MINICOR is a multi-national pragmatic research initiative planned for launch in early 2020. Collaboratively supported by academic institutions and commercial partners, it is coordinated and co-governed by the Worldwide Network of Clinical Education and Research (WNICER), a not for profit organization focussed on catalyzing innovative healthcare research and education.


The MINICOR initiative was seeded in 2018 following two years of active discussion among leading clinician scientists, institutions, vendors and patient representatives. Developed from inaugural efforts to standardize data across institutions to predict sudden death in non-ischemic dilated cardiomyopathy, core issues were identified related to poor standardization and inconsistent collection across institutions.  This led to engagement of scientists and vendors with shared interests in data-driven risk modelling in cardiovascular disease.  The concept of a global cross-institutional, cross-vendor data standardization effort, aimed at catalyzing development and implementation of artificial intelligence (AI) through cardiovascular diagnostics, was established.


To achieve this key investigators from around the globe have been engaged in the fields of cardiovascular imaging, electrophysiology, heart failure and clinical trial design. Strategic vendor partners have been similarly engaged. MINICOR was ultimately established as the first international consortium  dedicated to transparently engaging patients in developing data-driven tools for improved cardiovascular healthcare delivery.

MINICOR is a Pragmatic, Multi-Institutional Observational Cohort Registry. All patients referred to sepcific clinical units (Cardiovascular Magnetic Resonance (CMR) Imaging or Cardiac Device Clinics) at each site are approached for participation. While additional clinics may be supported in the future, CMR and Device clinics was chosen to lead this initiative based upon a strong foundation of work and focus on advanced stage disease phenotypes. 


Aligned with its pragmatic design, patients are automatically engaged through a validated HIPAA and GDPR-compliant tablet App during their routine "check-in" process, deploying consent and collecting baseline demographic information. Automated surveillance for imaging and device data for consented patients is then performed through an API (Applications Programming Interface) that securely communicates with each site's local vendor platforms (list of partnered companies available upon request). Through these partnerships vendor data is de-identified at source and securely uploaded to a secure local data center.  This data is provided to each institution for unrestricted research use while a consolidated data repository of pre-defined common data elements is established.