Susan Shortreed, PhD

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“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

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 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.

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

Simon GE, Shortreed SM, Johnson E, Beck A, Coleman KJ, Rossom RC, Whiteside US, Operskalski BH, Penfold RB. Between-visit changes in suicidal ideation and risk of subsequent suicide attempt. Depress Anxiety. 2017 Sep;34(9):794-800. doi: 10.1002/da.22623. Epub 2017 Apr 25. PubMed

Williams EC, Lapham GT, Bobb JF, Rubinsky AD, Catz SL, Shortreed SM, Bensley KM, Bradley KA. Documented brief intervention not associated with resolution of unhealthy alcohol use one year later among VA patients living with HIV. J Subst Abuse Treat. 2017 Jul;78:8-14. doi: 10.1016/j.jsat.2017.04.006. Epub 2017 Apr 13. PubMed

Penfold RB, Stewart C, Simon GE, Shortreed SM, Johnson E, Rossom RC, Operskalski B, Beck A. Antidepressant use by youth with minimal or mild depression: evidence from 3 health systems. Pediatr Qual Saf. 2017;2(2). pii: e017. Epub 2017 Mar 22. PubMed

Von Korff M, Shortreed SM, LeResche L, Saunders K, Thielke S, Thakral M, Rosenberg D, Turner JA. A longitudinal study of depression among middle-aged and senior patients initiating chronic opioid therapy. J Affect Disord. 2017;211:136-143. doi: 10.1016/j.jad.2016.12.052. Epub 2017 Jan 6. PubMed

Shortreed SM, Ertefaie A. Outcome-adaptive lasso: variable selection for causal inference. Biometrics. 2017 Mar 8. doi: 10.1111/biom.12679. [Epub ahead of print]. PubMed

Williams EC, Lapham GT, Shortreed SM, Rubinsky AD, Bobb JF, Bensley KM, Catz SL, Richards JE, Bradley KA. Among patients with unhealthy alcohol use, those with HIV are less likely than those without to receive evidence-based alcohol-related care: a national VA study. Drug Alcohol Depend. 2017 May 1;174:113-120. doi: 10.1016/j.drugalcdep.2017.01.018. Epub 2017 Mar 6. PubMed

Hanuese S, Shortreed SM. On the use of electronic health records for comparative effectiveness research. In: Gatsonis C, Morton SC, editors. Methods for Comparative effectiveness research. CRC Press

Hansen RN, Walker RL, Shortreed SM, Dublin S, Saunders K, Ludman EJ, Von Korff M. Impact of an opioid risk reduction initiative on motor vehicle crash risk among chronic opioid therapy patients. Pharmacoepidemiol Drug Saf. 2016 Nov 14. doi: 10.1002/pds.4130. [Epub ahead of print]. PubMed

Turner JA, Shortreed SM, Saunders KW, LeResche L, Thielke S, Von Korff M. Does association of opioid use with pain and function differ by fibromyalgia or widespread pain status? Pain. 2016 Oct;157(10):2208-16. doi: 10.1097/j.pain.0000000000000631.

Shortreed SM, Johnson EJ, Rutter CM, Kamineni A, Wernli KJ, Chubak J. Cohort restriction based on prior enrollment: Examining potential biases in estimating cancer and mortality risk. Obs Stud. 2016 Aug;2:51-64. Epub 2016 Sep 26. PubMed

 

Research

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New findings on treating hypertension in pregnancy

A study led by Dr. Sascha Dublin finds similar outcomes for 3 hypertension medications, filling an evidence gap.

COVID-19

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Greater infection risks linked to COVID-19 disparities

New work by Susan Shortreed, PhD, finds infection risks drive worse outcomes for some racial and ethnic groups.

Drugs, diabetes, disparities

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Studying COVID-19 risk and outcomes

Dr. Sascha Dublin tells how studies of KP electronic health record data can improve COVID-19 treatment and prevention.

news

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Mentorship awards go to Jane Anau and Dr. Jessica Chubak

The honor underscores the institute’s commitment to a work environment that fosters employees’ growth.