Yates Coley, PhD, is a biostatistician whose research promotes predictive analytics and learning health systems as a way to improve value and quality in health care delivery. Her statistical research focuses on developing clinical prediction models that are accurate, actionable, and fair. This work spans several statistical domains including repeated measurements, missing data, and machine learning.
Dr. Coley is currently a scholar with the CATALyST K12 Washington Learning Health System Program funded by the Agency for Healthcare Research and Quality and the Patient-Centered Outcomes Research Institute. As part of her training in learning health system research, Dr. Coley is studying current barriers to implementing evidence-based predictive analytics tools to help develop prediction tools that can be deployed and sustained in clinical care. Her research plan also focuses on statistical methods to address racial bias in clinical prediction algorithms.
Before starting as an assistant investigator at Kaiser Permanente Washington Health Research Institute (KPWHRI) in 2016, Dr. Coley was a postdoctoral research fellow at Johns Hopkins Bloomberg School of Public Health. There, she worked with urologists to develop a prediction model that enables personalized management of low-risk prostate cancer. She designed an interactive decision support tool that calculates and communicates patients’ predictions in real-time and is currently building the statistical structure necessary to support a continuously learning model. The resulting prediction tool will be integrated into the clinical workflow so that new observations will be automatically incorporated into the existing model, improving both patient-level predictions as well as researchers’ understanding of risk in the population.
Dr. Coley completed her PhD in biostatistics at the University of Washington. Her dissertation research proposed methods to improve effectiveness estimates in HIV prevention trials by accounting for unobserved variability in risk.
At KPWHRI, Dr. Coley collaborates on projects across a range of research areas including mental health, breast cancer imaging, bariatric surgery, and health services.
Bayesian analysis, causal inference, data visualization, hierarchical models, longitudinal data analysis, missing data, prediction, survival analysis
Suicide risk, depression treatment, measurement-based care, antipsychotic use in adolescents
Biostatistics, prostate cancer, risk stratification, stakeholder engagement, surveillance
Biostatistics, data visualization, interactive decision-support tools, learning health systems, stakeholder engagement
Biostatistics, clinical decision-support, learning health systems, patient-centeredness, shared decision-making, stakeholder engagement
Coley RY, Zeger SL, Mamawala M, Pienta KJ, Carter HB. Prediction of the pathologic Gleason score to inform a personalized management program for prostate cancer. Eur Urol. 2016 Aug 11. pii: S0302-2838(16)30472-9. doi: 10.1016/j.eururo.2016.08.005 [Epub ahead of print]. PubMed
Coley RY, Brown ER. Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model. Stat Med. 2016 Jul 10;35(15):2609-34. doi: 10.1002/sim.6884. Epub 2016 Feb 11. PubMed
Murnane PM, Coley RY, Baeten JM. Response to: every good randomization deserves observation. Am J Epidemiol.
Murnane PM, Brown ER, Donnell D, Coley RY, Mugo N, Mujugira A, Celum C, Baeten JM; Partners PrEP Study Team. Estimating efficacy in a randomized trial with product nonadherence application of multiple methods to a trial of preexposure prophylaxis for HIV prevention. Am J Epidemiol. 2015 Nov 15;182(10):848-56. doi: 10.1093/aje/kwv202. Epub 2015 Oct 19. PubMed
Farjo N, Turpin DL, Coley RY, Feng J. Characteristics and fate of orthodontic articles submitted for publication: An exploratory study of the American Journal of Orthodontics and Dentofacial Orthopedics. Am J Orthod Dentofacial Orthop. 2015 Jun;147(6):680-90. doi: 10.1016/j.ajodo.2015.01.020. PubMed
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