Patients, caregivers, and providers all want better treatments, more equitable access to care, and ultimately healthier communities. Achieving these goals requires changing how we approach health and making it more personal by integrating genomics into therapeutic development, leveraging artificial intelligence (AI) and machine learning (ML) to guide and improve clinical workflows, and even incorporating social determinants data into care plans.
A personalized approach has the potential to yield both cost savings and better health outcomes by improving patient experiences, increasing the efficacy of therapeutics, and creating efficiencies in care delivery and research. However, before organizations can achieve the mission of advancing personalized health, they first have to develop a solid data strategy and a clear plan to achieve that strategy.
It is important to note that these are not one-time technology projects. Organizations must embark on a digital journey to modernize, derive insights, and ultimately innovate on behalf of the patient. We call this the “Road to Personalized Health”, and it involves four key steps: migrating data, protecting data, unifying data, and innovating with data.
In the keynote session of our 4th annual healthcare and life sciences Industry Innovators event, I spoke with three industry leaders to gain insights and examples related to each of these four steps—for their individual organizations and for the industry as a whole.
The goal of data migration is to create a solid foundation for innovation by moving on-premises systems and data into the cloud. This allows organizations to better manage, secure, and analyze your data. While this sounds simple, it’s critical to get it right, as this is the building block from which all other initiatives develop.
Dr. Shafiq Rab, Chief Digital Officer and System CIO of Tufts Medicine, shares with us how his organization recently completed a full migration of their healthcare IT systems to AWS, standardizing workflows from 6 disparate systems into a single system. Today, they run the entirety of their EHR infrastructure on the cloud and have successfully migrated over 100 patient portals and 40 integrated applications to AWS, adding significant value. Tufts Medicine also deployed Amazon Connect, an easy-to-use cloud customer service contact center, to streamline virtual care and modernize network connectivity to provide a more secure and compliant operating environment.
According to Rab, taking the entire electronic health record for a major health system requires processing speed that few other cloud providers have been able to achieve. However, with AWS, Tufts Medicine has built a centralized cloud ecosystem to run their entire healthcare organization. Using optimized solutions for deploying Epic on AWS, Rab and his team automated monitoring and remediation of the ecosystem to securely maintain and manage all the migrated assets.
“After we engaged AWS, I think it took less than a year to complete the entire project,” said Dr. Rab. “That shows you the speed and commitment with which the organizations deliberately worked together to achieve this monumental task.”
After migrating systems and data into the cloud, the next step on the road to personalized health is protecting those assets and ensuring that they are compliant. No matter what kind of medical or scientific data an organization is working with, security is job zero. This goes beyond ransomware considerations—organizations must decide how to prepare for cybersecurity, architect for resiliency, and comply with global industry regulatory requirements while adhering to data sovereignty requirements. Systems and data must also remain available to the right people at all times, regardless of the situation. There’s no room for error when it comes to people’s health.
Dr. Paritosh Dhawale, SVP and GM of GE Healthcare, knows just how important it is that systems remain available, compliant, and secure. “Data protection is core to our business and close to our heart at GE Healthcare,” he said in our keynote panel. “Several of our workflows are patient-critical, and our applications are governed by FDA regulations. Protection of our data is the key to preventing security-related safety issues.”
Dhawale described how GE Healthcare’s Edison platform aggregates data from a multitude of sources—including electronic medical records, medical devices, laboratory systems, and genomics data—to create a holistic patient data repository. He said GE Healthcare takes a security by design approach, examining everything from cloud hosting infrastructure to identity management frameworks. The Edison platform hosts third-party applications besides GE applications, so security considerations include managing consent and authentication frameworks to place strict controls on data sharing.
On top of data security, global organizations like GE Healthcare must consider privacy standards and regulations that differ by country and region, including GDPR and HIPAA. Furthermore, many hospitals have their own privacy standards for patient data and cloud technology. Some data types, such as images, include embedded patient information, so Dhawale and his team employ smart tools that identify information that may need to be blacked out or otherwise removed. All these practices are part of building data protection into the foundation of medical software product development.
Once an organization has migrated and protected their systems and data, it’s time to break down the data silos that have haunted research and care delivery. This might mean unifying data across multiple health data platforms or incorporating research data and insights from other organizations.
Pulling data together to make it functional and actionable is a challenge we’ve all encountered. With purpose-built health AI services like Amazon HealthLake and Amazon Comprehend Medical, customers can work to make sense of their health data and derive insights from it. This often starts with extracting medical information from troves of unstructured health data to create a complete, chronological view of a patient’s medical history, which leads to better clinical decisions and more informed decision-making for providers, patients, and caregivers.
Elizabeth Theophille, Chief Technology Transformation Officer of Novartis, spoke on our panel about how her organization developed an enterprise-wide platform that ingests and unifies data across the complete Novartis product lifecycle.
“Looking at the end-to-end value chain from drug discovery to commercialization, there’s an absolute need to speed up execution and personalize the experience for customers,” she said. “The only way to do that in a cost-efficient manner is to put the data in one place. We’ve leveraged cloud technology to consolidate all of our data to support collaboration, insights, and innovation.” By breaking down data silos, Novartis aligned data assets with business results, using end-to-end data and analytics solutions to make better business and clinical decisions informed by deeper insights.
According to Theophille, Novartis went from managing 2000 complex, point-to-point, integrated applications to ingesting data into a universal cloud technology platform. “We’re building simplification while leveraging automation and new capabilities to make this happen at a speed that we haven’t seen before,” she said. “From drug discovery to manufacturing to sales, we’ve fully integrated and connected our data, representing a 360-degree view of the enterprise.”
This integration provides insights across multidisciplinary processes, enabling stakeholders across the organization to make better decisions. “It’s ultimately about allowing us to help reimagine medical innovation to get patients life-changing therapies much faster and at a lower cost,” she said.
After unifying data in the cloud, organizations reach the fun part: innovation. Truly successful innovation projects are built on a solid data strategy foundation, and they don’t have an endpoint; innovation is a continuous mindset.
By establishing a secure, compliant, and unified data strategy on AWS, we find our customers can more quickly develop and deploy projects that truly bring impact to patients and their business. From improving and accelerating diagnosis to modernizing care infrastructure to managing population health, AWS offers the most comprehensive machine learning platform. Organizations can unlock the potential of science and health data with solutions like Amazon SageMaker that democratize access to ML services and provide the tools to do precision medicine at scale.
All three panelists reflected on how they see industry leaders—including their own organizations—innovating with data to bring personalized health to patients:
Dr. Rab of Tufts Medicine emphasized how migration to cloud platforms gathers data all in one place while simultaneously unlocking unparalleled computing power that can extract information from that data to benefit patients. “We are innovating with ML and AI with the ultimate goal of providing personalized medicine and anticipatory care,” he said. “Our goal is not to keep the data to ourselves, but actually to liberate the data so the consumer can make decisions too.” According to Rab, achieving this goal will require collaboration not just among healthcare stakeholders but across industries spanning from technology and life sciences to travel and agriculture.
Dr. Dhawale described how technology solutions from GE Healthcare and third-party startups can work together to meet highly individualized patient needs across ages, genders, geographies, and medical conditions. “Patients are becoming more vocal about wanting to receive the best quality care. The level of virtualization we need to deliver this quality care across the board wouldn’t be possible without the cloud technology and collaboration provided by AWS,” he said.
Finally, Theophille highlighted Novartis’ patient support services as one of the most direct ways the organization is bringing precision medicine directly to patients using cloud technology. After receiving a specialty medicine from Novartis, patients gain access to an integrated platform that helps them navigate the complex world of approvals, authorizations, injection instructions, and beyond. This platform is part of Novartis’ universal cloud technology platform, to connect it to digital products that support patient treatments, such as companion apps and auto-injectors.
“As we continue to leverage the power of the cloud, putting our customers at the center, and democratizing access to our technologies, our business can now harness the platforms we have created to build new products to achieve their strategic goals at a pace and speed we’ve never experienced before,” she said.
Along with industry experts like these, AWS is committed to innovating on behalf of patients and caregivers to bring personalized health from vision to reality. To learn more, watch the full keynote panel and other sessions from the virtual event on demand.