Exploring Data and Analytics in Healthcare: A Q&A With Joe Fabrizio, Healthcare Associate Practice Lead

Author: Wavicle Data Solutions

With more than 30 years of experience helping major enterprises manage and leverage data, analytics, and AI, Joe Fabrizio serves as Wavicle’s Healthcare Associate Practice Lead. He spearheads healthcare data initiatives and works with payers, providers, accountable care organizations, managed services organizations, and other healthcare companies to help them achieve their business goals using data and analytics.


Drawing on previous experience leading IT and transformation strategies in the healthcare industry, Joe brings an expert perspective on today’s healthcare data and analytics challenges and how new technologies are changing the field.


Keep reading to get to know Joe and discover how data, analytics, and AI are changing the healthcare industry. 


Q: How did you get started in the healthcare industry? What excites you about working with healthcare companies?


A: Almost 30 years ago, I was working in capital markets on Wall Street when I was recruited by a former associate to join a new startup that had a healthcare data management solution. After a few years of explosive growth with Wall Street firms, I was asked to help the healthcare business refocus and reposition. That was my first foray into healthcare.


It was an interesting transition. I originally thought it would be easy to leverage concepts from FinServ, but it wasn’t. Although there was some architectural crossover and my experience solving high-volume transaction processing helped, I needed to fully understand healthcare business problems and speak the language to establish credibility. It took some time and education.


The switch from helping people manage money to helping people take care of people was very satisfying. The industry has its challenges, and those challenges tend to make the news because they touch all our lives almost every day. But the most rewarding aspect of being in healthcare tech is helping organizations solve those problems and impact better business and patient outcomes.


Now, digital transformations are changing the business landscape and creating new, exciting opportunities. I find that it’s worth the effort to continue with data modernization to move up the data maturity curve in order to leverage the value of data assets in respect to reducing the costs of care and increasing quality and efficiency. In the end, there is a massive amount of impact we can make.


Q: What big challenges do you see the healthcare industry facing today? What role do data and analytics play in those challenges?


A: Challenges exist and always will, especially in areas such as legislative and regulatory change, managing cost and finding efficiencies, changing competitive landscapes, and finding new ways to manage chronic conditions. However, I think there are key areas where data and analytics can play a significant role.


COVID-19 changed everything. It exasperated old issues, highlighted new ones, and forced evolution in business models that drive technical innovation. This is especially true in areas like telehealth and remote care, retail health, staffing, and digital patient engagement. Workforce shortages and burnout, which had been getting worse over time, became a prominent issue. Social determinants of health, an expanding area of data analysis that helps organizations understand how better to serve certain communities and demographics, was also highlighted by the pandemic.


Another focus area is the impact of digital transformation on business, technology, and the people being served. As seen in other industries, understanding more about who your customers are, what they need, and how best to serve and interact with them can transform results. However, while digital solutions can improve how a business understands and interacts with its customers, they also create new data challenges. Organizations must strategically manage that data and leverage it as an asset that creates business value.


Of course, there is also an ongoing shift from treatment-based services to proactive wellness. This requires new strategies for patient engagement and provider compensation. Data and analytics have a role to play in predicting outcomes and behaviors, helping determine engagement channels and programs, understanding social determinants, finding and creating operational efficiencies, and managing workforce demands.


Clearly, the healthcare industry is facing a lot of challenges, and there are a lot of opportunities too. We haven’t even touched on the potential of generative AI for imaging analysis, clinical and diagnostic augmentation, speech-to-text processing during patient interactions, and automation. The future possibilities are endless, and the role of data and analytics will be critical.


Q: Many healthcare companies have been slow to modernize because of the strict industry regulations about patient privacy. Why is now the time to modernize?


A: Privacy and compliance are and always will be a factor to be managed.


When we talk about data strategy, depending on the industry, we may highlight defensive strategies or offensive strategies. Defensive strategies are usually focused on protecting data, and offensive strategies are focused on generating value from data.


Healthcare had to focus on defensive strategies first. Although that focus on protecting data remains necessary, at some point, you must decide to start embracing the offensive. It depends on your location on the data maturity curve and how comfortable you are with your systems and processes for security, privacy, and compliance.


There are external factors driving modernization, such as the explosion of data from digital transformation initiatives, the need to work differently to satisfy the needs of a new generation of customers, the industry’s low customer satisfaction rates, and the costs of chronic conditions. Right now, the U.S. spends more on healthcare than any other developed nation, but we remain near the bottom of the list in relation to outcomes. Data modernization and leveraging the value of data are part of the solution.


Q: Patient engagement and care are prime focus points for healthcare organizations today. How do analytics and AI contribute to new strategies for improving experiences and outcomes?


A: Wavicle has been working with B2C companies for years in the retail and hospitality sectors. We have proven models for how data, analytics, and AI can help a company understand its customers and track their sentiments across interactions and data sources to improve satisfaction and loyalty. Many of those models can be leveraged in healthcare as well.


While the desired outcomes are different in these industries – for example, in healthcare, we may be focused on the person’s health, the best way to engage to drive healthy behaviors, or how best to interact with the smallest cost-of-care footprint – the premise is largely the same. Plus, some outcomes, like loyalty, revenue, profit, and customer satisfaction, translate directly across industries.


Q: What’s next? What trends are on the horizon for 2024?


A: I am excited to have an impact wherever we can. In the short-term, I see two different tracks for healthcare data and analytics.


The first is for healthcare organizations at the beginning of their data and analytics journey. They need a partner like Wavicle to help them create data strategies, architecture, governance, and use case pilots. Those organizations are at the beginning, identifying how they can drive value from their data.


The other is for healthcare companies that have already made strong strides in their journey and moved up the data maturity curve. These organizations want to go further and derive more complex and valuable insights from more data. They have the chance to implement more complex algorithms and models, a need to manage their data better as volumes skyrocket, and the opportunity to experiment with the power, promise, and potential pitfalls of generative AI.


There is so much that can be done with an organization’s structured and unstructured datasets when proper data disciplines are applied and a group decides to stretch themselves. Machine learning and generative AI have opened new avenues for exploration, but to have an impact, these initiatives must be aligned with business objectives. That is true across the board, for every data project from modernizations to innovative advanced analytics initiatives.


I see huge transformational power in all these technologies, but everything returns to a single focus: driving better business and patient outcomes.



Wherever you are on the data maturity curve, Wavicle can help you level up. Get in touch with an expert today.