How can we improve the way we deliver healthcare, moving from the pipeline to a platform


In the world, healthcare providers have been battling with a lack of access and quality for years. Even though providers, patients and payers all call for reform, the health sector has been unresponsive to external disruption. There is a need for producers and consumers to work together to create a new healthcare paradigm that will revolutionize healthcare delivery and advance cures.

To drive transformation it is necessary to alter our mindset. We must move from traditional, linear pipeline-service-model thinking to a platform approach, which brings together longitudinal medical data, producers and consumers to co-create a new healthcare paradigm that fundamentally changes how we provide healthcare and advance cures.

In order to achieve this I believe it is the obligation of healthcare providers such as Mayo Clinic and others – who manage the complicated emotional and data-driven elements of healthcare decision-making alongside our patients on a daily basis and work with other partners to facilitate a patient-centered change that addresses not just access, cost , and quality, but also scalability the privacy of data and equity in addition to the artificial intelligence’s (AI) growing role in the field of medicine. Here at Mayo Clinic, our novel instrument for healthcare transformation is Mayo Clinic Platform, which could serve as a model for the global revolution in healthcare.

The unique structure of a platform for healthcare

A healthcare platform can’t be replicated from other industries. It is essential to build the medical platform from ground from the top, and its structure must be able to reconcile seemingly contradictory terms protecting patients’ information while allowing for innovation by providing wide access to information.

Mayo Clinic Platform begins with an entirely new digital platform that is flexible and extremely secure. Our cloud-hosted platform , which is home to one of the most extensive longitudinal clinical data sets worldwide – utilizes verified, de-identified data within the form of a federated model for learning where instead of transferring information to software, we’ve reversed the process and added algorithms to the unidentified data (see the figure 1 below). This design creates a glass wall’ that allows other collaborators the ability to access data in order to improve healthcare without data being ever removed from the platform which puts the patient and their privacy rights first . This is a crucial need to safeguard the trust of patients within the healthcare system that is platform-based.

Making use of platforms to create to increase access and expand information

A healthcare platform facilitates the aggregation and integration of various clinical and non-clinical information that will enable us to treat more patients connect patients and data to generate new knowledge and improve the way we treat patients by creating new, verified end-to end algorithms as well as other solutions that are innovative to improve healthcare.

In our clinic, doctors and researchers in collaboration with external partners like Google, nference, and others have utilized massive data sources to develop algorithms to help detect early cardiovascular diseases such as pancreatic cancer, breast cancer, neuromuscular diseases and depression with the intention to alter the course of illness for the individual patient. We’re also working on additional AI applications to reduce the stress of administrative and clinical tasks.

We’re hopeful that utilizing data, technology and analytics will help improve the quality of healthcare, make it more accessible and democratize. more affordable and accessible to everyone. A good example of this is our work on Electrocardiogram AI algorithms. It is our belief that, in the not too distant future, and at a affordable cost, a smartphone or other low-cost device can run several AI algorithms, and will be able to monitor patients for asymptomatic disorders of 15-20. This will allow us to examine people on a massive the scale of a hospital and detect disease quickly, allowing us to intervene. Another example that could be scaled up is an algorithm that reduces the time spent by clinicians in designing complicated neck and head radiation therapy plans down from 17 hours down to just one hour. In the next few years, we expect that more hospitals across the globe will be able to detect, treat and prevent complicated illnesses as a result of the flow of clinical information via our platform.


The hospital will take the patient

Moving away from pipeline thinking and platform thinking allows for the expansion of care in remote locations such as home-hospital models that we relied on during the outbreak. It is believed to be 40percent of healthcare providers will move 20% of their hospital beds to homes over three years.

In the beginning in the COVID-19 disease, the organization started Advanced Care at Home (ACH) that provides comprehensive hospital-quality medical treatment to patients at their homes. They receive 24/7 access from an Mayo Clinic provider, as well as regular in-home visits by a group of local healthcare providers. In partnership with our partner Medically Home, this initiative integrates all the necessary elements that support the home-based hospital experience, by using technology, a providers’ networks and knowledge to meet the patient’s requirements. Through ACH we’ve managed to reduce the number of readmissions by half, which means patients are less confined to our facilities and spend more time with their families and living their lives. Our team has been working closely in partnership with Kaiser Permanente and Medically Home to develop a model for care that can be scaled and have formed an all-encompassing Advanced Care at Home Coalition to sustainably scale it. ACH is only one aspect of the new healthcare system that utilizes various data inputs to provide seamless shifts between traditional and digital in-person healthcare.

Platforms to help improve equity

There is a valid worry that the use of AI on data on a platform for healthcare could create more the disparities. However, the ethical and accepted usage of AI coupled with platform-based idealism can provide equitable healthcare access for many poor populations across the globe.

As part of the Mayo Clinic Platform, we have created a process that tests every algorithm we design and implement, to ensure that it’s appropriate for the its intended purpose. Alongside US health care providers as well as partners from across the sector, we’ve formed the Coalition of Health Care AI to create guidelines to ensure the delivery of high-quality healthcare to all with transparent and reliable Health AI technology. One of the deliverables of the coalition is an algorithm-labelling system that will define the data that is used to create every algorithm, as well as its value and limitations in relation to a specific population, for instance an algorithm that is trained on female-specific data could not be applicable to males. The project on data labelling is designed to boost the credibility, equity and inclusion of all through fostering confidence and transparency in AI algorithms, and ensuring that users know that the algorithms are suitable for their intended usage (see the figure 2 below).


The shift from pipeline to platform thinking has the potential to transform healthcare and provide the needed flexibility that will help us better handle the next health crisis. In the last two years, we’ve demonstrated the possibilities, the utility and scale-ability that platform thinking can bring to healthcare. We now need to see a massive implementation by biotech, government agencies pharmaceutical companies, NGOs, and healthcare providers , with obstacles to stop regression towards pipeline-based thinking. Platform thinking will allow us to identify and prevent diseases and facilitate hospital-level treatment for patients at home , and help scale clinical knowledge to reach many populations in remote parts of the globe. It is the new future that we are building together today, as the platform revolution is finally coming to healthcare.

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