Insightful health: Amplifying intelligence in healthcare patient flow execution

Description

In the past five years, Hospital Albert Einstein (one of the most referenced in Latin America) has faced significant patient demand growth in number and complexity. During this period, the hospital focused on patient flow operation evolution by process efficiency and descriptive analytics, increasing its virtual capacity to 64 beds. To take the next step in productivity, the hospital partnered with Accenture to establish a new and innovative standard to patient flow operation by embedding sophisticated AI components into the business decision process.

Fabio Ferraretto and Claudia Regina Laselva offer an overview of IRIS, the resulting analytics platform, and explain how it evolved patient flow experience and efficiency with the use of applied AI, statistics, and combinatorial math, allowing the hospital to anticipate E2E visibility within patient flow operations, from admission of emergency and elective demands to assignment and medical releases.

The hospital applied AI in the ER part of the patient flow in order to score the admission propensity of every patient, offering visibility and accuracy into future demands for beds, and then applied statistics and combinatorial math to dtermine patient-bed ideal assignment. The benefits for the hospital are wiser and faster planning, scheduling, and assigning patient demands, higher-quality care (lower waiting times for admission and shorter times of stay), and higher operational efficiency (postponement in expansion CAPEX).