Healthcare is in an intense era of retooling, similar to the Industrial Revolution of several centuries ago. Bright minds in healthcare and technology are shaping new tools powered and empowered by artificial intelligence, machine learning and deep learning. This burgeoning Age of Intelligence is matching minds and machines to sharpen knowledge and insight to improve the delivery of care for patients, populations, practitioners and providers.
We are thinking, differently, as AI moves quickly from hypothetical to business critical. For healthcare organizations today, collecting data and using analytics to improve performance and positively impact patient outcomes is a critical success factor. Finding the right data, at the right time, increasingly in real time, often competes with the need to impose the security and compliance standards a healthcare environment demands.
These organizations require systems that deliver ubiquitous data availability and real-time analytics to make data actionable for clinicians at the point of care, for researchers on the cutting edge of innovation, and for administrators driving operational efficiency.
Success in providing these capabilities will require a departure from traditional architectures and will necessitate a move toward an agile, high-performing and cost-effective data platform that supports the operations of today and the innovation of tomorrow.
In my more than 15 years working in healthcare IT, most recently as the Deputy CIO for Weill Cornell Medicine, I have seen that organizations that are successful in leading this new age of intelligence and discovery are leveraging their strong internal relationships between administrators, researchers, clinicians, technology teams and strategic technology partners. And then they’re thinking outside the box, changing physical architectures and infrastructures to support the groundbreaking work to leverage AI and accelerate the pace.
The power comes in our ability to take care of the individual based on insights and data from the population. Think precision medicine, prevention, prediction and patterns. So how do we get from here to there, maximizing AI and putting it at clinicians’ fingertips? Here are some questions to ask yourself and your team.
Your greatest assets are in the data you generate and maintain. How do you and your organization view data governance in general and more specifically when it comes to big data? Are you enabling access to these assets in support of your organization’s AI initiatives?
AI is all about connecting disparate data sets to generate new insights. How are you connecting with others within your organization? Are you working to create a community around AI so that economies of scale can be gained, inspiration shared and multi-disciplinary teams can form?
Innovation is a great way to reshape the current landscape in the short-term and quickly needs to become the new norm. How are you integrating your innovation programs around AI with current operations? How can you develop a stronger relationship with your internal IT teams? What is your roadmap to convert discoveries into production systems?
Success in AI requires new ways of thinking in diagnostics and in treatment but also in architecture. Can your current enterprise architecture and strategic technology partners support the goals of your AI initiatives? Is your “tech stack” agile and performant enough to support you in your journey to reshape the delivery of care?
We’re in an amazing time in healthcare. Hospitals and health systems are turning data on the shelf into actionable knowledge, increasing insight, efficiency and value. Are you ready for the revolution? I’d love to continue the dialogue. Reach out. Let’s connect.
