At Pivot Point Consulting, a consulting firm for health IT, Ranjan Sousa serves as vice chairman of the practice’s information, analysis, and artificial intelligence. ( It was ranked No. In 2024, KLAS ranked first best for Tried Services and Technical Services. His history and knowledge of AI and analysis are considerable. And he has a lot to say about these two technologies, which are so crucial to care, when asked to look forward to 2025 in wellbeing IT. As a result of using the two systems in tandem to push growth, Sesa predicts significant things for relational AI, a new way of shipping for AI and analytics. We spoke with him about the upcoming season, and this is what he had to declare. Q. You say in 2025 genAI may appear into its own, creating potential for significant savings. How is this going to occur? A. In 2025, genAI proof-of-concepts and aircraft programs will begin to explore ways to submit novel product investments or twilight existing ones by doing it themselves. These will begin to exhibit positive influence and value for healthcare organizations. GenAI’s ability to analyze structured and unstructured data to produce forecast and normative insights is most advantageous to areas like diagnostics, individual flow optimization, and operational tasks like billing and supply chain. Organizations will shift their traditional methods of investing in technology after these first successes, allowing them to delay new product acquisitions and step out legacy systems in favor of building custom systems internally. This genAI deployment will have its problems. Healthcare agencies will face barriers like data protection and ethics concerns, regulatory compliance, integration with existing systems, and the need for labor and individual training. Addressing these challenges may need strong, flexible data governance policies, investments in cybersecurity measures, proper planning for technology integration, and extensive training programs to adapt to new tools and workflows. By harnessing these superior abilities, health systems will uncover extraordinary profits. Automatic programming is drastically shorten the number of errors and processing times in claims management, resulting in quicker reimbursements and lower operational costs. Consensus prediction improves operational efficiency and patient care delivery by allowing better resource allocation and staffing decisions. As efficiency improves, patients will experience reduced costs, shorter wait times and higher-quality care due to more effective use of resources and personnel. The ongoing migration to the cloud, with its scalability, data-sharing capabilities and computational power, is the cornerstone of this transformation. genAI applications’ extensive data storage and processing requirements are supported by cloud infrastructure, facilitating seamless integration into existing workflows. However, this transition raises security concerns, particularly those relating to HIPAA and data breaches. Organizations will also need to learn how to use the numerous tools available to innovate with data while also learning how to effectively do this. Q. On another front, you suggest that there will be a new delivery model for analytics and AI in 2025. What is it, and what would it mean for healthcare? A. Legacy centralized, transactional approaches to analytics and AI delivery that are rigid, top-down and project-oriented will give way to a federated and collaborative model. The legacy approach is geared more toward a static environment and struggles to adapt to the changing demands of the current ecosystem of care. By contrast, the federated collaborative model empowers decentralized teams to make agile, real-time decisions. This shift is not only a response to technological advancements but also a cultural transformation, emphasizing trust, autonomy and cross-functional collaboration. Adopting a bottom-up decision-making structure more closely complies with the demands of care providers and patients at the moment. It makes it possible to create more customized, context-aware systems that address particular problems faced by various departments or units. This strategy promotes faster delivery of data products, reduces bureaucratic reluctances, and fosters innovation by encouraging structured experimentation at all levels of the organization. From an operational perspective, federated models can lead to significant productivity gains. Employees who are more apt to make decisions and make meaningful contributions to initiatives are more likely to be engaged and satisfied in their roles. In an increasingly competitive industry, this enriched work environment helps to attract and retain top talent as well as raise morale. This model is not without challenges. To ensure consistency, security, and compliance across decentralized teams, organizations must invest in robust, flexible data governance frameworks. Additionally, fostering a culture of collaboration and continuous learning is essential to realize this approach’s full potential. Nonetheless, those who can overcome these obstacles will succeed, and those who don’t will have to work up the pace will struggle. Q. You claim that the most influential organizations will use AI and analytics to drive growth in 2025. How will this be accomplished? A. There will be a lot of pressure to use AI and analytics to lower costs and increase profitability by removing redundancy and waste from the system as a result of the rise in competition, which will be driven by mergers and acquisitions. Leading organizations will counteract this relentless cost reduction effort by utilizing AI and analytics to boost growth and increase profitability, improving outcomes and enhancing the patient and provider experience along the way. Analytics and AI are not just effective means of lowering costs; they also function as potent stimulators of growth and boost profitability. A prime example lies in AI-enabled personalized medicine. AI can help tailor treatment plans to individual patients, improving clinical outcomes and boosting patient satisfaction, by analyzing sizable amounts of patient data. For instance, healthcare providers that use AI to improve cancer treatment pathways can improve patient recovery rates while enhancing their standing as experts in advanced care. Similarly, predictive modeling in revenue cycle management allows organizations to identify financial bottlenecks and improve revenue collection, creating new growth opportunities. For sustainable success, it is crucial to balance investing in growth initiatives with cost savings. Leading organizations achieve this balance by reinvesting the profits from efficiency gains in creative projects that advance their strategic positioning. These businesses use analytics to streamline operations while also funding cutting-edge research and patient-centered care initiatives. This dual focus has resulted in improved patient experiences and operational efficiency, leading to the company’s ability to grow and be profitable for a long time. By 2025, healthcare organizations will need to stay competitive with the help of several emerging AI and analytics technologies. Technologies such as generative AI for clinical decision support, real-time predictive analytics for operational management, and AI-driven digital twins will become increasingly important. Digital twins, for instance, enable healthcare organizations to simulate and optimize hospital operations, predict patient flow, and test new care delivery models in a virtual environment. However, achieving true interoperability, which seamlessly connects disparate data sources across the healthcare ecosystem, will be perhaps the most transformative focus area. This will allow organizations to generate holistic, actionable insights, ultimately improving care coordination, reducing costs and driving better patient outcomes. Leading positions in the healthcare industry will be those that successfully strike a balance between growth-oriented innovation and efficiency-driven cost savings. They will improve their financial health and establish a more patient-centered and provider-friendly healthcare ecosystem by strategically utilizing analytics and AI. Follow Bill’s HIT coverage on Linked In: Bill Siwicki
Email him: bsiwicki@himss .org
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