This case study presents how Hospital Israelita Albert Einstein, leading Latam healthcare organization, utilized advanced analytics to determine the optimal layout for their new Cancer Center hospital. In 2021, as part of their expansion plan, they have decided to build a new Cancer Center in São Paulo, migrating their oncological operation to the new site.

The project for the new hospital was based on three pillars: Clinical Safety, Architecture and Operational Efficiency. The latter was the focus for the analytics’ team effort, using process mining, forecasting the future demand and optimization to generate the ideal layout to minimize movement flows.

The approach taken was based on 3 workstreams:

• Use of process mining  to generate clinical pathways (CP) for all oncology patients in the current operation
• Clustering algorithms to classify the patients considering the different medical specialties used in their CPs
• An optimization model was developed, using mathematical models and metaheuristics, to receive the future demand for each CP along with resources’ requirements and generate the optimal layout suggestion

We captured impressive results: >15% reductions in movements for patients, visitors and materials and >8% for health staff, generating cost savings of approximately 3% of total operating cost.