Events

Upcoming events and seminars

January 15, 2025

Cluster randomized and stepped-wedge trials: design issues and tools

12 to 1 p.m.

Speaker: Mary Ryan Baumann, PhD, (she/her/hers), is an assistant professor of biostatistics at the University of Wisconsin – Madison, with joint appointments in the Department of Population Health Sciences and the Department of Biostatistics and Medical Informatics. She researches both methodological and logistical issues in clustered data analysis and study design, particularly cluster randomized and pragmatic trials. This allows her to help her UW and UW Health colleagues conduct sophisticated health and health services research for Wisconsin and beyond.

Summary
CRTs (cluster randomized trials) and stepped-wedge trials are popular study designs used to answer large-scale, community-based research questions. However, it can be difficult to obtain information to reliably inform design parameters like intracluster correlation. I’ll discuss some recent work documenting the challenges real study teams have faced in designing and analyzing these trials, and several tools I and colleagues have developed to bridge these gaps.

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Past events and Seminars

December 18, 2024

Reducing Sitting in Older Adults: The Healthy Aging Resources to Thrive (HART) Trial

12 to 1 p.m.

The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speakers: Dori Rosenberg, PhD, MPH, (she/her), is a senior investigator at KPWHRI. She conducts clinical trials and epidemiologic research on physical activity and sedentary behavior in older adults and populations with chronic conditions in order to prevent or delay progression of cognitive and functional decline.

Mikael Anne Greenwood-Hickman, MPH, (she/her), is a senior collaborative scientist at KPWHRI. She conducts and supports mixed methods research focused primarily on physical activity and sedentary behavior in older adults and the promotion of healthy cognition and physical function in aging.

Weiwei Zhu, MS, (she/her), is a senior collaborative biostatistician at KPWHRI. Her experience includes observational studies with repeated measurements, randomized controlled trials, and multisite analyses. She has collaborated on research in women's health, cancer, aging and geriatrics, and opioid use.

Andrea Cook, PhD, (she/her), is a senior biostatistics investigator at KPWHRI. She has a primary research focus on developing methods for pragmatic clinical trials, vaccine and drug safety postmarket surveillance, and correlated data.  

Summary
The presentation will describe the Healthy Aging Resources to Thrive trial to examine whether sedentary behavior reduction improves heart health in older adults. It will examine how the trial adapted to the COVID-19 pandemic including being able to do all study activities remotely and statewide to be more inclusive of those living in outlying areas.

December 3, 2024

Incorporating the Patient Voice in Pediatric Oncology Trials

4 to 5 p.m.

The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

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Speaker: Michelle M. Nuño, (she/her/hers). I am an Assistant Professor of Clinical Population and Public Health Sciences in the Division of Biostatistics at the University of Southern California. My methodological work focuses on efficient sampling designs in survival analysis. In particular, I am interested in expanding the use of the nested case-control design, a sampling design often used to reduce data collection costs in rare disease, time-to-event settings. I am also a Senior Statistician at Children’s Oncology Group, where I work on clinical trials in germ cell tumors, late effects and survivorship, cancer care delivery research, and patient-reported outcomes. A large focus of my work recently has been to expand the inclusion of patient-reported outcomes to pediatric oncology trials to learn about the patient’s experience during and after treatment. I believe in mission of the Children’s Oncology Group and am confident that through our work and collaborations, we can improve the lives of children with cancer in the United States and around the world.

Summary
Patient-reported outcomes (PROs) are becoming increasingly important in clinical trials because they provide a unique opportunity to hear directly from the patient. Incorporating PROs improves our understanding of treatment tolerability and the impact of treatment on patients’ quality of life, providing valuable insights essential for improving patient care delivery. In many cases, treatment tolerability may also impact disease outcomes. While the significance of PROs is well recognized, we often encounter challenges related to the design and analysis of studies, particularly in pediatric trials. For example, some children may be too young or too ill to complete PRO measures. Additionally, some PRO measures allow completion by a parent or caregiver proxy. When including PRO endpoints in trials, special consideration should be given to ensure that all required data are collected without placing an excessive burden on patients. We will discuss considerations for the inclusion and analysis of PROs in pediatric oncology trials.

November 20, 2024

Inference for model-agnostic longitudinal variable importance

12 to 1 p.m.

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The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: Brian Williamson, PhD, (he/him/his), is an assistant investigator at KPWHRI; an affiliate assistant professor at the University of Washington; and an affiliate investigator at Fred Hutchinson Cancer Center. He develops statistical methods that enable efficient use of patient data to improve public health and healthcare for everyone.

Summary
In prediction settings where data are collected over time, it is often of interest to understand both the importance of variables for predicting the response at each time point and the importance summarized over the time series. Building on recent advances in estimation and inference for variable importance measures, we define summaries of variable importance trajectories. These measures can be estimated and the same approaches for inference can be applied regardless of the choice of the algorithm(s)

used to estimate the prediction function. We propose a nonparametric efficient estimation and inference procedure as well as a null hypothesis testing procedure that are valid even when complex machine learning tools are used for prediction. Through simulations, we demonstrate that our proposed procedures have good operating characteristics, and we illustrate their use by investigating the longitudinal importance of risk factors for suicide attempt.

October 1, 2024

Nirsevimab Safety: Preliminary Results from the Vaccine Safety Datalink

4 to 5 p.m.

The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: Matthew F. Daley, MD, (he/him), is a Senior Clinician Investigator at the Institute for Health Research. He conducts research on a broad range of pediatric-oriented topics. He is focused particularly on vaccine-related topics, including vaccine safety, vaccination coverage, and parental vaccine hesitancy. Dr. Daley is a practicing pediatrician at Kaiser Permanente Colorado. He is an investigator on the Vaccine Safety Datalink, a national network designed to study the safety of licensed and authorized vaccines. Additionally, he recently completed a term as a member of the Advisory Committee on Immunization Practices (ACIP), which provides advice and guidance to the Centers for Disease Control and Prevention (CDC) on the use of vaccines in the U.S. civilian population.

Summary

• Nirsevimab is a long-acting monoclonal antibody, licensed in 2023 for use in the prevention of lower respiratory tract infections caused by RSV.
• Nirsevimab is recommended for all infants <8 months of age, and certain high-risk infants 8-19 months of age.
• The clinical trials of nirsevimab did not indicate safety concerns; however, additional post-licensure data is needed, for when nisevimab is used during routine care.
• The objective of this study was to investigate the safety of nirsevimab, by examining pre-specified adverse events among nirsevimab recipients in the Vaccine Safety Datalink (VSD).
• The results presented should be considered preliminary, and not for circulation.

September 18, 2024

Understanding the costs to families of caring for a child with a mental health condition: results of the r-Kids study

12 to 1 p.m.

The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: Frances Lynch (she/her), Distinguished Investigator, Center for Health Research at Kaiser Permanente Northwest and the OCHIN network of community health clinics

Summary
This presentation will describe the development of a conceptual model of the economic impacts experienced by families of children with mental health and developmental conditions.  In addition, the presentation will describe the r-Kids study, that used the conceptual framework to estimate the costs to families of over 1400 children.  The r-Kids study included a racially and ethnically diverse sample of families from 4 sites, including families served in public health clinics. 

July 17, 2024

On Being a Black Woman

12 to 12:55 p.m.

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The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: Kanetha Wilson, PhD, is a research associate at Kaiser Permanente, Georgia. Her research focuses on health outcomes at intersections of race, gender, and class. As a Robert Wood Johnson Fellow, her training included rich understandings of health policy and how social determinants of health and contextual factors affect public health. She is a mixed methods sociologist who employs both qualitative and quantitative methodologies for holistic approaches to understanding the health of Black women. She previously led a study on the lived experiences of Black women breast cancer survivors, conducting interviews with women across 3 Southern states. She continues work exploring lived experiences and health for Southern Black women in her current study exploring the role of location on depression/anxiety, blood pressure, and BMI using data from KPGA members. This study uses MLM clustered models and semi-structured interviews to explore the complex interworking of context and health as women navigate being Black in Southeastern America.

Summary
Dr. Wilson will take a mixed methods approach to spotlight how lived experiences of Southern Black women affect physical and mental health outcomes.  She will use data she collected and/or analyzed over the last 10 years to situate the experience of being Black in America.  Mixed in will be a little RWE.

May 7, 2024

How Lived Experience Shapes My Approach to Mental Health Care

12 to 12:55 p.m.

The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: Helene Speyer, MD, PhD, is a psychiatrist and researcher in the Danish health care system, based in Copenhagen, Denmark. In addition to her clinical practice, she does research on the discontinuation, tapering, maintenance, effectiveness, and side effects of antipsychotic drugs; exercise interventions, weight management, lifestyle coaching and mental health; and metabolic and cardiac risk factors and schizophrenia.   

Summary
In this seminar, Dr. Speyer will discuss the personal and theoretical underpinnings of her research on patient-centered mental health treatment, particularly the use of medications for depression, attention-deficit disorders, and psychotic illnesses. She explains how her own health care experiences and her clinical studies motivate her research and approach to working with clients.   

April 2, 2024

Recipes for Natural Language Processing: A Guide to Solving Problems using Clinical Text

12 to 12:55 p.m.

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The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: David Cronkite (he/him), MS, has been a computational linguist at KPWHRI for over 10 years, supporting a number of projects by applying NLP in diverse environments including mental health, marijuana use, COVID-19, neuropathy, and anaphylaxis. He has particular interests in building scalable, portable, and reusable solutions in addition to exploring applications of machine learning in resource constrained environments.

Speaker: Will Bowers (he/him/his), MS, is a computational linguist here at KPWHRI. He leverages natural language processing (NLP), linguistics, and machine learning (ML) to extract information from medical records. Will contributes to various projects at KPWHRI, like Adult Changes in Thought (ACT), FDA’s Sentinel Initiative, and projects studying substance abuse. Will received his Master of Science in Computational Linguistics in 2021, and a Bachelor of Science in Informatics in 2020, both from the University of Washington. He enjoys working in research, and he is interested in pursuing a PhD in computational linguistics, biomedical informatics, or a related field.

Summary
Natural language processing (NLP) is a quickly evolving field that is transforming many aspects of human life. Here at KPWHRI, David Cronkite and Will Bowers are hard at work applying NLP to health research. In this presentation, they will provide an overview of how they leverage NLP to unlock a largely untapped resource – medical records. They will introduce us to what NLP is, how it is uniquely employed at KPWHRI, and provide ideas for future projects that leverage NLP).

February 6, 2024

Robustly estimating heterogeneity in factorial data using Rashomon Partitions

12 to 1 p.m.

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The views expressed in the seminars and events hosted by KPWHRI do not necessarily reflect those of Kaiser Permanente

Speaker: Tyler Harris McCormick (he/him/his) is a Professor of Statistics and Sociology at the University of Washington, where he is also a core faculty member in the Center for Statistics and the Social Sciences.  He is also a Senior Data Science Fellow at the eScience Institute, UW's data science center.  Tyler's work develops statistical models that infer dependence structure in scientific settings where data are sparsely observed or observed subject to error.  His recent projects include estimating features of social networks (e.g. the degree of clustering or how central an individual is) using data from standard surveys, inferring a likely cause of death (when deaths happen outside of hospitals) using reports from surviving caretakers, and quantifying & communicating uncertainty in predictive models for global health policymakers.  He holds a Ph.D. in Statistics (with distinction) from Columbia University and is the recipient of an NIH New Innovator (DP2) Award, NIH Career Development (K01) Award, Army Research Office Young Investigator Program Award, and a Google Faculty Research Award.  Tyler is the former Editor of the Journal of Computational and Graphical Statistics (JCGS) and a Fellow of the American Statistical Association.  More information is available on his website: thmccormick.github.io.

Summary
This presentation will propose an approach to enumerating heterogeneity in the relationship between an outcome and discrete covariates by creating a Rashomon Partitions Set (RPS). Each Rashomon partition consists of the feature combinations that maximize heterogeneity in the outcome space. We construct this by pooling similar feature combinations using priors over pooling patterns in an overarching Bayesian model.  We show that we can characterize the set of Rashomon Partitions in terms of its fraction of the overall posterior and size.  Further, we demonstrate that the RPS is enumerable in meaningful settings by leveraging the insight that many potential combinations of features are, in practice, nonsensical for pooling because they represent different dimensions in the covariate space.  We demonstrate RPS construction in the context of two practical settings: finding heterogeneity in outcomes of a randomized trial and examining racial disparities in health outcomes in a large clinical dataset.  This is joint work with Arun Chandrasekhar (Stanford Economics) and Aparajithan Venkateswaran (UW Statistics).

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