Weekly OHDSI Digest - 18June2018

MauraBeaton · June 18, 2018, 8:04pm

OHDSI MEETINGS THIS WEEK

OHDSI Community Call - Tuesday at 12pm ET
https://meetings.webex.com/collabs/#/meetings/detail?uuid=M59X2V1U61WC9ASID2Z5N3UT95-D1JL&rnd=811649.98682211121
US TOLL: +1-415-655-0001
Meeting Number: 199 982 907

Architecture Working Group - Thursday at 10am ET
Webex: https://jjconferencing.webex.com/mw3100/mywebex/default.do?service=1&siteurl=jjconferencing&nomenu=true&main_url=%2Fmc3100%2Fe.do%3Fsiteurl%3Djjconferencing%26AT%3DMI%26EventID%3D610982452%26UID%3D501476547%26Host%3DQUhTSwAAAAQu4P1o9qm71JJ1Zj4-uvZbjQttsCinu71JCRxBAHAXnzjjRAiTspTzU9ojLmjMF4CcTBWw4zn1dqYPTWu5vJ9_0%26FrameSet%3D2%26MTID%3Dm3e1ceeca56f1e94c9fcf1ae98c10e02e

GIS working group meeting - Next Monday (June 25th) at 10am ET

Meeting Number: 735 317 239
Password: gaia

ANNOUNCEMENTS

2018 OHDSI Symposium - REGISTER NOW
Registration is officially open for the 2018 OHDSI Symposium which will take place Friday, October 12th. You can register here: https://www.ohdsi.org/symposium-registration-2/
A separate registration for tutorials will open shortly. Tutorials will take place before and after the symposium on October 11th and 13th. More details about tutorials can be found here: https://www.ohdsi.org/tutorial-workshops/

2018 OHDSI Symposium - CALL FOR PARTICIPATION
The OHDSI Symposium Planning Committee are now accepting abstract submissions for the 2018 collaborator showcase. We are inviting collaborators to submit abstracts to present posters, software demonstration or oral presentations during the collaborator showcase which will take place during the main symposium on Friday, October 12th. More details are available here: https://www.ohdsi.org/collaborator-showcase/
Abstract Submissions Due: 5pm on Thursday, August 7, 2018

2018 China Symposium
This year’s China Symposium is taking place June 29th to July 1st in Guanzhou, China. More details are available here: https://www.ohdsi.org/events/2018-china-symposium/

Moving Study Materials to Github
We currently in the process of consolidating all OHDSI study materials on the OHDSI github and will be retiring the wiki page within the next few days. If you have study materials on the OHDSI wiki, please move them here: https://github.com/OHDSI/StudyProtocolSandbox
Completed studies should be moved here:
https://github.com/OHDSI/StudyProtocols

There are always distractions, if you allow them.

Tony La Russa

COMMUNITY PUBLICATIONS

Developing a Regional Distributed Data Network for Surveillance of Chronic Health Conditions: The Colorado Health Observation Regional Data Service.

ncbi.nlm.nih.gov

Developing a Regional Distributed Data Network for Surveillance of Chronic Health Conditions: The Colorado Health Observation Regional Data Service.

E Bacon, G Budney, J Bondy, MG Kahn, EV McCormick, JF Steiner, D Tabano, JA Waxmonsky, R Zucker and AJ Davidson, Journal of public health management and practice : JPHMP, Jun 2018 07

Electronic health records (EHRs) provide an alternative to traditional public health surveillance surveys and administrative data for measuring the prevalence and impact of chronic health conditions in populations. As the infrastructure for secondary use of EHR data improves, many stakeholders are poised to benefit from data partnerships for regional access to information. Electronic health records can be transformed into a common data model that facilitates data sharing across multiple organizations and allows data to be used for surveillance. The Colorado Health Observation Regional Data Service, a regional distributed data network, has assembled diverse data partnerships, flexible infrastructure, and transparent governance practices to better understand the health of communities through EHR-based, public health surveillance. This article describes attributes of regional distributed data networks using EHR data and the history and design of Colorado Health Observation Regional Data Service as an emerging public health surveillance tool for chronic health conditions. Colorado Health Observation Regional Data Service and our experience may serve as a model for other regions interested in similar surveillance efforts. While benefits from EHR-based surveillance are described, a number of technology, partnership, and value proposition challenges remain.

Using the Personal Health Train for Automated and Privacy-Preserving Analytics on Vertically Partitioned Data.

ncbi.nlm.nih.gov

Using the Personal Health Train for Automated and Privacy-Preserving Analytics on Vertically Partitioned Data.

J van Soest, C Sun, O Mussmann, M Puts, B van den Berg, A Malic, C van Oppen, D Towend, A Dekker and M Dumontier, Studies in health technology and informatics, 2018

Conventional data mining algorithms are unable to satisfy the current requirements on analyzing big data in some fields such as medicine, policy making, judicial, and tax records. However, applying diverse datasets from different institutes (both healthcare and non-healthcare related) can enrich information and insights. So far, analyzing this data in an automated, privacy-preserving manner does not exist to our knowledge. In this work, we propose an infrastructure, and proof-of-concept for privacy-preserving analytics on vertically partitioned data.

A Methodology for Fine-Grained Access Control in Exposing Biomedical Data.

ncbi.nlm.nih.gov

A Methodology for Fine-Grained Access Control in Exposing Biomedical Data.

A Trifan, J van der Lei, C Díaz and JL Oliveira, Studies in health technology and informatics, 2018

Biomedical data integration and processing is a very sensitive issue and a main barrier for research, since it normally implies dealing with private clinical information. To overcome this problem, we propose a solution based on multiple levels of data visibility, combined with a fine-grained access control over the shared data. Through our proposal, on one hand, data custodians can decide the level of detail at which they want to share data, in a flexible manner that can be adjusted along the time. On the other hand, adequate permissions are provided to the users that want to access the data, according to their role and research plan.

The Data Gap in the EHR for Clinical Research Eligibility Screening

Pharmacogenomic Approaches for Automated Medication Risk Assessment in People with Polypharmacy