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.
Dublin S, Idu A, Avalos LA, Cheetham TC, Easterling TR, Chen L, Holt VL, Nance N, Bider-Canfield Z, Neugebauer RS, Reynolds K, Badon SE, Shortreed SM. Maternal and neonatal outcomes of antihypertensive treatment in pregnancy: a retrospective cohort study. PLoS One. 2022 May 16;17(5):e0268284. doi: 10.1371/journal.pone.0268284. eCollection 2022. PubMed
Simon GE, Shortreed SM, Rossom RC, Beck A, Clarke GN, Whiteside U, Richards JE, Penfold RB, Boggs JM, Smith J. Effect of offering care management or online dialectical behavior therapy skills training vs usual care on self-harm among adult outpatients with suicidal ideation: a randomized clinical trial. JAMA. 2022;327(7):630-638. doi: 10.1001/jama.2022.0423. PubMed
Walker RL, Shortreed SM, Ziebell RA, Johnson E, Boggs JM, Lynch FL, Daida YG, Ahmedani BK, Rossom R, Coleman KJ, Simon GE. Evaluation of electronic health record-based suicide risk prediction models on contemporary data. Appl Clin Inform. 2021;12(4):778-787. doi: 10.1055/s-0041-1733908. Epub 2021 Aug 18. PubMed
Simon GE, Shortreed SM, DeBar LL. Zelen design clinical trials: why, when, and how. Trials. 2021;22(1):541. doi: 10.1186/s13063-021-05517-w. PubMed
Penfold RB, Whiteside U, Johnson EE, Stewart CC, Oliver MM, Shortreed SM, Beck A, Coleman KJ, Rossom RC, Lawrence JM, Simon GE. Utility of item 9 of the patient health questionnaire in the prospective identification of adolescents at risk of suicide attempt. Suicide Life Threat Behav. 2021 Jul 31. doi: 10.1111/sltb.12751. [Epub ahead of print]. PubMed
Penfold RB, Johnson E, Shortreed SM, Ziebell RA, Lynch FL, Clarke GN, Coleman KJ, Waitzfelder BE, Beck AL, Rossom RC, Ahmedani BK, Simon GE. Predicting suicide attempts and suicide deaths among adolescents following outpatient visits. J Affect Disord. 2021 Jul 1;294:39-47. doi: 10.1016/j.jad.2021.06.057. [Epub ahead of print]. PubMed
Coley RY, Walker RL, Cruz M, Simon GE, Shortreed SM. Clinical risk prediction models and informative cluster size: assessing the performance of a suicide risk prediction algorithm. Biom J. 2021 Oct;63(7):1375-1388. doi: 10.1002/bimj.202000199. Epub 2021 May 24. PubMed
Coley RY, Johnson E, Simon GE, Cruz M, Shortreed SM. Racial/ethnic disparities in the performance of prediction models for death by suicide after mental health visits. JAMA Psychiatry. 2021 Apr 28:e210493. doi: 10.1001/jamapsychiatry.2021.0493. [Epub ahead of print]. PubMed
Simon GE, Matarazzo BB, Walsh CG, Smoller JW, Boudreaux ED, Yarborough BJH, Shortreed SM, Coley RY, Ahmedani BK, Doshi RP, Harris LI, Schoenbaum M. Reconciling statistical and clinicians' predictions of suicide risk. Psychiatr Serv. 2021 Mar 11:appips202000214. doi: 10.1176/appi.ps.202000214. [Epub ahead of print]. PubMed
Coulombe J, Moodie EEM, Shortreed SM, Renoux C. Can the risk of severe depression-related outcomes be reduced by tailoring the antidepressant therapy to patient characteristics? Am J Epidemiol. 2020 Dec 9:kwaa260. doi: 10.1093/aje/kwaa260. [Epub ahead of print]. PubMed
A study led by Dr. Sascha Dublin finds similar outcomes for 3 hypertension medications, filling an evidence gap.
New work by Susan Shortreed, PhD, finds infection risks drive worse outcomes for some racial and ethnic groups.
Dr. Sascha Dublin tells how studies of KP electronic health record data can improve COVID-19 treatment and prevention.
The honor underscores the institute’s commitment to a work environment that fosters employees’ growth.