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 M. Shortreed, PhD

Senior Biostatistics Investigator, Kaiser Permanente Washington Health Research Institute
Affiliate Professor, Department of Biostatistics, University of Washington

Susan.M.Shortreed@kp.org
206-287-2088

Curriculum vitae (CV)

Biography

Susan Shortreed, PhD, uses statistics and machine learning methods to address health science problems, with a special emphasis on analyzing complex longitudinal data. She develops and evaluates statistical approaches for observational data, and works to improve the design and analyses of studies that use data collected from electronic health care records. She is leading a project to develop statistical methods for constructing personalized treatment strategies using data captured from electronic health records.

Dr. Shortreed earned her PhD in statistics from the University of Washington. Then 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 in Montreal, Canada. Dr. Shortreed has collaborated with scientists in a broad range of areas including alcohol use, cancer screening, and medication safety. She now works alongside researchers in mental and behavioral health, evaluating and comparing treatments for chronic pain and depression, and interventions to prevent 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 and developing risk prediction algorithms to identify individuals who may be at increased risk for suicidal behavior.

Dr. Shortreed is also an affiliate professor of biostatistics at the University of Washington School of Public Health. She served on the executive board for the American Statistical Association’s Section on Statistics in Epidemiology and the editorial board of the Journal of the Royal Statistical Society, Series C: Applied Statistics.

Research interests and experience

Biostatistics

Design and analysis of studies that use data collected from electronic health records; analysis of complex longitudinal data; methods for constructing personalized treatment strategies, computational statistics and algorithms; machine learning; variable selection methods.

Medication Use & Patient Safety

Biostatistics; machine learning; using data collected from electronic health records to study rare adverse events; opioid safety; medication safety in pregnancy.
Mental Health

Biostatistics; treatment for chronic depression; suicide prevention; developing personalized treatment strategies; developing risk prediction models.

Recent publications

Zheng Y, Corley DA, Doubeni C, Halm E, Shortreed SM, Barlow WE, Zauber A, Tosteson TD, Chubak J. Analyses of preventive care measures with incomplete historical data in electronic medical records: an example from colorectal cancer screening. Ann Appl Stat.14(2), 1030-1044. https://doi.org/10.1214/20-AOAS1342.

Dublin S, Walker RL, Floyd JS, Shortreed SM, Fuller S, Albertson-Junkans LH, Harrington LB, Greenwood-Hickman MA, Green BB, Psaty BM. Renin-angiotensin-aldosterone system inhibitors and COVID-19 infection or hospitalization: a cohort study. medRxiv. 2020:2020.07.06.20120386. doi: 10.1101/2020.07.06.20120386. PubMed

Shortreed SM, Simon GE. Using predictive analytics to improve pragmatic trial design. Clin Trials. 2020 Aug;17(4):394-401. doi: 10.1177/1740774520910367. Epub 2020 Mar 10. PubMed

Richards JE, Shortreed SM, Simon GE, Penfold RB, Glass JE, Ziebell R, Williams EC. Association between patterns of alcohol use and short-term risk of suicide attempt among patients with and without reported suicidal ideation. J Addict Med. 2020 Mar 5. doi: 10.1097/ADM.0000000000000637. [Epub ahead of print]. PubMed

Chen L, Shortreed SM, Easterling T, Cheetham TC, Reynolds K, Avalos LA, Kamineni A, Holt V, Neugebauer R, Akosile M, Nance N, Bider-Canfield Z, Walker RL, Badon SE, Dublin S. Identifying hypertension in pregnancy using electronic medical records: the importance of blood pressure values. Pregnancy Hypertens. 2020 Jan;19:112-118. doi: 10.1016/j.preghy.2020.01.001. Epub 2020 Jan 3. PubMed

Carrell DS, Albertson-Junkans L, Ramaprasan A, Scull G, Mackwood M, Johnson E, Cronkite DJ, Baer A, Hansen K, Green CA, Hazlehurst BL, Janoff SL, Coplan PM, DeVeaugh-Geiss A, Grijalva CG, Liang C, Enger CL, Lange J, Shortreed SM, Von Korff M. Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data. J Drug Assess. 2020 Apr 28;9(1):97-105. doi: 10.1080/21556660.2020.1750419. eCollection 2020. PubMed

Richards JE, Shortreed SM, Simon GE, Penfold RB, Glass JE, Ziebell R, Williams EC. Short-term risk of suicide attempt associated with patterns of patient-reported alcohol use determined by routine AUDIT-C among adults receiving mental healthcare. Gen Hosp Psychiatry. 2020 Jan-Feb;62:79-86. doi: 10.1016/j.genhosppsych.2019.12.002. Epub 2019 Dec 18. PubMed

Simon GE, Shortreed SM, Rossom RC, Penfold RB, Sperl-Hillen JAM, O'Connor P. Principles and procedures for data and safety monitoring in pragmatic clinical trials. Trials. 2019 Dec 9;20(1):690. doi: 10.1186/s13063-019-3869-3. PubMed

Simon GE, Shortreed SM, Johnson E, Rossom RC, Lynch FL, Ziebell R, Penfold ARB. What health records data are required for accurate prediction of suicidal behavior? J Am Med Inform Assoc. 2019 Dec 1;26(12):1458-1465. doi: 10.1093/jamia/ocz136. PubMed

Simon GE, Shortreed SM, Coley RY. Positive predictive values and potential success of suicide prediction models. JAMA Psychiatry. 2019 Jun 26. pii: 2737196. doi: 10.1001/jamapsychiatry.2019.1516. [Epub ahead of print]. PubMed