There will be (6) full-day tutorial workshops offered this year at the 2018 OHDSI Symposium in Bethesda, MD; (2) workshops are introductory and (4) are advanced.
Please note that Symposium Registration and Tutorial Workshop Registration are separate. You are not registered for the symposium if you only register for a tutorial and you are not registered for a tutorial if you have only registered for the symposium.
Tutorial Registration is now closed. If you would like to be placed on a wait list, please click on the button below and fill out the wait list form. If you are accepted into the course, you will receive a workshop acceptance ticket via email.
Tutorial Workshop Wait List FormThe (2) introductory tutorial workshops will take place on Thursday, October 11, 2018. There are no prerequisites for the introductory courses; attendance will be on a first-come, first-served basis. Registration is 8am-9am. A buffet lunch will be served and workshops will end at 5pm.
The (2) introductory workshops are:
1) OMOP Common Data Model and Standardized Vocabularies
This workshop is for data holders who want to apply OHDSI’s data standards to their own observational datasets and researchers who want to be aware of OHDSI’s data standards, so they can leverage data in OMOP CDM format for their own research purposes.
Faculty: Christian Reich, Erica A.Voss, Mui Van Zandt, Clair Blacketer, Rimma Belenkaya, Dmytry Dymshyts, Don Torok, Stephen Lyman, Karthik Natarajan
Room: White Oak A, lower level of hotel
2) An Overview of the OHDSI Analysis Ecosystem
This tutorial will discuss the OHDSI analysis ecosystem and showcase the functionality available within the OHDSI methods library and ATLAS for designing and executing analytical use cases for clinical characterization, population-level effect estimation, and patient-level prediction within one institution or across the entire OHDSI network. This workshop is for data holders, researchers, and regulators who want to learn more about the exciting tools developed by the OHDSI community. It is a high-level overview of various topics, doing 30-minute sessions covering principles and implementation for: vocabulary, ACHILLES data characterization, cohort definition, cohort characterization, incidence rate summary, population-level estimation, and patient-level prediction.
Faculty: Patrick Ryan, Kristin Feeney Kostka, Anthony Sena, Greg Klebanov
Room: White Oak B, lower level of hotel
The (4) advanced tutorial workshops will take place on Saturday, October 13, 2018. The workshop prerequisites are listed below under each course. There will be fees charged to guarantee a seat at these advanced courses and there will also be a no fee, waitlist option. Registration is 8am-9am. A buffet lunch will be served and workshops will end at 5pm.
The (4) advanced workshops are:
1)Patient-Level Prediction
This workshop is for researchers who want to design prediction studies for precision medicine and disease interception using the OHDSI tools and programmers who want to implement and execute prediction studies using the OHDSI methods library.
Course prerequisites: knowledge of OMOP CDM and Vocabularies and either 1) epidemiologic knowledge understanding of how to define cohorts or 2) R programming skills.
Faculty: Peter Rijnbeek, Jenna Reps, Seng Chan You, Ross Williams
Room: Forest Glen, lower level of hotel
Participants are encouraged to watch these tutorials from past years in preparation for the tutorial:
CDM tutorial: https://www.ohdsi.org/past-events/2017-tutorials-omop-common-data-model-and-standardized-vocabularies/
Cohort definition: https://www.ohdsi.org/ohdsi-cohort-definition-and-phenotyping-tutorial-recording/
2) Population-level Effect Estimation
This workshop is for researchers who want to design estimation studies for safety surveillance and comparative effectiveness using the OHDSI tools and programmers who want to implement and execute estimation studies using the OHDSI methods library.
Course prerequisites: knowledge of OMOP CDM and Vocabularies and either 1) epidemiologic knowledge understanding of how to define cohorts or 2) R programming skills.
Faculty: Martijn Schuemie, Patrick Ryan, Marc Suchard, Jamie Weaver
Room: Brookside A, lower level of the hotel
Participants are encouraged to watch these tutorials from past years in preparation for the tutorial:
CDM tutorial: https://www.ohdsi.org/past-events/2017-tutorials-omop-common-data-model-and-standardized-vocabularies/
Cohort definition: https://www.ohdsi.org/ohdsi-cohort-definition-and-phenotyping-tutorial-recording/
3) Data Quality
Participants will learn how to understand and use three freely available sets of tools that assess the quality of OMOP v5 data. A conceptual framework for data quality will be presented, followed by hands-on instruction for installing and running all three sets of tools: Achilles Heel; PEDSnet DQA Toolkit; and DQe-c, DQe-v and automated outlier detection. The class will involve running these tools against a real dataset.
Course prerequisites: Participants should know the domains and vocabularies in the OMOP CDM, understand its person-level organization, the way concepts and concept relationships are used to represent local codes in a standardized fashion. Participants should also have at least beginner level R and SQL programming skills.
Faculty: Andrew Williams, Michael Kahn, Vojtech Huser, Hossein Estiri, Hanieh Razzaghi, Connor Callahan, Tim Bergquist, Robert Miller
Room: Glen Echo, lower level of the hotel
Participants are encouraged to watch this tutorial from last year in preparation for the tutorial:
CDM tutorial: https://www.ohdsi.org/past-events/2017-tutorials-omop-common-data-model-and-standardized-vocabularies/
4) Cohort Definition/Phenotyping
This workshop is to develop better approaches for designing and implementing phenotypes, both rule-based heuristics and increasing the use of probabilistic phenotypes. The learning objectives and technical competencies are:
• Learn principles for cohort definition and evaluation
• Develop rule-based heuristics in ATLAS
• Apply cohort definitions to analytical use cases of: disease phenotyping, exposure definition, cohort characterization, effect estimation and prediction.
• Design predictive model-based phenotype evaluation using APHRODITE.
Course prerequisites: knowledge about CDM and vocabulary AND need to know the contents of the patient-level data you are working with. This course is very important and foundational to our ability to conduct all the types of analyses, including clinical characterization, population-level prediction, and patient-level prediction.
Participants are encouraged to have access to their own patient level data, either via direct SQL or through an Atlas installation, for the duration of the tutorial.
Faculty: Chris Knoll, Gowtham Rao, RuiJun (Ray) Chen, Juan Banda, Joel Swerdel
Room: Brookside B, lower level of the hotel
Participants are encouraged to watch this tutorial from last year in preparation for the tutorial:
CDM tutorial: https://www.ohdsi.org/past-events/2017-tutorials-omop-common-data-model-and-standardized-vocabularies/
