This class is an introduction to decision analysis and cost-effectiveness analysis; it provides a global introduction to the theory, techniques, and practical issues surrounding model development for health economic analysis, with a focus on development and testing of decision trees. Other topics include systematic review, meta-analysis, health status measurement with utilities, budget impact modeling, and quality assessment of health economic models. The class consists of interactive didactic lectures supported by hands-on laboratories and reading assignments to become familiar with decision analysis software. 


Digital health is a broad term that encompasses use of digital devices and platforms, including electronic health records (EHRs), patient-provider portals, mobile health (mHealth) applications, and wearable biosensors to improve the process and outcomes of healthcare delivery. In this course, we will explore how digital interventions are being employed to drive clinical decisions and offer value to healthcare organizations, their patients, and their staff. 


The goal of the capstone project is to demonstrate skills learned in year 1 in an applied setting within Cedars-Sinai. Specifically, this included the following course objectives:

  1. Demonstrate proficiency in applying HDS academic theory into pragmatic, applied problem solving.
  2. Appreciate how HDS requires leadership, team science, shared decision-making among diverse stakeholders and strong interpersonal communication skills.
  3. Demonstrate proficiency in the mechanics of American healthcare financing.
  4. Utilize scientific methods to solve HDS and quality improvement problems including hypothesis generation, literature search and approaches to data collection, visualization, and analysis.
  5. Become proficient in oral and written communication of HDS analyses and results, learning how to tell a story with data in a way that engages stakeholders and ultimately leads to improved healthcare delivery.