CRISP: Clinical Research Intensive Summer Program

What prerequisites are required?

Clinical training and familiarity with medical writing and publications are required because examples are drawn from the medical literature. No prior biostatistical or epidemiologic training is required. The electives do not require any prior experience.

Although it is not required for you to bring your own research projects, if you do, you will have an opportunity to discuss them with experienced clinical investigators and fellow students. Depending on the nature of the projects, you may also have an opportunity to develop them further in your classes.

What is the time commitment?

The program will be held in-person on the Fred Hutch Cancer Center campus from July 7-25, 2025. Lectures are recorded and may be viewed after the class but there is no hybrid option. In-class discussion and engagement are viewed as critical components of the course, as are the interactions with classmates during class breaks, group projects, and social activities. During the course, students should be excused from most clinical responsibilities including clinics, inpatient and consult services, on-call etc. Beepers should be turned off during class. This is an intensive didactic experience with out-of-class assignments and group project meetings. Participants should plan on up to 4 hours of class a day and a similar out-of-class commitment throughout the 3-week period.

Class Schedule

NOTE: Class schedule for 2025 is not yet finalized.

NOTE: Course descriptions below are from CRISP 2024. Updated descriptions for 2025 are coming soon.

Participants will take both Epidemiology and Clinical Biostatistics in the morning.

Introduction to Epidemiology for Clinicians

This course will cover essential epidemiologic concepts, skills, and study designs with a focus on clinical research. Topics include measures of disease frequency and excess risk, overview of study designs, causal inference, screening, measurement error, misclassification, effect modification, and confounding. Students will engage with clinical literature throughout the course, building skills in understanding how and why to incorporate particular epidemiologic methods in clinical settings. Other out of class work includes problem sets that will challenge students to think creatively and critically about epidemiologic methods; computation will be minimal, but students will be pushed to apply concepts quickly and thoughtfully.

In the final week of the course, students will write a proposal describing a research question and related background literature, potential datasets or methods of gathering data, and an analysis plan. Students will receive feedback on their proposals from instructors and through peer review.

Clinical Biostatistics

The course will expose participants to some of the key statistical concepts relating to the analysis of data by using examples from the health sciences literature and example data. The topics will relate to questions such as: How many individuals do I need for my study? Do I have enough data to answer my research question? What is the best design to answer my research question? What criticisms of my study might I be able to anticipate?

For example, lectures will cover:

• basic study designs/approaches (experimental/observational and confirmatory/exploratory)
• basic analysis tools (descriptive stats and graphs including SD vs SE and dependent an independent variables, sample vs population)
• other specific topics: bias, confounding
• hypothesis testing, confidence intervals, power, multiple comparisons
• regression
• other topics depending on literature and data examples

Students will be given datasets so they can learn R programming to illustrate concepts introduced in class. No prior experience with R is required. Students familiar with R will have the opportunity to attempt more advanced problem sets.

NOTE: Course descriptions below are from CRISP 2024. Updated descriptions for 2025 are coming soon.

Participants will choose one of the options below for their afternoon course.

Improving Healthcare Quality and Measuring Outcomes with Epic Data

This course is designed for practicing clinicians and researchers with an interest in incorporating quality improvement (QI) methods in their work. This interactive and challenging course will prepare students to apply the Institute for Healthcare Improvement (IHI) Model for Improvement to the design and execution of a QI project. Students will also learn to use the robust self-service data tools within Epic that allow for measurement of both QI and research interventions. Topics of the session will include an introduction to widely used QI methods, understanding systems and quality drivers, QI and the IRB, developing quality measures, leading QI interventions, extracting data from Epic with Cogito self-service tools, statistical process control methods and software, and publishing QI interventions. Learners are welcome to bring a QI project to develop and kickstart during the course, or may work with hypothetical examples. Learners who complete the homework exercises will qualify for data access at UW Medicine as a Cogito Power User.

Clinician and Patient-Reported Outcomes

Survey course of theory, concepts and methods for assessing health status, signs/symptoms, daily functioning and quality of life outcomes in clinical trials and health research. Topics covered will include: 1) Overview and uses of Clinical Outcome Assessments (COAs); 2) Clinician-Reported Outcomes (ClinROs); 3) Patient-Reported Outcomes (PROs); 4) Observer-Reported Outcomes (ObsROs); 5) Measurement theories and psychometric properties; 6) Instrument development and design; 7) Instrument selection; 8) Interpreting change scores; 9) Instrument modification and cultural adaptation; and 10) Incorporation into clinical care. Out of class exercises will include: Classification of COAs, selecting an appropriate instrument for context of use, generation and crafting of instrument content, instrument scoring, interpretion of instrument change scores, and evaluation of health and quality of life assessments in a clinical trial.

What is the cost of the program?

The cost is $3,000 for the 3-week course, payable to Fred Hutch Cancer Center. It is hoped that tuition will be paid by others (Departments, Divisions, Programs or mentors) rather than by students.  Costs cover instruction, course materials, welcome reception and final celebration, and some lunches.

Tuition is due for accepted applicants by June 1, 2025 to reserve your place in the course.

What does the course application entail?

Applications will be accepted starting November 12, 2024, and students will be notified starting January 13, 2025. Click here to download a PDF preview of the application. Applications sent after January 13th will be considered on a space-available basis. Applicants should also provide the following:

• A C.V.
• A brief personal statement of interest (fewer than 100 words, about 500 characters including spaces)

When will I know if I am selected to participate?

We will review your application and contact you by January 13, 2025 or within the next 2 weeks, whichever is later. Please notify us if you do not hear from us within that time frame. All components of an application are required before it is reviewed. If necessary, a waitlist will be kept in case space opens. The enrollment maximum is 60 because of classroom size.

What other clinical research training opportunities are available?

The table below lists some options and describes how the Clinical Research Intensive Summer Program (CRISP) differs.

Do I get any academic credit or a certificate?

No. This course is not affiliated with the UW or School of Public Health and no academic credit will be given toward a degree. People who finish the course will get a Certificate of Completion.

What will I be asked to do after the course is finished?

Participants also agree to complete a feedback survey at the end of the course to provide critical input to improve the course. We are also interested in measuring the impact of the course on participants and their careers. Students will be asked to let us to contact them for 10 years for the purpose of ascertaining career accomplishments and will provide intermittent CVs or biosketches.

What metrics will be tracked?

We will ask you to provide career data because we expect that participation in this course will result in:

1. Better understanding of applied research methods, measured by perceived self-efficacy in conducting your research projects
2. Greater and more impactful long-term research productivity, measured by publications, grants and academic faculty positions and promotions
3. A desire for more formal training in clinical research methods, measured by the number of students who pursue additional classwork, or MPH or MS degrees

Faculty

Susanne May

Dr. Susanne May is Professor of Biostatistics at the University of Washington (UW) and Director of the UW Clinical Trials Center. She has close to 30 years of experience in providing statistical support for observational studies and clinical trials and/or leading major data and clinical coordinating centers. She has taught a variety of biostatistical classes primarily to non-statisticians. She is a co-author on two biostatistical text books which are both known for their ability to convey complex statistical methodology to non-statistical audiences

Jessie Seiler

Dr. Jessie Seiler (jseiler@uw.edu) is a teaching fellow at the University of Washington School of Public Health. She teaches epidemiologic methods and courses related to structural racism and the social and political determinants of health. Her research focuses on race-based bullying and violence, using both quantitative and qualitative methods, as well as social network analysis tools. In her time at UW, she has been deeply involved with pedagogy design and curriculum planning in the Department of Epidemiology. Dr. Seiler earned her MPH from Emory University’s Rollins School of Public Health and her PhD in Epidemiology from UW’s School of Public Health.

Andrew White

Dr. Andrew White is the director of education at the UW Center for Scholarship in Patient Care Quality and Safety, a Professor of Medicine, and a practicing hospitalist at UWMC. He is also a board-certified Clinical Informaticist and the UW Assistant Chief Medical Information Officer for clinical decision support. His research has focused on communicating with patients after harm, medical reasoning, and using IT to improve safety and value. Dr. White will be joined by a team of colleagues at UW and Seattle Childrens who regularly co-teach classes on Quality Improvement.

Clinical Investigator Lunches

Paul Martin

Dr. Paul Martin is a Professor Emeritus at Fred Hutch and the University of Washington. He has more than 45 years of clinical and research experience in hematopoietic cell transplantation with an emphasis on clinical trials and retrospective studies related to acute and chronic graft-versus-host disease. He served as Medical Director of Clinical Research Support (i.e., the clinical trials office) at Fred Hutch from 2011 to 2017 and is currently the Director of the Pilot Program for the ITHS.

Course Organizer

Stephanie Lee

Dr. Stephanie Lee (sjlee@fredhutch.org) is the Fred Hutch Co-PI for the Institute of Translational Health Sciences (ITHS) and a Professor at Fred Hutch and the University of Washington. She has been an NIH-funded investigator for 25 years and leads the Chronic Graft-vs.-Host Disease (GVHD) Consortium, a multi-center group dedicated to observational and therapeutic studies for this complication of blood and marrow transplantation. She earned her M.P.H. from the Harvard School of Public Health in 1996 after participating in a similar summer program during her hematology-oncology fellowship.

For administrative questions, please contact:

CRISP@fredhutch.org

Everyone was outstanding and I feel so fortunate to have had this amazing teaching team.

I thought the Biostats and Epi instructors were fantastic.

I loved all of the content. I agree with having more dedicated time for R and bringing in slicer dicer for those who did the outcomes elective (which I loved).

Working in small groups to design PROs was very helpful. This hands-on time is high yield.

The formal approach to QI projects was really eye opening. I enjoyed learning some of the more formal methods approaches (SPC, driver diagrams, etc.). Working through the process with individual projects was helpful to grasp the topics.

[Meetings with senior investigators were] Extremely helpful. I was able to utilize their knowledge to understand my research better. Great insight into ways to look further into my data.

These [enrichment lectures] were outstanding and the material was not only relevant to career development but demystified so many things.

They [enrichment lectures] covered a wide range of topics at an appropriate level for fellows/junior faculty and were very engaging and helpful. They gave concrete, actionable advice.

Great that this class is multidisciplinary because it allowed a lot of sharing between departments that does not really happen.

I really enjoyed getting to know the other investigators in this cohort.