3rd Seattle Symposium on Health Care Data Analytics

Event presentations

• A data science framework for learning health systems Yates Coley (PDF, 1.49MB)
• Computational Health Economics & Outcomes Research Sherri Rose (PDF, 2MB)
• EHR-based Phenotyping in the Presence of Patient-Driven Observation Process Rebecca Hubbard (PDF, 348 KB)
• EQuIP, An Evidence-based Quality Improvement Process: Improving the Speed to Insight Lucy A. Savitz (PDF, 645 KB)
• Improving Health Decisions; A Statistical Call to Arms Scott L. Zeger (PDF, 2.06MB)
• Leveraging the EHR as a platform for real-time predictive models, Part 1 Vincent Liu (PDF, 1MB)
• Leveraging the EHR as a platform for real-time predictive models, Part 2  Vincent Liu (PDF, 2.3MB)
• Leveraging the EHR as a platform for real-time predictive models, Part 3 Vincent Liu (PDF, 1.92MB)
• Measuring actionable social determinants of health to improve health care access Krisda H. Chaiyachati (PDF, 2MB)
• Monitoring Health Behaviors with Sensor Mobile Technology Vadim Zipunnikov (PDF, 2MB)
• New Methodological Approaches for Opioid and Overdose Surveillance Daniel B. Neill (PDF, 1 MB)
• Statistical Challenges in the Design of a Pragmatic Trial of Primary Care-based Treatment for Opioid Use Disorders Jennifer Bobb (PDF, 2 MB)
• Using health care data to study and improve colorectal cancer screening Jessica Chubak (PDF, 2 MB)
• What Data Sources Can Help Learn About Diet, Nutrition, and Chronic Disease Risk Ross L. Prentice (PDF, 424KB)

Learning from health care data to improve patient outcomes and public health

• Agenda & speakers
• Who should attend?
• When & where
• Registration
• Cancellation policy
• Accommodations
• Transportation & parking

The 3rd Seattle Symposium on Health Care Data Analytics will bring together biostatisticians, health informaticists, epidemiologists, and other data scientists to discuss health research and methods that involve large health care databases. Expert speakers will share their research on:

• statistical approaches to learning from electronic health care data;
• methods for precision medicine; and
• health policy.

Experts who are involved in national research initiatives that use large health care databases will discuss methodological challenges encountered in this setting and share ideas for addressing them.

Questions? Please send them to SeattleSymposium@kp.org.

Agenda and speakers

• View symposium program [PDF]
• Meet our speakers, discussants, and instructors [PDF]

Who should attend?

• Scientists who are actively conducting or interested in conducting research on methods for large observational health care databases, including biostatisticians, data scientists, epidemiologists, informaticists, and health services researchers.
• Students, junior researchers, and those new to the field of health care data analytics are especially encouraged to attend! Students may register at a discounted rate (limited availability).

When & where

Short courses (Monday, Oct. 22, 2018) include:

• Targeting learning for data adaptive causal inference in observational and randomized studies. Instructors: Mark van der Laan, PhD, UC Berkeley, and Susan Gruber, PhD, Putnam Data Sciences, 8 a.m.–12:15 p.m.
  Abstract
  

  Data-driven decision making succeeds when data are transformed into reliable, interpretable information. Targeted Learning offers a principled statistical approach utilizing state-of-the-art machine learning to answer questions about health and safety, while still providing statistical inference in terms of confidence intervals and formal testing. The targeted learning framework combines two state-of-the-art methodologies, super learning (SL) for data adaptive machine learning, and targeted minimum loss-based estimation (TMLE) for efficient semi-parametric estimation. The course will motivate the use of targeted learning and provide a comprehensive overview of the framework. Real-world applications will be used to illustrate how targeted learning can be used to answer the kinds of complex questions that arise in practice.

• Data Visualization. Michael Jackson, PhD, Kaiser Permanente Washington Health Research Institute, 2–4 p.m.
  Abstract
  

  Researchers and health care professionals can use well-designed statistical graphics to understand data and to guide viewers toward correct inferences. These graphics can also be powerful tools for communicating study findings. While statistical software makes it easy to produce standard figures, default options often leave much to be desired. The result can be figures that distract, confuse, or even distort data. In this workshop, participants will learn the fundamentals of effective data visualization and how to apply these fundamentals to create their own graphics. We will begin by reviewing general principles for displaying data, enabling viewers to make comparisons and identify trends and correlations. We will then show how to put these principles into practice, creating charts that are appropriate for a given dataset and that effectively use color and annotation. We will also walk through techniques for going beyond the default settings of some software packages to produce well-designed figures.

Symposium
Tuesday, October 23: 8 a.m.–5 p.m.
Wednesday, October 24: 8 a.m.–12:30 p.m.

The symposium will be held at the Hyatt Olive 8 in downtown Seattle. See accommodation information below.

Registration

To register, please visit our online registration page. Space is limited—register today to reserve your spot!

Short Courses:
Short Course #1: Targeting learning for data adaptive casual inference in observational and randomized studies, $325.

Short Course #2: Data Visualization, $225.

Short Course #1 and #2, $500. Registration for the short courses is now open. Symposium registration is required in order to attend the short courses.

Symposium Student registration: $175 (limited availability).

Symposium Standard registration: $350.

Symposium registration fees include a continental breakfast on Monday and Tuesday, as well as lunch on Monday.

Cancellation policy

All cancellation requests need to be made in writing and sent to SeattleSymposium@kp.org. Cancellations received on or before Monday October 15, 2018, will be subject to a full refund. Cancellations made after October 15, 2018, will not be refunded.

Accommodations

Hyatt Olive 8 Seattle
1635 8th Avenue
Seattle, Washington, USA, 98101
Phone: 206-695-1234
Email: seattleolive8.hyatt@hyatt.com

• A limited number of rooms have been reserved at discounted rate of $255 per night. The government rate will be available for government employees (government ID required at check-in).
• You must book by Friday, September 28, 2018, to receive the discount. Space is limited. Please reserve your spot as soon as possible using the Hyatt’s online reservation system, which has been customized for this event.
• If you need help making your reservation, please call the Hyatt at 888-421-1442. (Be sure to mention that you are attending the Kaiser Permanente Washington Health Research Institute Symposium.)

Transportation & parking

From Seattle-Tacoma International Airport (Sea-Tac):

• Estimated taxi fare is $55 (one way) from airport to hotel.
• Shuttle Express: The estimated fee is $18 (one way, shared shuttle service) and a reservation is required.
• SoundTransit Link light rail from Sea-Tac to downtown Seattle: The fee is $3 and the train runs every 10–15 minutes. The closest stop to the Hyatt Olive 8 is Westlake Station (about a quarter mile walk from the station to the hotel).

The Hyatt Olive 8 offers easy valet parking at a rate of $55 per night (tax included). Guests have in-and-out privileges, so you can come and go as you please.

View map and driving directions on the hotel website.

explore Seattle

Our conference hotel is located in the heart of downtown Seattle. Check out VisitSeattle.org or the hotel’s activities page to find dining, shopping, and attractions to enjoy while visiting.

child care resources

• Child Care Resources of King County offers referral services in six languages, including Spanish. By phone: 1-877-543-0059.
• Care.com can connect you to babysitters, nannies, child care centers, special needs caregivers, and more. By phone: 1-877-227-3115.