ICHI 2019 Workshop Proposal: openEHR and Data Reuse Networks

发表日期:2019-01-30 16:42

ICHI 2019 Workshop Proposal

Workshop Title: Open Electronic Health Records and Data Reuse Networks


Workshop Organizers




Xudong Lu

Zhejiang University


Koray Atalag

The University of Auckland


Jim Warren

The University of Auckland


Shinji Kobayashi

Kyoto University


Heather M. Leslie

University of Maine


Dongsheng Zhao

Academy of Military Medical   Science, China


Zhengxing Huang

Zhejiang University


Fei Wang

Cornell University



Workshop Description

The paradigm of the Learning Healthcare System sets data reuse as a corner stone for the continuous improvement of our healthcare system and the rapid adoption of new evidence. This has led health data not only to be considered as a strategic asset, but also to become a public good that can improve healthcare in particular, and the society in general. For realizing the LHS, health data need to be accessible (when all privacy requirements are met), and understandable across the different stakeholders that use them. This means that clinical data need to be seamlessly incorporated to various Electronic Health Records (EHRs) when it is transmitted from one organization to another. Only then it is possible to build longitudinal cross-institutional EHRs that can be shared and accessed by the different health providers involved in a patient′s care. From a data reuse perspective, the challenge is not only to incorporate data from one EHR into another so it is possible for humans to interpret these data, but also to make these data machine interpretable so data-driven analytics can be performed. Therefore, allowing semantic interoperability is needed for preserving the meaning of data. This has motivated health authorities in several countries to support and fund initiatives towards the standardization of clinical information for care, clinical research, epidemiology surveillance, population heath, decision support etc.

To address the challenge that clinical data needs to be understandable for various stakeholders and applications, several projects in Germany, Norway, China, Brazil, and Australia propose to apply openEHR as an open standard for building open platform EHRs and also as a specification for enabling secondary use of clinical data. OpenEHR defines a methodology for building interoperable EHRs which core is the definition of commonly agreed Clinical Information Models (CIMs) known as archetypes. This is a key feature that translates to: a) the ability to build Health Information Systems based on stable conceptual models provided that archetypes are validated by multidisciplinary teams at a national level; and (b) the empowerment of health providers by allowing them to manage and govern their health data independently from vendors, thus allowing them to switch from one product to another with a minimal impact.

OpenEHR is a versatile and scalable open standard for EHRs and data reuse. However, it also makes the adoption of openEHR a complex process for several reasons. First, the organizational process for adopting openEHR is very complex since the vendors, clinics, and national health trusts need to carefully coordinate their developments for eliciting, validating, and implementing archetypes. Secondly, from a technical point of view, the openEHR methodology involves challenges related to choosing selecting suitable technologies for implementing openEHR, and integrating openEHR servers with other technologies that are part of the EHR ecosystem such as terminology servers and middleware needed to interact with systems based on other standards (IHE, FHIR, CDA, etc.).

The workshop will discuss the different strategies and lessons learned while implementing openEHR in different countries. In particular, it will cover the large adoption of EHRs to build open platforms avoiding vendor locking and the recent advances in using openEHR technologies for performing phenotyping queries and data-driven analytics.

The objectives of this workshop are:

1. Share the knowledge and experience gained from the project of using the openEHR methodology.

2. Attract healthcare providers who have access to interesting sources of data and problems but lack the expertise in data modeling to reuse the data effectively.

3. Enhance interactions between researchers (from both academia and industry) working on problems from medicine and healthcare.

ICHI is a unique venue for this workshop as leading researchers and practitioners from academia and industry will be able to participate. A workshop where healthcare professionals can have an audience, present and discuss their problems, views and ideas on the field as well as pose research challenges will attract them to ICHI. The organizers of this proposed workshop have continuous and in-depth contact with people working on openEHR and clinical data reuse in China, Europe, and US which will attract a broad and varied set of participants. This workshop will present the participants experiences concerning the adoption and use of openEHR as open standard for clinical data. In particular, they will cover the challenges, main factors to consider, benefits, and lessons learned when adopting openEHR as interoperability standard for EHRs and data reuse. Each participant brings expertise built from different projects that involve national infrastructures for managing clinical information. Thus the workshop does not focus on pilot case studies, but on nation-wide projects for EHR standardization and data reuse.



Topic areas for the workshop include (but are not limited to) the following:

l  Lessons learned in openEHR information modeling at national and international level.

l  Challenges and success factors when adopting openEHR as an open platform architecture:

n  coordination among archetype governance bodies, vendors and clinics;

n  clinical models governance;

n  technology selection;

n  post-deployment follow-up.

l  OpenEHR and data reuse:

n  Modeling the data-reuse API (coordination between data reuse networks and archetype governance bodies);

n  Standardization of distributed sources;

n  Future challenges (GDPR and privacy preservation challenges in data reuse, Archetype Query Language enhancements for data reuse, and the role of terminologies in openEHR phenotyping).

l  Coexistence with disparate standards (HL7 FHIR, IHE etc.)


Duration of the workshop: half-day workshop

Planned activities

The workshop will be organized into three sessions.

The first session will focus on describing the background, the challenges, the methodology adopted, and the future research directions of openEHR.

The second session will focus on the methods, tools, results and lessons learned from the representative projects of the openEHR modeling and implementation in China, Japan, New Zealand, Brazil and other countries.

The third session will focus on the data reuse applications, e.g., clinical risk prediction for cardiovascular diseases, based on the obtained interoperable EHRs from the openEHR modeling and implementation.

Each speaker will be allocated 30 minutes for brief presentation which will be followed by a joint discussion session for question and answers in the remaining time.

Prof. Xudong Lu will give a brief closing summary of the workshop. 

The action items will be elicited and circulated to the attendees interested in following-up after the conclusion of the workshop.


The organisation of the discussion session

The questions to discuss will include, but not be limited to:

1.       Which research / development activities are you currently undertaking / interested to explore in openEHR modeling?

2.       What are the key relevant research questions in openEHR modeling and collaboration? How are they different from the research questions for other modeling/standardization methods?

3.       What challenges and opportunities are encountered in the implementation of  openEHR?

4.       What are the prospects and possibilities for implementing clinical data registries based on openEHR in different counties?


Specific educational goals

The workshop will provide the attendees with the following valuable opportunities:

1.       A global appreciation and understanding of the nature and scope of openEHR modeling, along with the major challenges for the future;

2.       The ability to identify the key roles that openEHR can play in building disease registries;

3.       The opportunity to learn the experiences of experts from two different countries about openEHR modeling and registry implementation;

4.       The opportunity to learn collaborative modeling and data analysis on ACS datasets between different counties.

5.       Networking opportunities with colleagues from around the world.



Expected Attendees

The intended participants are consumers, researchers, practitioners, software vendors, care providers and policy makers with interest in openEHR promotion, modeling and implementation. If the workshop is accepted, all presenters agree to be present at the conference.

Expected number of participants: 60


Short biographies

Xudong Lu

Professor, Zhejiang University, Hangzhou, China. Xudong Lu is a Professor in the Department of Biomedical Engineering at Zhejiang University and an elected openEHR Management Board member. He organized numerous openEHR promotion activities in China and directed his team to implement significant openEHR based systems.


Koray Atalag, MD, PhD, FACHI

Senior Research Fellow, Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand. Koray has 20+ years of experience in openEHR and has been a past management board member of openEHR. He has been involved in setting up the ANZACS-QI Registry and directed the openEHR modelling study of registry datasets.


Jim Warren

Professor of Health Informatics, Department of Computer Science, University of Auckland, Auckland, New Zealand. Jim is passionate about using IT to improve long-term condition management through decision support for health care providers and health consumers.
He is a member of the VIEW Research Team which has developed the ANZACS-QI registry and the PREDICT system for CVD risk prediction system in New Zealand. He has directed the application of the data driven machine learning based algorithm on the registry dataset.


Shinji Kobayashi

Shinji is a senior lecturer in the EHR research unit at Kyoto University, Co-chair of the Japan openEHR Association and the openEHR ambassador in Japan.


Heather Leslie

Heather is the principal consultant at Atomica Informatics and Co-lead for the openEHR Foundation's Clinical Program. Since 2004 she has guided the evolution of 'the openEHR approach' to creation of clinical content for electronic health records using archetypes, including driving development of the online Clinical Knowledge Manager (CKM) tool. She has also provided clinical modelling/clinical knowledge governance consulting services and training to many international eHealth programs & organisations - including Norway's Nasjonal IKT, NHS England, Australian Digital Health Agency, Canada's Alberta Health Services and the Ministry of Health in Brazil.


Dongsheng Zhao

Professor Zhao is the director of information center of Academy of Military Medical Science, China. His main research areas include health information system modeling, biomedical big data analysis and medical AI. He was the past vice president of CMIA, and served for several national/international conferences, such as EC member of Medinfo2017, co-chair of World Chinese Health Informatics Symposium on Medinfo2017, CMIA2015 SPC co-chairs, SPC member of 16th China-Japan-Korea Joint Symposium on Medical Informatics. He has published about 100 academic papers and is a recipient of several science and technology awards from government. At present, He is leading the construction of several National wide health information systems using OpenEHR Technology, such as the EHR systems for Chinese Army, integrated clinical and follow-up data platform for China Stroke Screening and Intervention Project.


Zhengxing Huang

Associate professor, Zhejiang University, Hangzhou, China, Zhengxing Huang is Keen to devote in research on healthcare data minining, computer-aided medical decision support using heuristic, algorithmic and/or statistical methods as exemplified in decision theory, protocol development, artificial intelligence, etc.


Fei Wang

Associate Professor in Division of Health Informatics, Department of Healthcare Policy and Research, Cornell University. His major research interest is data analytics and its applications in health informatics. His papers have received over 5,300 citations so far with an H-index 39. His papers won best paper award in ICHI 2016, best student paper award in ICDM 2015, best research paper nomination for ICDM 2010, Marco Romani Best paper nomination in AMIA TBI 2014, and his paper was selected into the best paper finalist in SDM 2011 and 2015. Dr. Wang is an action editor of the journal Data Mining and Knowledge Discovery, an associate editor of Journal of Health Informatics Research and Smart Health, and an editorial board member of Pattern Recognition and International Journal of Big Data and Analytics in Healthcare. Dr. Wang is the vice chair of the KDD working group in AMIA. More details of Dr. Wang can be found on https://sites.google.com/site/feiwang03/.

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