Healthcare Predictive Analytics

Course Overview

A practical, data‑driven course that teaches learners how to apply predictive modelling to improve clinical outcomes, operational efficiency, and population health. The course covers healthcare data preparation, risk scoring, early‑warning systems, readmission prediction, utilisation forecasting, machine‑learning techniques, and ethical considerations specific to clinical and patient‑level analytics.

Target Audience

• Healthcare analysts and clinical informatics professionals

• Quality improvement, patient safety, and care management teams

• Hospital operations, nursing leadership, and clinical coordinators

• Public health, insurance, and population health analysts

• Students or professionals entering predictive modelling or health informatics

Course Outcomes

• Understand predictive modelling concepts within clinical and operational contexts

• Prepare and transform healthcare data while meeting privacy and regulatory requirements

• Apply machine‑learning techniques for risk scoring, readmission prediction, and early‑warning alerts

• Use predictive insights to support care pathways, chronic disease management, and resource planning

• Evaluate model performance using healthcare‑appropriate metrics and validation methods

• Identify bias, fairness, and ethical considerations in healthcare predictive models

• Build dashboards to monitor predictive outputs and support clinical decision‑making

• Communicate predictive insights clearly to clinicians, administrators, and leadership teams