital was built) so the resources are always strained.

The Hospital Information System (HIS) currently used is Selene, a solution developed by CompuGroup Medical. Everything related to management of supply and demand in the outpatient department is stored within this system, so only one data source is needed for the purpose of solving the challenge.

Our organization has a strong data engineering department with direct access to the system’s database and sound knowledge of the data models so access to the information should not be a problem.


The  Challenge main objective is to optimize the scheduling system used in the outpatient department so better efficiency can be reached. Specifically, we are asking for the design of an algorithm or support tool that provides the best allocation of slots whatever the demand based on a series of constraints (which are basically the availability of resources). As said before this can be done in two phases:

  1. 1. Predict the future demand using historical data.
  2. 2. Propose schedules for the resources using predicted demand and constraints.

It is important to note that the solution only should be able to simulate ´real world´ scenarios, to consume and produce the input and output data. We are not looking for an operational solution that is expected to replace any current system. The possibility to re-run the simulation cheaply and frequently will allow us to have greater flexibility, as defining the schedules manually is a cumbersome and time-consuming task.

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