Outcomes Research Fellowship

A unique opportunity for a researcher from an MPOG participating site to join MPOG for a one-year fellowship. The fellowship will allow the selected candidate to use the MPOG platform to transform real-world data into actionable knowledge. Applications are accepted each year in October.

About

The Multicenter Perioperative Outcomes Group (MPOG) is accepting applications from active MPOG member centers for the one‑year MPOG Outcomes Research Fellowship. As a leader in perioperative research, performance improvement, and digital innovation, MPOG provides fellows with a uniquely rich, mentored educational experience.

Fellows may select one of two training pathways:

  • Onsite Fellowship at the MPOG Coordinating Center, University of Michigan (Ann Arbor, MI)

  • Hybrid Fellowship, allowing fellows to remain at their home MPOG member institution

All fellows must dedicate at least 50% non‑clinical time to fellowship activities. The curriculum includes monthly MPOG didactics led by faculty from the Coordinating Center and participating sites, along with hands‑on experience in perioperative data science, quality improvement, and collaborative research.

Learning Objectives

Research Informatics

  • Gain experience working with major electronic health record (EHR) ontologies such as ICD and CPT.
  • Understand common data models used to store and harmonize EHR data, including MPOG and OMOP.
  • Learn the full MPOG data onboarding process, including: Data extract infrastructure, clinical content mapping, and data validation workflows
  • Data diagnostics and quality assurance
  • Evaluate methods for patient matching across diverse data sources (MPOG, surgical registries, claims datasets).
  • Understand differential privacy risks and how data type and granularity influence research limitations.
  • Develop computed research phenotypes derived from EHR data.

Large Dataset Analyses

  • Identify research questions that are appropriate for observational data analysis.

  • Recognize research questions that should not be addressed using observational methods due to bias, confounding, or feasibility limitations.

  • Understand the significance of missing data, including mechanisms (MCAR, MAR, MNAR) and available handling strategies.

  • Apply physiological monitoring artifact reduction techniques to improve data quality.

  • Identify strengths and weaknesses of complementary perioperative large datasets (registries, claims, device data, etc.).

  • Apply appropriate research reporting frameworks, including: STROBE (observational studies), RECORD (EHR‑based observational studies), and CONSORT (randomized trials)

  • Compare advantages and disadvantages of major statistical analysis techniques used in perioperative outcomes research.

Performance Measure and Improvement

  • Understand the Delphi process for developing quality metrics and building consensus across a national collaborative.
  • Gain familiarity with SQUIRE guidelines for reporting healthcare improvement initiatives.

The Project

The fellowship applicant may choose to emphasize one of these aspects (Informatics, Large dataset analysis, or Performance measurement). All fellows will engage in a Practicum Capstone Project, executing an MPOG- based clinical research project or quality metric development feasible using solely the MPOG standardized data file*.

To achieve these learning objectives, MPOG fellows will actively participate in several MPOG activities, including but not limited to: site onboarding, quality metric development and validation, research phenotype development and validation, scientific facilitation, statistical analysis design, and manuscript preparation.

*Note: For 2026-2027 Fellowship applicants, see important guidance about SDF data here.

Apply

Required qualifications:

  • Valid immigration status and work authorization at an MPOG participating site before your expected start date
  • Completion of medical doctorate degree (MD, MBBS, MBChB, or equivalent)
  • Minimum 50% protected non-clinical time devoted to fellowship (documentation by chair required)
  • Identification and letter of support from a faculty mentor at the applicant’s local MPOG center
    • Note: The letter should clearly outline the faculty mentor’s time commitment to support the applicant during the project.

Preferred qualifications:

  • Postgraduate training in anesthesiology or surgical residency
  • Experience with observational dataset analysis for research or quality improvement
  • Coursework in epidemiology or clinical research

Salary:

  • Salary support and professional development funding sources will vary based upon hybrid vs onsite pathway. Fellows may choose to apply concurrently to the University of Michigan NIH T32 Post-Doctoral training program.

Application process:

The application cycle for the 2026-2027 fellowship year is now closed. Please contact mpog-research@med.umich.edu with any questions.

Your application packet should include:

    • Cover letter
    • Current CV
    • Letters of support
      • This should be distinct from a letter of recommendation
      • 50% protected time should be explicitly stated in letter from Department Chair
    • 1-page research plan (analogous to NIH-style Specific Aims page)
    • 1-page training plan (analogous to K/IARS/FAER Training Plan)

View an example application packet here.
Additional Application Instructions
Frequently Asked Questions

For any inquiries please email

mpog-research@med.umich.edu