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Kathryn L. Colborn, PhD, MSPH
Professional Experience
| 2021 - | Associate Professor, Department of Surgery, University of Colorado School of Medicine |
| 2019 - | Research Director, Surgical Outcomes and Applied Research Program, Department of Surgery, University of Colorado School of Medicine |
| 2019 - | Secondary Faculty, Department of Biostatistics and Informatics, Colorado School of Public Health |
| 2016 - | Co-Director, Data Informatics and Statistics Core, Palliative Care Research Cooperative Group |
| 2019 - 2021 | Assistant Professor, Department of Surgery, University of Colorado School of Medicine |
| 2017 - 2019 | Assistant Professor, Department of Biostatistics and Informatics, Colorado School of Public Health |
| 2015 - 2017 | Assistant Research Professor, Division of Health Care Policy and Research, University of Colorado School of Medicine |
Education and Training
- Postdoctoral Associate, Institute for Disease Modeling (2014)
- PhD, Biostatistics, University of California, Berkeley (2013)
- MSPH, Biostatistics, Tulane University (2005)
- BS, Health and Exercise Science, Colorado State University (2003)
Research and Grants
Publications:
https://www.ncbi.nlm.nih.gov/myncbi/1nGbbI7JMLAAu/bibliography/public/
PI Extramural Grants:
- Automated Surveillance of Postoperative Infections (ASPIN) (08/01/2020-07/31/2025). Agency for Healthcare Research and Quality, R01HS027417 (MPI)
- Identification of postoperative infections using electronic health record and administrative claims data (04/01/18-03/31/20). Agency for Healthcare Research and Quality, R03HS026019
- Development of an automated early warning system for malaria transmission using machine learning (11/01/16-04/29/18). Bill and Melinda Gates Foundation, Grand Challenges Explorations, OPP1161891
Awards:
- National Institutes of Health Loan Repayment Program (2018-2022)
Research Interests
- Infectious Diseases
- Statistical methods for analysis of electronic health records data
- Statistical methods for the development and validation of clinical prediction models
- Surgical outcomes and health services research
- Methodologies for improving rare event classification
- Machine learning and high dimensional model selection
- Design and analysis of cluster-randomized trials