Course Detail

Healthcare Analytics Lab (40721)

Course Description by Faculty

  • Adelman, Dan
  • Content
    The healthcare industry is now undergoing a transformation as data analysis is being rapidly deployed to improve clinical, operational, and financial outcomes. The Healthcare Analytics Laboratory will focus on applying data-driven analytics and insights to identify and create healthcare delivery efficiencies. Student teams will work on real-world improvement projects with prominent healthcare institutions.

    The Laboratory provides students with opportunities to:

    1. Apply and reinforce tools and frameworks developed elsewhere in the Booth curriculum

    2. Develop leadership skills and build effectiveness in teams;

    3. Learn a healthcare context deeply through an intensive project experience

    4. Develop proficiency at presenting data analyses to executive audiences

    5. Impact real-world healthcare delivery.

    Thus, the course will help students develop the skills required to successfully deliver evidence-based management analytics in the real world. Projects will be carefully scoped, and most data will be acquired, before the course begins so that students can make steady progress towards clear, attainable goals. Students will present milestones every two weeks to the instructional team (which consists of the faculty instructor and graduate students who serve as project mentors) and, on occasion, to the entire class. Final presentations will be delivered to hospital executives and physician leaders.

    The course is for students interested in leveraging the academic rigor of data and decision analysis to improve healthcare delivery. It is an excellent course for those interested in careers in or related to the healthcare industry, and business analytics more broadly.

    Project Descriptions for 2022

    Students are welcome to send questions to

  • Prerequisites

    Students will receive substantial coaching support and feedback around projects, but they will not receive direct classroom instruction on the healthcare industry or working with healthcare data. For these, students are strongly encouraged to enroll in Bus 40206 (Healthcare Business Analytics) prior to taking the Lab. Taking this class will help you to make better use of your time in the Laboratory and assist you in meeting your personal learning objectives. Students who have previously taken Bus 40206 will be given priority for admittance into the Lab.

    Depending on the project students are assigned to, other courses may be helpful. Some projects require only basic statistics, but others require more advanced statistics at the level of Bus 41201 (Big Data), Bus 41100 (Applied Regression Analysis), or Bus 41204 (Machine Learning). For some projects, it is helpful to have a background in operations management (Bus 40000) and/or cost accounting (Bus 30001). Occasionally, a project uses concepts covered in Bus 36106 (Managerial Decision Modeling). Programming experience at the level of Bus 32100 (Data Analysis in R and Python) is helpful but not required.

    Any of these courses can be taken concurrently with the Lab. While students having background in the courses relevant to a project will be given priority for admittance into the Lab, not every student is required to have all of these recommended pre/co-requisites. Teams will be comprised of members having a variety of complementary skills and backgrounds.

    Students should also be prepared to work collaboratively within a highly energized, self-managed work team, and be interested in developing their personal skills around team and individual behavior.

    • Application-based course

  • Materials
    Students will work with real-world healthcare data that is protected by HIPAA and confidential to sponsors, on a secure, private server housed at Chicago Booth. As such, students will receive training and certification in HIPAA as part of their first class assignment.
  • Grades

    Evaluation Criteria: project deliverables, presentations, participation in project teams and engagement in the class sessions, written assignments. Students typically spend 8-12 hours per week on their projects

    Enrollment is closed for the Winter 2022 course.

    Cannot take pass/fail. No auditors. Provisional grades will be given to graduating students.

    • Mandatory attendance week 1

    • No auditors

    • No pass/fail grades

  • Syllabus
  • Winter 2022Section: 40721-01W 8:30AM-11:30AMHarper CenterC06In-Person Only
Description and/or course criteria last updated: January 20 2022