Robert Wellman, MS

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“Being part of Kaiser Permanente research teams gives me a chance to develop cutting-edge biostatistical methods while contributing to health care research with a national impact.”

Robert Wellman, MS

Principal Collaborative Biostatistician, Kaiser Permanente Washington Health Research Institute

Biography

A graduate of the University of Washington (UW) biostatistics program, Robert Wellman, MS, joined the Kaiser Permanente Washington Health Research Institute (KPWHRI) Biostatistics Unit in 2009. His work spans a diverse collection of topics including mental health, pharmacoepidemiology, postmarketing drug safety surveillance, obesity, diagnostic test accuracy, back pain, and breast cancer. Prior to this, he spent 5 years in the Biostatistics Core at the UW Center for AIDS Research.

Research interests and experience

  • Biostatistics

    Causal inference; longitudinal data; diagnostic and screening test accuracy; clinical trials; survival analysis: rare disease outcomes; nonparametrics; missing data; electronic data; distributed data; statistical computing

    Vaccines & Infectious Diseases

    Biostatistics; HIV/AIDS; vaccine safety

    Complementary & Integrative Health

    Biostatistics; clinical trials; back pain

    Obesity

    Biostatistics; bariatric surgery

  • Cancer

    Biostatistics; breast cancer; effects of chemotherapy; accuracy of automated data; screening test accuracy; advanced imaging

    Medication Use & Patient Safety

    Biostatistics; pharmacoepidemiology; postmarketing drug safety surveillance; big data; electronic health record and claims data

    Mental Health

    Biostatistics; suicide risk prediction, machine learning

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Recent publications

Coughlin JW, Nauman E, Wellman R, Coley RY, McTigue KM, Coleman KJ, Jones DB, Lewis KH, Tobin JN, Wee CC, Fitzpatrick SL, Desai JR, Murali S, Morrow EH, Rogers AM, Wood GC, Schlundt DG, Apovian CM, Duke MC, McClay JC, Soans R, Nemr R, Williams N, Courcoulas A, Holmes JH, Anau J, Toh S, Sturtevant JL, Horgan CE, Cook AJ, Arterburn DE, PCORnet Bariatric Study Collaborative Preoperative Depression Status and Five Year Metabolic and Bariatric Surgery Outcomes in the PCORnet Bariatric Study Cohort 2023 Apr;277(4):637-646. doi: 10.1097/SLA.0000000000005364. Epub 2022-01-19. PubMed

Shortreed SM, Walker RL, Johnson E, Wellman R, Cruz M, Ziebell R, Coley RY, Yaseen ZS, Dharmarajan S, Penfold RB, Ahmedani BK, Rossom RC, Beck A, Boggs JM, Simon GE Complex modeling with detailed temporal predictors does not improve health records-based suicide risk prediction 2023 Mar 23;6(1):47. doi: 10.1038/s41746-023-00772-4. Epub 2023-03-23. PubMed

Lewis CC, Jones SMW, Wellman R, Sharp AL, Gottlieb LM, Banegas MP, De Marchis E, Steiner JF Social risks and social needs in a health insurance exchange sample: a longitudinal evaluation of utilization 2022 Nov 28;22(1):1430. doi: 10.1186/s12913-022-08740-6. Epub 2022-11-28. PubMed

Coleman KJ, Wellman R, Fitzpatrick SL, Conroy MB, Hlavin C, Lewis KH, Coley RY, McTigue KM, Tobin JN, McBride CL, Desai JR, Clark JM, Toh S, Sturtevant JL, Horgan CE, Duke MC, Williams N, Anau J, Horberg MA, Michalsky MP, Cook AJ, Arterburn DE, Apovian CM, PCORnet Bariatric Study Collaborative Comparative Safety and Effectiveness of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy for Weight Loss and Type 2 Diabetes Across Race and Ethnicity in the PCORnet Bariatric Study Cohort 2022 Oct;157(10):897-906. doi: 10.1001/jamasurg.2022.3714. Epub 2022-08-31. PubMed

Sherman KJ, Wellman RD, Jones SMW, Lewis CC Interest in Mindfulness Training for Chronic Low-Back Pain: Results from a Vignette-driven, Web-based Survey of Patients 2022 Jun;28(6):484-496. doi: 10.1089/jicm.2021.0427. Epub 2022-03-23. PubMed

 

Research

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Acupuncture safe and effective for chronic low back pain in older adults

NIH-funded study finds that acupuncture improves pain, physical functioning.

Research

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Remote programs effective for chronic pain, study finds

Telehealth and online cognitive behavioral therapy could expand treatment options for chronic pain in rural areas.

New findings

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Simpler models to identify suicide risk perform similarly to more complex ones

Models that are easier to explain, use could have better uptake in health care settings.