Susan Shortreed, PhD

“By using rich data sources such as electronic health records, we can begin to identify which treatments will work best for which people.”

Susan Shortreed, PhD

Group Health Research Institute Associate Investigator


Susan Shortreed's research brings together statistics and machine learning methods to address health science problems, with a special emphasis on analyzing complex longitudinal data and overcoming missing-data challenges. Much of her methodological work is focused on developing and evaluating statistical inference approaches for observational data, such as data from electronic health care records or from randomized clinical trials with missing information. Dr. Shortreed is also interested in developing new machine learning methods and extending current best-practice methods, specifically for personalized dynamic treatment strategies, clustering, and model selection methods.

Dr. Shortreed earned her PhD in statistics from the University of Washington in 2006. After completing her degree, she spent two years in the Department of Epidemiology and Preventive Medicine at Monash University in Melbourne, Australia, and two years in the School of Computer Science at McGill University. Dr. Shortreed has collaborated with scientists in a broad range of areas including cancer screening, cardiovascular disease, and medication and vaccine safety. Currently, she works most often with researchers in mental and behavioral health, evaluating and comparing treatments for chronic pain, depression, and bipolar disorder, and interventions to prevent alcohol misuse, smoking, and suicide. Dr. Shortreed is an investigator with the Mental Health Research Network, designing studies to address important public health concerns, such as determining which antidepressant medications work best for which patients.

In addition to her GHRI work, Dr. Shortreed is an affiliate associate professor at the University of Washington Biostatistics Department. She serves on the Executive Board for the American Statistical Association’s Section on Statistics in Epidemiology.

Research interests and experience

  • Biostatistics

    Analysis of complex longitudinal data and data collected from electronic health records; methods for overcoming missing data; computational statistics and algorithms; variable selection methods

  • Medication Use & Patient Safety

    Biostatistics; data mining

  • Mental Health

    Biostatistics; treatment for chronic depression and bipolar disorder; suicide prevention; developing personalized dynamic treatment strategies

Recent publications

LeResche L, Saunders K, Dublin S, Thielke S, Merrill JO, Shortreed SM, Campbell C, Von Korff MR. Sex and age differences in global pain status among patients using opioids long term for chronic noncancer pain. J Womens Health (Larchmt). 2015 Jul 8 [Epub ahead of print]. PubMed

Lapham GT, Rubinsky AD, Shortreed SM, Hawkins EJ, Richards J, Williams EC, Berger D, Chavez LJ, Kivlahan DR, Bradley KA. Comparison of provider-documented and patient-reported brief intervention for unhealthy alcohol use in VA outpatients. Drug Alcohol Depend. 2015 May 27. pii: S0376-8716(15)00263-X. doi: 10.1016/j.drugalcdep.2015.05.027. [Epub ahead of print]. PubMed

Saunders K, Shortreed S, Thielke S, Turner JA, LeResche L, Beck R, Von Korff M. Evaluation of health plan interventions to influence chronic opioid therapy prescribing. Clin J Pain. 2015 Jan 23. [Epub ahead of print]. PubMed

Friesen MC, Shortreed SM, Wheeler DC, Burstyn I, Vermeulen R, Pronk A, Colt JS, Baris D, Karagas MR, Schwenn M, Johnson A, Armenti KR, Silverman DT, Yu K. Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies. Ann Occup Hyg. 2014 Dec 3. pii: meu101 [Epub ahead of print]. PubMed