MedInfo - program

SESSION 305: <br/>Information and knowledge management

Track 6

Monday, July 10, 2023

11:00 AM - 12:30 PM

C4.5

Overview

C4.5
Panels

Details

This session contains two 40 minute panels.

Panel: Motivation and challenge to standardise healthcare data across the world: OHDSI network

This panel includes OHDSI data network members from around the world, representing four diverse geographic regions, Asia, Australia, Europe, and the US. The panelists will discuss the motivation to join the network, the challenges to convert data to the model, issues around data quality, and vocabulary standardisation in their region. The panelists will discuss their experience in utilising these data to execute network studies to collaboratively generate real-world evidence to support health-care decision making throughout the lifecycle of medicinal products. Lastly, panelists will discuss the lessons learned in being part of the OHDSI data network and community and their perspectives on creating a sustainable data-ecosystem for research.

Panel: Standardised representations of systemic anticancer therapy regimens as an enabler of real-world evidence synthesis

Systemic anticancer therapy (SACT) regimens are complex, varied, and poorly represented in most electronic medical record data. To understand the patterns of SACT in real-word practice, it is necessary to develop standardized representations. The purpose of this panel is to discuss the scope of the problem, outline evolving methods to organize and represent SACT data, and demonstrate several methods to extract SACT information from real-world data sources.

Learning objectives:

Understand the complexities of SACT and name several approaches to standardly represent SACT
Appreciate the challenges of coordinated representation of complex temporal events and discuss several complementary approaches to temporal resolution
Learn about how patterns of SACT in real-world practice change over time, and how these changes relate to the understanding of the overall landscape of cancer treatment and prognosis

Speaker

Dr Michael Legg FAIDH

Consultant Health Informatician

Michael Legg & Associates

Session chair

Biography

Michael Legg is an expert in digital health and Principal of Michael Legg & Associates, consultants in information and organisational systems. He is a professional non-executive director and has previously led small, medium and large, for-profit and not-for-profit health care organisations and been a member of more than 20 boards and committees both national and international.

Prof Rae Woong Park

Professor

Ajou University

Panel: Motivation and challenge to standardise healthcare data across the world: OHDSI network

11:00 AM - 11:40 AM

Presentation

Biography

Dr Park is the Chair of the Department of Biomedical Informatics of Ajou University, South Korea. He had won almost 75 government research grants on medical informatics and has more than 180 publications in the medical informatics area. Dr Park is an active international collaborator of OHDSI and now he is in charge of FEEDER-NET (Federated E-health Big Data for Evidence Renovation Network), in which data from 60 Korea hospitals are harmonised.

Prof Seng Chan You

Assistant Professor

Yonsei University

Panel: Motivation and challenge to standardise healthcare data across the world: OHDSI network

11:00 AM - 11:40 AM

Presentation

Biography

Dr You is a Professor at the department of biomedical systems informatics in Yonsei University College of Medicine. He is a board-certified internist. Dr You has participated in, developed and led various research activities in the OHDSI Network in terms of data standardisation, vocabulary standardisation, OMOP CDM extension for genomic, text, and radiology data, and clinical epidemiology. Currently, he serves as Korean chapter leader in OHDSI-APAC.

Dr Jeremy Warner

Professor

Brown University

Panel: Standardised representations of systemic anticancer therapy regimens as an enabler of real-world evidence synthesis

11:50 AM - 12:30 PM

Presentation

Biography

Dr Warner is Professor of Medicine at Brown University, a practicing hematologist, the Deputy Editor of HemOnc.org [1], and Chief Software Architect of HemOnc [2]. HemOnc.org is the largest freely available SACT knowledge base and is used widely by healthcare professionals in the United States (~70% of approximately 30,000 monthly users) and around the world. HemOnc is an ontology constructed using the HemOnc.org website data and additional resources such as mappings to RxNorm codes and has been adopted by the Observational Health Data Sciences and Informatics (OHDSI) community as the standard representation of SACT in the OMOP Standardized Vocabularies.

Dr Georgina Kennedy

Senior Research Fellow

Ingham Institute

Panel: Standardised representations of systemic anticancer therapy regimens as an enabler of real-world evidence synthesis

11:50 AM - 12:30 PM

Presentation

Biography

Dr Georgina Kennedy is a clinical research data specialist with an interest in natural language processing and machine-learning data-driven modelling. She is delivering a collaborative research program focusing on the systematic improvement of quality, integrity and capacity of clinical data research using innovative software platforms and methods.

Dr Asieh Golozar

Professor of the Practice & Director of Clinical Research at the Ohdsi Center | VP Head of Data Science

Northeastern University

Panel: Standardised representations of systemic anticancer therapy regimens as an enabler of real-world evidence synthesis

11:50 AM - 12:30 PM

Presentation

Biography

Asieh Golozar, MD, PhD, MHS, MPH is a physician epidemiologist and professor of the practice and director of clinical research at the OHDSI Center at Northeastern University. Dr Golozar leads the OHDSI Oncology Working Group, endeavouring to extend the OMOP Common Data Model to support representation of cancer diagnoses and treatments at a granularity required for conducting large-scale observational cancer research. The Oncology Working Group has been leading efforts on reliable abstraction of SACT treatment regimen from individual drugs accounting for temporal sequence of drug exposure and deviations from the expected time schedule.