From direct care to the analytics architecture of the State

My career started where the data starts: in clinical practice. I qualified as a nurse at the University of Chile and spent years in inpatient units, emergency shifts and pre-hospital ambulance care. That period taught me something no course does: a first-hand understanding of how patients collide with hospital bureaucracy, where care gets stuck, and how much complexity hides inside a clinical record.

Unlike approaches that treat health data as a purely abstract or computational object, my technical work was built from the operational failures of direct care. The transition was deliberate: first care management and operational excellence, with a Lean Six Sigma Black Belt certification at the University of Chile and postgraduate studies in Public Management, Managerial Control, Business Process Management and Senior Management of Health Institutions. Then engineering and predictive analysis, with computer science studies at the Pontifical Catholic University of Chile and the full curriculum of an MBA specialising in Health.

That sequence explains the path: from micro-operational redesign of clinical processes to applied data science, ministry-level analytics architecture and predictive modelling at national scale. One constant runs through all of it: hunting for the system’s blind spots, the places where patients disappear inside the bureaucracy.