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.  Students will be prepared for careers as consultants, analysts, or managers in the healthcare industry, or in any industry or career that relies on data for making important business decisions.

    Application Timeline:

    • View project descriptions here.
    • Watch a recording of the October 30th information webinar here.
    • The application will open following the October 30th webinar. First-round applications are due Tuesday, November 7 at 11:59pm.
    • Students will be notified of acceptance by Friday, November 10.

    Students are welcome to send questions to

  • Prerequisites

    Students may take this course and Bus 40206 (Healthcare Business Analytics) either concurrently or sequentially in any order.  These courses are organized similarly to typical college-level science courses, with both a lecture component (Bus 40206) and a lab component (Bus 40721).   Thus, students who take both receive the complete educational experience, but students may also choose to take only one.  Students in Bus 40206 receive foundational learning in the healthcare industry through the lens of business analyses using data, as well as training in conducting business analyses in an interface that does not require prior coding or data analysis experience. Students in both courses use Data Science Studio (DSS) by Dataiku, while students who take Bus 40721 also use Tableau to create data visualizations.

    Students who choose to take Bus 40721 without having had Bus 40206 will need to complete trainings in both DSS and Tableau.  Typically, teams include at least some members who have taken Bus 40206, and thus they are able to share any material from that course that is directly relevant to the project with other team members.  Students who choose to take Bus 40206 without taking Bus 40721 will not benefit from reinforcing and applying their learnings to a real-world project and sponsor. Students who take both courses will benefit from having a broad understanding of how business analyses are conducted in the healthcare industry, and how their lab project fits into the broader industry landscape.   They will be fully prepared to conduct business analyses in the healthcare industry from day one of employment as a consultant, analyst, or manager. 

    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.   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

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

    • Mandatory attendance week 1

    • Allow Provisional Grades (For joint degree and non-Booth students only)

    • No auditors

    • No pass/fail grades

  • Syllabus
  • Winter 2024Section: 40721-01W 8:30AM-11:30AMBooth 455 (NBC Tower)132In-Person Only
Description and/or course criteria last updated: November 2 2023