Partnerships and interoperability

This page contains brief descriptions and links to additional information about the groups and initiatives that we are working with in developing Cochrane linked data.  

The HarmoniSR Project

We are collaborating closely with the HarmoniSR project - a within-Cochrane project that aims to harmonise the (currently quite disparate) approaches to annotating studies used by different Trial Search Coordinators within Cochrane Review Groups. There are clearly many opportunities for synergy between these 2 projects.  Perspectives, experiences and critiques from TSCs will be essential in building the ontologies, vocabularies, triple store and tools - all of which should be developed in a way that will support the coordination and standardization of approaches that HarmoniSR is looking to achieve.

MAGIC

Description of MAGIC from their website

MAGIC is a non-profit organization backed by an international team of doctors and researchers. Our goal is to improve the authoring, adaptation, presentation, dynamic updating, and dissemination of medical guidelines using the GRADE methodology. MAGIC aims to facilitate shared decision making between patients and providers. This is accomplished by developing decision aids and using guidelines directly in EHRs and decision support systems, all with structured data.

Dedicated to open data, we aim to improve the flow of information between different actors in the medical knowledge ecosystem. We are passionate about helping spread the adoptionand use of trustworthy guidelines, hoping to benefit the health of everyone in the world.

Linn Brandt attended our London linked data meeting in December 2014 and has continued the discussions with us since that time.  Linn has put together a Google spreadsheet  comparing data models in MAGIC, GRADEpro, the York databases, clinicaltrials.gov and others. See linkedPICO- Guideline/evidence data models Overview of whats out there for details & discussion.

Drugome

This project is attempting to find new uses for existing drugs, primarily by data mining genomic and proeteomic databases. They would like to combine this with evidence of efficacy from Cochrane reviews. They have offered a Phd student or postdoc for six months to assist with annotations. See Complete Drugome Project Plan (in Wrike) for additional details.

OMOP/IMEDS/OHDSI

See The Observational Medical Outcomes Partnership (OMOP) Vocabularies for details of a project that has mapped relationships between a large number of potentially relevant vocabularies (including MeSH, SNOMED CT, RxNorm, LOINC, ATC and ICD-9 and 10).  A full list is available at OMOP Vocabulary Licensing Issues.  Their mapping process has created clinically relevant hierarchies (e.g. a category of antihypertensive drugs) which looks as if it could be quite useful.

OHDSI (Observational Health Data Sciences and Informatics).  This (mainly US based) consortium is primarily interested in using large observational datasets (e.g. computerized medical records, or adverse drug reaction reports submitted to regulators in addition to published RCTs or observational study reports) to identify drug risks and benefits. 

The Finnish Medical Society Duodecim

Through its publishing arm Duodecim Medical Publications produces EBM Guidelines and The Evidence-Based Medicine electronic Decision Support (EBMeDS) system.  Ilkka Kunnamo, the Editor-in-Chief of EBM Guidelines has been a Cochrane contributor for many years.  Ilkka has put together the following diagram outlining his vision of future linkages of data from electronic health records, studies, reviews, guidelines and other sources.