Heather Cartwright, General Manager of Microsoft Health, joined me to contemplate the new horizons in healthcare made possible by SAS and Microsoft’s new strategic partnership.
The four walls of the doctor’s office are disappearing. Following decades of planning for hypotheticals, this year health care organizations were compelled to make good on the promise of digital transformation.
Meeting the challenges of a global pandemic means that every health care stakeholder — from patients and providers to insurers and pharmaceuticals — must share data from disparate geographies, scenarios, and populations in the effort to help understand, treat, and eventually eradicate COVID-19. No doubt, the processes built today — as well as the key lessons learned and preparations made — will define the future of healthcare.
But, how can we securely connect data, establish interoperability, and empower healthcare organizations to speed up their digital transformation timelines?
That was the subject of a stimulating conversation I had with Heather Cartwright, who leads new cloud and AI technologies for health data at Microsoft. Her team is accelerating healthcare innovation through artificial intelligence and computing, a goal that SAS and Microsoft share and are working together to reach through our new strategic partnership.
From what we discussed, it seems the future of health care is bright—and full of data.
Transforming our understanding of human health
Massive efforts are underway to connect healthcare data that comes in every form, standard, and quality imaginable. Gaining insights from the intersection of patient observations and clinical trials, for instance, can feel Sisyphean—yet that ability will likely define the future of healthcare.
The Healthy Nevada Project is already demonstrating the value and possibilities of connecting patient data. This community-based, genetics study uses SAS machine learning and artificial intelligence to improve population health in Nevada.
By gathering information from citizens who enroll in the program, geneticists can identify predispositions for certain diseases, or alert asthma patients when they travel to a part of the state with poor air quality.
To amplify these applications of data analytics and AI on a global scale requires massive compute power and a secure infrastructure to share and control patient data. That’s what excites me about our new partnership with Microsoft and the combined power of SAS analytics running on Azure.
Heather agrees, citing unsustainable workloads in the healthcare space as an impetus for adoption of the cloud. “There is an overwhelming increase in the types of data care teams need to manage. As the number of inputs clinicians use to treat patients grows, we need to leverage different tools for health data. Cloud technology provides the scale which is urgently needed to manage health data workloads, but just as important, it enables machine learning with that data. Health leaders understand how that will transform our understanding of human health and how we deliver care in the futures. So healthcare is finally saying, ‘okay we need to go to the cloud, and we need to know how.’”
As the leader of SAS’ scientific response to COVID-19, I can testify to the difficulty of bringing observational patient data derived from health care claims, health care registries, clinics, and all types of patient interactions together for analysis. To lead the way forward, healthcare organizations need a comprehensive enterprise cloud strategy and an analytics strategy that drives insight from this real-world data.
Microsoft has been hard at work developing a cloud that meets healthcare’s unique requirements and idiosyncrasies. What’s driven their innovation, Heather said, is an ambition “to understand the nuances of care teams: what researchers need for healthcare and how diverse data sets are brought together in different segments of the health care industry—whether you’re looking at radiology, genomics, or epidemiology.”
This understanding is sure to drive successful outcomes in every corner of the industry. With a solution that’s customized to healthcare’s unique requirements and a cloud that can bring massive data sets together, pharmaceutical companies will drive a lot more value—they’ll get insights about their medicines, and how patients are needing help. It can help bring ‘value-based healthcare,’ which everybody has been talking about for years already, to fruition.
Microsoft and SAS are committed to meeting healthcare organizations where they are, with cloud-based solutions that are ready to run on day one, but can also scale as organizations—or crises—grow. Mercy, a leader in both technology and clinical care, shows the promise of these solutions. Among the first organizations running SAS analytics natively on Azure, Mercy boasts a virtual health division and an analytics culture that helps them bring information together about COVID-19 patients and rapidly package that data to make it available to other health organizations working on innovative therapies.
The safe and secure cloud
The healthcare industry takes a conservative approach to innovation and for good reason. Patients deserve a careful, validated approach. But in order to deliver on this approach, healthcare needs scale, and it needs to be able to drive insights from different types of data sources.
Azure has the power to deliver the scale needed in healthcare, with a unique commitment to compliance in nearly every region of the world. As Heather put it, “when you're innovating, trust is essential. We want to make sure that health systems maintain control over their data when they move it to the cloud, that they can define database access and bring their own identity. We make sure these security measures are in place so our customers can trust that their data is in the right foundation, because that frees them to really focus on innovation.” SAS builds on that foundation with AI and analytics designed for Azure.
There are always patients at the end of healthcare solutions, and the technologies that SAS and Microsoft build for providers, health insurers, pharmaceutical companies, and physicians will always be rooted in maintaining those patients’ safety and security, while empowering better health outcomes.
Driving innovation through analytics
Heather also spoke to the value of flexibility, remarking on how Azure Synapse enables the ability to work in whichever environment healthcare professionals are already comfortable. “Scientists shouldn’t have to learn a new language in order to work with a different data set,” she explained.
Critical to that flexibility are the feedback loops and machine learning that enables dynamic decision-making at every level of healthcare. “It is so important to bring the front lines of healthcare into that machine learning process,” Heather noted, “Feedback loops are essential to make models better...refining, expanding even, or identifying new algorithms we need to develop.”
SAS and Microsoft are building solutions that physicians can trust. We’re rapidly creating simpler interfaces that do not hide the analytical complexity or the data complexity, but still allow decision makers to make the right decision, to extract insights that correctly steer how they need to run their organization. From Heather’s lens, transparency in AI development is key. ”People using data models should be able to go deeper and understand what is happening in those models, what the inputs are for those models and the parameters, so that they can have trust in it. And then we can continue to validate and make sure that they are working at the right levels.” In other words, acceleration shouldn’t come at the cost of proven, hierarchical data validation processes.
One example of how analytics help physicians make better, trusted decisions, is in oncology. Without substituting the expertise of the physicians, SAS’ deep learning algorithms and models helped Amsterdam UMC automate the read-out of metastatic liver lesions due to chemotherapy treatment by rapid calculation of various metrics like volume or surface of the lesions. The algorithms didn’t hide the complexity of the analytics, but they did provide enormous support for oncologists who would otherwise spend a lot of time on error-prone tasks.
Human expertise, complemented by computational power, leads to more accurate patient treatment. And access to cloud resources makes the clinical workflow and point of care analysis far easier.
Defining the future of healthcare
If healthcare organizations have data in the cloud, analytics engines running, and data science teams working closely together, they will have a readiness machine to make decisions in a crisis. I’m thrilled to work with Heather as SAS and Microsoft build that secure and powerful readiness machine together.
