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The healthcare industry’s ongoing shifts from a fee-for-service to a value-based models, is pushing technology platforms to further streamline healthcare delivery operations.



ECMP aims to establish the feasibility and build an AI platforms that will integrate tools to improve interventional cardiology operations and delivery of care in its centers across Indonesia.

ECMP will also accompany third party operators in the choice and adoption process of cardiac AI technologies to assure optimal ROI and successful integration.


To achieve this we seek to collaborate with interventional cardiologists, clinical scientists, deep learning experts and companies with a shared mission to advance cardiac catherization and reduce healthcare costs through AI.

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AI has initiated a transformation in healthcare, powered by the increasing availability of healthcare data and the rapid evolution of analytic technologies.


The nature of interventional cardiology creates an opportunity to develop AI based solutions designed to improve real-time clinical decision making, streamline workflows in the catheterization laboratory, and standardize catheter-based procedures through advanced robotics.


AI offers the potential for transformational advancement in cardiovascular care delivery, yet practical applications of this approach have yet to be integrated into clinical workflows and systems.


The healthcare industry is increasingly focusing on value-based care and on reducing costs for equal or better quality. It’s forcing many operators to use AI applications to increase automation beyond traditional information technology and electronic medical record use cases.


For the technology to make a tangible impact, algorithm developers need to identify compelling use cases where the use of AI can improve clinical outcomes and deliver a positive ROI for healthcare operators.


Moreover, the technology needs to be integrated with the existing user interfaces and workflows to augment doctors’ knowledge and efficiency. It must also be readily accessible when needed.


Multiple applications and AI algorithms provide actionable information that allows healthcare providers to reduce the cost of care, while improving diagnostic confidence and patient outcomes

Post-processing for angiography

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Fractional flow reserve

Clinical decision support system

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