1. CDM and Vocabulary | ||
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Aim | - Learning the history of OMOP and OHDSI - Understanding of OMOP-CDM structure - Learning how to find codes and concepts |
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Educator | Chungsoo Kim (Ajou University School of Medicine) | |
Participant preparation | Personal laptop (Chrome browser must be installed) | |
Schedule | Time | Content |
10:00-11:00 | Introduction: History of OMOP and OHDSI | |
11:00-11:15 | Break | |
11:15-12:00 | Vocabulary 1 – Basic relationships | |
12:00-13:00 | Lunch | |
13:00-14:30 | Vocabulary 2 – Hierarchy Exercise SQL example | |
14:30-14:45 | Break | |
14:45-16:00 | OMOP-CDM table structure |
2. Phenotyping by ATLAS | ||
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Aim | - Learning cohort definition and phenotyping using ATLAS - Learning how to make the cohorts using ATLAS |
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Educator | Jaehyeong Cho (Ajou University School of Medicine) | |
Participant preparation | Personal laptop (Chrome browser must be installed) | |
Schedule | Time | Content |
10:00-10:50 | Phenotyping using the common data model (Overview) | |
10:50-11:00 | Break | |
11:00-12:00 | Student exercise (Activity) | |
12:00-13:00 | Lunch | |
13:00-16:00 | ATLAS walkthrough: vocabulary searching, concept set creation, cohort definitions (Rule-based phenotyping in ATLAS) |
1. Population Level Estimation (PLE) | ||
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Aim | - Planning and executing the comparative effectiveness study using OHDSI tools - Creating and exercising new-user comparative cohort using propensity score |
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Educator | Seng Chan You (Ajou University School of Medicine) | |
Participant preparation | Personal laptop (Chrome browser must be installed) | |
Course prerequisites | - Knowledge for OMOP-CDM structure and vocabulary - Epidemiologic knowledge or medical research experience - R programing skill |
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Educational content | Time | Content |
09:00-10:30 | Observational study design (in English) – Patrick Ryan | |
10:30-12:30 | Dissecting cohort study (in English) – Martijn Schuemie | |
12:30-13:15 | Lunch | |
13:15-17:00 | Exercise (in Korean) – Seng Chan You |
2. Patient Level Prediction (PLP) | ||
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Aim |
- Learning the design of PLP studies for precision medicine and disease intercept - Making the PLP studies using ATLAS - Executing PLP studies in R |
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Educator | Youjin Park (Ajou University School of Medicine) | |
Participant preparation | Personal laptop (Chrome browser must be installed) | |
Course prerequisites | - Knowledge of OMOP-CDM and vocabularies - Understanding how to define cohorts using ATLAS - R programming skills |
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Educational content | Time | Content |
09:00-10:00 (60min) | Presentation: What is Patient-Level Prediction? | |
10:00-10:45 (45min) | Exercise: Selection of prediction problem | |
10:45-11:00 (15min) | Break | |
11:00-12:00 (60min) | Presentation: Learning the OHDSI Patient-Level Prediction Framework | |
12:00-12:30 (30min) | Presentation: Introduce Patient-Level prediction studies at the OHDSI consortium | |
12:30-13:15 (45min) | Lunch | |
13:15-14:15 (60min) | Guided tour through implementing Patient-Level Prediction | |
14:15-14:30 (15min) | Break | |
14:30-16:30 (120min) | Exercise: Design and implement your own Patient-Level Prediction | |
16:30-17:00 (30min) | Present the result of your own Patient-Level Prediction |