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 associate 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.
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.
Biostatistics; machine learning; using data collected from electronic health records to study rare adverse events; opioid safety; medication safety in pregnancy.
Biostatistics; treatment for chronic depression; suicide prevention; developing personalized treatment strategies; developing risk prediction models.
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 3;19:112-118. doi: 10.1016/j.preghy.2020.01.001. [Epub ahead of print]. 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;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 Sep 16. pii: 5570544. doi: 10.1093/jamia/ocz136. [Epub ahead of print]. 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
Simon GE, Shortreed SM, Coley RY, Penfold RB, Rossom RC, Waitzfelder BE, Sanchez K, Lynch FL. Assessing and minimizing re-identification risk in research data derived from health care records. eGEMS (Wash DC). 2019;7(1):6. doi: 10.5334/egems.270. PubMed
Shortreed SM, Cook AJ, Coley RY, Bobb JF, Nelson JC. Challenges and opportunities for using big health care data to advance medical science and public health. Am J Epidemiol. 2019 May 1;188(5):851-861. doi: 10.1093/aje/kwy292. PubMed
Shortreed SM, Rutter CM, Cook AJ, Simon GE. Improving pragmatic clinical trial design using real-world data. Clin Trials. 2019 Jun; 16(3):273-282. PubMed
Simon GE, Yarborough BJ, Rossom RC, Lawrence JM, Lynch FL, Waitzfelder BE, Ahmedani BK, Shortreed SM. Self-reported suicidal ideation as a predictor of suicidal behavior among outpatients with diagnoses of psychotic disorders. Psychiatr Serv. 2018 Dec 10:appips201800381. doi: 10.1176/appi.ps.201800381. [Epub ahead of print]. PubMed
Chen L, Pocobelli G, Yu O, Shortreed SM, Osmundson SS, Fuller S, Wartko PD, McCulloch D, Warwick S, Newton KM, Dublin S. Early pregnancy hemoglobin A1C and pregnancy outcomes: a population-based study. Am J Perinatol. 2018 Nov 30. doi: 10.1055/s-0038-1675619. [Epub ahead of print]. PubMed
The honor underscores the institute’s commitment to a work environment that fosters employees’ growth.
A love of problem-solving, math, and health science drive Dr. Shortreed’s work for better mental health treatment.
Dr. David Arterburn discusses reassuring news from his PCORnet study of the most widely used anti-obesity drug in the United States.
Dr. Cara Lewis reflects on using implementation science to integrate patient-reported symptoms into behavioral health care.