Ryan Sousa is vice president of data, analytics and artificial intelligence at Pivot Point Consulting, a healthcare IT consulting firm. (In 2024, it was ranked first in the KLAS ranking in the managed services and technical services category). His experience and expertise in artificial intelligence and analytics is extensive. When asked to look ahead to 2025 in healthcare IT, he has a lot to say about these two technologies that are so significant to healthcare.
Sousa predicts gigantic things for generative AI, a recent way of delivering AI and analytics and using both technologies in tandem to drive growth. We interviewed him about next year and here’s what he had to say.
Q. You say that in 2025, genAI will become operational, creating the potential for significant savings. How will this happen?
AND. In 2025, genAI proof-of-concept and pilot programs will begin to demonstrate positive impact and value for healthcare organizations as they begin to explore how they can defer recent or terminate existing product investments by doing it themselves.
Areas such as diagnostics, patient flow optimization, and administrative tasks such as billing and supply chain benefit most from genAI due to its ability to analyze structured and unstructured data to generate predictive and prescriptive insights.
These early successes will prompt organizations to rethink time-honored approaches to technology investment, enabling them to defer recent product acquisitions and retire legacy systems in favor of building their own systems tailored to their individual needs.
Adopting genAI will not be without challenges. Healthcare organizations will face hurdles including data privacy and ethics issues, regulatory compliance, integration with existing systems, and the need for employee and patient education.
Meeting these challenges will require stalwart, scalable data management policies, investments in cybersecurity measures, strategic planning for technology integration, and comprehensive training programs to adapt to recent tools and workflows.
By leveraging these advanced capabilities, health systems will unlock unprecedented benefits. Automated coding can significantly reduce errors and processing time in claims management, leading to faster refunds and lower administrative costs.
Census prediction enables better resource allocation and staffing decisions, improving operational efficiency and the delivery of patient care. As efficiency increases, patients will experience reduced costs, shorter wait times and higher quality of care through more effective exploit of resources and staff.
The basis of this transformation is the continuous migration to the cloud, with its scalability, data sharing capabilities and computing power. The cloud infrastructure supports the enormous data storage and processing needs of genAI applications, facilitating seamless integration into existing workflows.
However, this transition raises security concerns, particularly around data breaches and compliance with healthcare regulations such as HIPAA. Additionally, organizations will need to learn to leverage the wide range of tools available to drive data-driven innovation, while also learning how to excel in financial operations to do so cost-effectively.
Question: On the other hand, you are suggesting a recent way of delivering analytics and artificial intelligence that will be introduced in 2025. What is it and what will it mean for healthcare?
AND. The legacy, centralized, transactional approach to AI analytics and delivery that is stiff, top-down, and project-oriented will give way to a federated and collaborative model. Legacy approaches were designed for a more unchanging environment and struggle to adapt to the lively needs of today’s care ecosystem.
In turn, the federated collaboration model enables decentralized teams to make agile decisions in real time. This change is not only a response to technological advances, but also a cultural transformation, emphasizing trust, autonomy and cross-functional collaboration.
Adopting a bottom-up decision-making structure allows you to better align analytics and AI initiatives with the immediate needs of healthcare providers and patients. It allows you to create more tailored and context-aware systems that solve specific challenges across departments or units.
This approach facilitates faster delivery of data products, minimizes bureaucratic delays, and fosters innovation by encouraging structured experimentation at all levels of the organization.
From an operational standpoint, federated models can lead to significant productivity gains. Employees who are empowered to make decisions and make meaningful contributions to initiatives are more engaged and satisfied in their roles. This enriched work environment not only boosts morale, but also helps attract and retain top talent in an increasingly competitive industry.
This model is not without its challenges. Organizations must invest in a stalwart and versatile data governance framework to ensure consistency, security and compliance across decentralized teams. To fully realize the potential of this approach, it is vital to support a culture of collaboration and continuous learning.
That said, those who can overcome these challenges will succeed, while those who don’t will struggle to keep up.
Q. One more look at 2025: You say leading organizations will leverage analytics and AI to drive growth. How will they do it?
AND. As competition increases driven by recent players and mergers and acquisitions, there will be significant pressure to leverage analytics and artificial intelligence to reduce costs and improve profitability by eliminating waste and redundancy from the system.
Leading organizations will balance this relentless focus on cost reduction by leveraging analytics and artificial intelligence to promote growth and greater profitability – improving outcomes and enriching patient and provider experiences along the way.
Analytics and AI are not just cost-cutting tools – they are powerful growth drivers that contribute to profitability. A perfect example is personalized medicine using artificial intelligence. By analyzing massive amounts of patient data, AI can assist tailor treatment plans to individual patients, leading to better clinical outcomes and greater patient satisfaction.
For example, healthcare organizations that exploit AI to optimize cancer treatment pathways can improve patient recovery rates while strengthening their reputation as a leader in advanced healthcare. Similarly, predictive modeling in revenue cycle management allows organizations to identify financial bottlenecks and improve revenue collection, creating recent growth opportunities.
Balancing cost reductions with investments in growth initiatives is critical to sustained success. Leading organizations achieve this balance by reinvesting savings from efficiency gains into inventive projects that improve their strategic position.
These organizations exploit analytics to improve operations while investing in cutting-edge research and patient-centered care initiatives. This dual focus delivered operational efficiency and improved patient experience, enabling the organization to achieve sustainable growth and profitability.
Looking ahead, several recent analytics and AI technologies will be critical to keeping healthcare organizations competitive through 2025. Technologies such as generative AI for clinical decision support, real-time predictive analytics for operational management, and digital twins based on artificial intelligence will become more and more popular. more and more significant.
For example, digital twins enable healthcare organizations to simulate and optimize hospital operations, predict patient flow, and test recent care delivery models in a virtual environment. But perhaps the most transformative area of focus will be achieving true interoperability – seamlessly connecting disparate data sources across the healthcare ecosystem.
This will enable organizations to generate holistic, actionable insights that will ultimately improve care coordination, reduce costs and deliver better patient outcomes.
Healthcare organizations that successfully balance performance-based cost reductions with growth-oriented innovation will emerge as leaders. By strategically using analytics and artificial intelligence, they will improve their financial situation and create a more patient-centric and provider-friendly healthcare ecosystem.