How We Have Seen Healthcare Change In The Last 20 Years
As someone with 20 years of experience in the software industry, I’ve seen firsthand how technology has radically transformed healthcare. From working with Oracle, Epicor, and Infor (Lawson) to helping implement Electronic Medical Records (EMR), I’ve been at the forefront of healthcare’s digital transformation. But the changes I’m witnessing today, particularly with Artificial Intelligence (AI), are nothing short of revolutionary. Looking back, it’s amazing to see how far we’ve come, especially when I think about a conversation I had early in my career.
The Early Days: The Mind-Blowing Idea of Remote Hosting
When I first entered the healthcare space, one of the most exciting and forward-thinking ideas was storing and hosting patient data remotely. I remember speaking with a representative from Denver Health about the possibility of hosting their data on remote servers instead of keeping everything on-site. At the time, the concept of hosting data “somewhere else” felt incredibly radical. This was the early 2000s, and the idea of moving critical healthcare data out of the building and into the cloud (which wasn’t labeled yet) was almost unthinkable. Yet, as we explored this possibility, we could already see the potential for better data management and disaster recovery.
Fast forward to today, and we’ve come a long way. Back in 2008, when I sold my first EMR deal, I was convincing server warriors to host off-site. Now, not only have companies adopted this method of storage, but they have fully embraced the cloud, making remote data storage a standard practice. Hospitals and clinics store massive amounts of data in multiple secure locations worldwide, all accessible with just a few clicks. AI is now leveraging this data to analyze medical records, make predictions, and even improve patient care in ways we could only imagine back then.
AI and Diagnostics: A Leap Forward
When I was working with EMR systems at Oracle and Lawson, the goal was to digitize healthcare data and improve the accuracy and accessibility of patient records. But even with this shift, diagnosing conditions often still relied heavily on human expertise. Today, AI is taking that data to the next level, helping doctors make faster and more accurate diagnoses.
AI-driven tools are now capable of analyzing medical images like X-rays, MRIs, and CT scans far more efficiently than a human could. Back when we were selling EMR systems, I could never have predicted that AI would play such a significant role in diagnosing cancer or heart disease. But now, AI can identify early signs of conditions with astounding accuracy, enabling earlier interventions and better patient outcomes.
Personalized Medicine: From General to Tailored Care
While EMR systems provided healthcare professionals with a centralized way to manage patient data, they didn’t offer much in terms of tailoring treatments to individual patients. Fast forward to today, and AI is changing that by enabling personalized medicine. AI analyzes not just patient history but also genetic data, lifestyle factors, and environmental influences, helping doctors craft treatment plans tailored specifically to patients. My own doctor’s office is using AI to answer customer questions over chat, granted the older generation prefers to speak with someone personally so it’s not eliminating jobs at this point its refining our practices and making businesses more efficient.
When I worked with Workday, we talked a lot about improving hospital operations, but I never imagined that data could go beyond just tracking and organizing patient information. AI has taken that data and turned it into actionable insights, leading to more precise treatments, especially in oncology and genetics.
AI in Predictive Analytics: Prevention Over Reaction
When I was helping healthcare providers adopt data management systems, the focus was primarily on improving operational efficiency. Today, AI is enabling something even more groundbreaking: predictive analytics. AI can analyze patient data to predict future health events, such as heart attacks or strokes before they even happen.
For instance, AI tools can track vital signs and predict the risk of sepsis in real time, allowing healthcare providers to intervene before it’s too late. This shift from reactive to proactive healthcare is a game-changer. It’s a leap forward from the days when we were simply managing data. Now, we’re using AI to actively prevent illness.
The Future of Healthcare: Cloud, AI, and Beyond
Looking back, I’m amazed at how far we’ve come from those early days of remote data hosting. Now, we have cloud-based infrastructures that enable seamless data sharing, enhanced security, and far greater computing power, all of which are crucial for AI to function effectively. Healthcare is becoming smarter and more efficient, with AI driving faster diagnoses, personalized treatments, and predictive care. At the same time, as AI becomes more embedded in healthcare, we must address challenges around bias, trust, and ethics to ensure equitable and effective care.
As someone who has spent years working in the healthcare software space, I find it exciting to see how AI is transforming healthcare in ways that would have seemed impossible two decades ago. From a time when hosting data remotely was a groundbreaking concept, we’ve arrived at an era where AI revolutionized the way healthcare providers diagnose, treat, and manage patient care. However, even with AI’s advancements, people will always remain central to healthcare, as it is an industry fundamentally about human care. The next challenge is how different generations adapt—while younger professionals seamlessly integrate AI into their workflows, some, like my mom, still resist even carrying a smartphone!
Meanwhile, competition among major healthcare software players continues to evolve, with Oracle eclipsing Infor and Workday to maintain their edge. Figures like Eric Lefkofsky, the Founder and CEO of Tempus, are at the forefront of integrating AI into healthcare. Under his leadership, Tempus is building the world’s largest library of molecular and clinical data, coupled with an operating system to make that data accessible and useful to physicians. This initiative aims to enhance precision medicine by leveraging AI to provide personalized treatment options for patients. I look forward to what’s next!
