Advanced Analytics Section

The Advanced Analytics Section is composed of cross-functional team members. These team members have expertise in advanced and innovative analytic methods applied synergistically in health economics, health services research and data science projects to improve care delivery.

Researchers in the Advanced Analytics Section collaborate on a range of investigations, primarily around these areas of discovery:

  • Comparative effectiveness research.
  • Assessing the cost-effectiveness of healthcare interventions.
  • Risk prediction using machine learning.
  • Knowledge synthesis, including systematic literature review and meta-analysis.
  • Pragmatic trial design and methods.

Faculty members in the section provide scientific leadership across investigations supported by the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery. Much of their work aligns with one of these three programs:

Scientists in the Advanced Analytics Section engage in projects designed to improve healthcare delivery at Mayo Clinic and elsewhere. Recent projects include:

  • Evaluating an adult care coordination program on patient activation among patients who are critically ill.
  • Analyzing the cost-effectiveness of ex-vivo lung perfusion among patients undergoing lung transplants.
  • Evaluating a virtual nursing model for patients admitted to general medical hospital units.
  • Conducting a pragmatic trial to analyze an artificial intelligence (AI) algorithm to identify patients with unmet social needs for referral to a community health worker program.
  • Applying AI and machine learning in surgical outcomes, transplant and early-warning systems for infection or critical health events.
  • Treating suicidal thoughts and behaviors in youth.
  • Determining the effects of dietary digestible carbohydrate intakes on risk of cardiovascular disease and type 2 diabetes.
  • Conducting digital-enabled, decentralized trials and cluster-randomized, pragmatic trials to test AI-guided clinical decision support tools.

Faculty members provide regional and national leadership in external communities, including:

  • AcademyHealth, including its Methods and Data Council
  • IEEE Computational Intelligence Society
  • International Society for Pharmacoeconomics and Outcomes Research's Medication Adherence and Persistence Special Interest Group
  • Midwest Comparative Effectiveness Public Advisory Council