As we wrap up another year and get ready for 2025 to begin, it is once again time for everyone’s favorite annual tradition of Health IT Predictions! We reached out to our incredible Healthcare IT Today Community to get their insights on what will happen in the coming year and boy did they deliver. We in fact got so many responses to our prompt this year, that we have had to narrow them down to just the best and most interesting. Check out the community’s predictions down below and be sure to follow along as we share more 2025 Health IT Predictions!
Check out our community’s Healthcare Data and Healthcare Analytics predictions:
Russ Fendley, Senior Vice President, Public Sector and Payer Sales at HHAeXchange
Healthcare organizations are prone to data silos because each state they operate in might have different standards and regulations. Additionally, individual plans often have unique processes, which can result in variations, efficiency challenges, and data aggregation inconsistencies. If organizations, such as MCOs, have their own corporate aggregator, they can compare homecare costs, cost avoidance, and payments across their entire book of business.
Looking ahead to 2025, we will likely see more healthcare organizations move toward a centralized data aggregator to help streamline and standardize their handling of the growing homecare spend, identify areas for cost avoidance, and improve overall care quality across their whole operation, from the top and down to individual plans.
Derek Streat, CEO at DexCare
With rising demand, physician burnout, and razor-thin margins, health systems face a critical challenge: expanding access, maximizing limited providers, and strengthening financial health, all without further straining resources. The answer lies in harnessing data. By making sense of fragmented datasets, health systems can orchestrate care with precision, routing patients to the right setting at the right time. And this isn’t just operational efficiency, it’s about delivering better experiences for both patients and clinicians.
In 2025, I’m bullish on AI as a catalyst to unlock healthcare’s data potential. Systems that embrace real-time orchestration will dynamically match capacity with demand across clinics, virtual care, and nursing resources to ease workforce pressures, close coverage gaps, and turn margins from survival to growth. Next year isn’t about keeping pace, it’s about building smarter, more resilient systems.
Kazu Okuda, MD, Founder and CEO at Universal Brain
In 2025, more psychiatrists, neuroscientists, and clinical development programs will help grow the burgeoning field of precision psychiatry, which is data-driven and based on analysis of objective, interpretable biomarkers that help clinicians identify subtypes within common conditions, such as depression. As previous studies have shown, quantifiable biomarker data, such as brain activity measures, enables targeted, personalized, and effective treatment and accelerates improved outcomes.
David Lareau, CEO at Medicomp Systems
2025 will mark a critical shift from AI experimentation to standardization in clinical settings, with healthcare organizations implementing strict validation protocols to ensure AI tools are trained on real patient data rather than synthetic datasets. We’ll see the emergence of ‘trusted AI networks’ where healthcare organizations share validated clinical algorithms and outcomes data, creating a foundation for true interoperability. The focus will move from deploying isolated AI tools to creating integrated clinical intelligence platforms that combine decision support, documentation improvement, and patient engagement while maintaining human oversight.
Ronen Lavi, Co-Founder and CEO at Navina
In 2025 and the coming years, clinical AI will tackle some of the industry’s most pressing pain points, particularly data overload. The overwhelming amount of patient data has long posed a serious challenge for clinicians. In many cases, the increasing adoption of AI solutions has only led to an even larger growth in data, adding to providers’ cognitive burden rather than alleviating it. The AI solutions that succeed will be those that help providers interpret vast datasets, transforming raw data into insightful, context-specific information that enhances decision-making, improves patient outcomes, and reduces unnecessary workload. AI’s transformative potential in healthcare lies in its ability to integrate and analyze data across multiple modalities, speech, text, visual, and sensor data from medical devices unlocking new opportunities for care.
In 2025 and beyond, AI will push the boundaries of traditional modalities, enabling the synthesis of complex datasets like ambient data, physical exam findings, and even biometric inputs. This multi-modal approach will allow AI not only to see and hear but also to deeply understand and capture the complete picture of each patient’s health. Accessing these diverse data streams will also enable precision medicine that tailors treatments to individual patients with unparalleled accuracy. With AI’s ability to interpret and act on these data-rich, previously inaccessible modalities, patient care will be more personalized, holistic, and effective.
Maurine Gilbert, Director of Client Engagement at VITL
In 2025, we anticipate a shift in how patients engage with their healthcare data. Patients increasingly demand, and deserve, unfettered ownership and control over how their information is shared and protected. This is particularly important to them when it comes to sensitive data, such as reproductive health data, substance use disorder data, and other data that has special privacy concerns. Patients need assurances that their health information is safeguarded, and they want a voice in deciding how and with whom that information is shared. It’s important that healthcare organizations and health information exchanges meet this expectation by prioritizing transparency, continuously strengthening their cybersecurity infrastructure, and adopting patient-first policies that enable better control and trust. It’s clear that the future of healthcare data isn’t just about access, it’s about trust and protection.
Shobha Phansalkar, PhD, FAMIA, VP of Client Solutions and Innovation, Health Language at Wolters Kluwer Health
While 2024 may have been one of the biggest years of transformation in healthcare when it came to the use of AI, the same thing that held us back when EHRs were first mandated nearly 20 years ago hinders the progress of healthcare today: bad data. Amid the desire for rapid transformation, organizations can’t forget the importance of this fundamental currency that will power future discovery and insights. Without a system in place that can help assess, clean, maintain, and organize data, health systems will be hindered in their ability to leverage AI effectively, make informed decisions, and unlock the full potential of technology to improve patient outcomes, operational efficiency, and innovation in care delivery.
Anne Donovan, Vice President and General Manager of Health Language at Wolters Kluwer Health
We’ve seen a notable uptick in the use of artificial intelligence at the point of care to improve patient-provider interaction, increase efficiency, and streamline workflows, but we can’t just capture more data through AI or otherwise for the sake of documentation. We need to be purpose-driven in thinking about how the data will be used within the healthcare system to facilitate care and financial-related considerations between providers and payers. To ensure the meaningful exchange of health information, organizations need to proactively design strategies that share data while maintaining the intentionality behind the data capture.
Ashley Franks, Chief Nursing Informatics Officer at TigerConnect
Hospitals will focus on nursing as they step into the world of artificial intelligence (AI). Predictive analytics will begin making bedside staff proactive in delivering care instead of largely reactive, coordinating consults and testing much faster than in the past. By drawing on the immense data resources of the hospital and medical science, AI can empower the nurse to detect conditions such as sepsis and other complications before they become full-blown crises. Bedside staff can coordinate care in addition to delivering it.
Timi Leslie, President and Executive Director at BluePath Health and Connecting for Better Health
In 2025, we anticipate that data usability will become increasingly important, not only in making sure that networks can connect but also that clinicians and providers can appropriately use and apply this information in clinical and social service settings. We predict that in the year ahead, providers and clinicians will have an increasing influence on data-sharing design usability, visibility, and access.
B.J. Boyle, Chief Product Officer at PointClickCare
The premise of AI in healthcare is largely centered on creating greater efficiencies and clinical decision support for care teams. The integrity and free flow of data is a key part of the equation. In 2025, adhering to federal data-sharing standards will become increasingly important when it comes to advancing AI use cases in a highly regulated industry. While this will require greater upfront investment, secure data exchange is table stakes for patients and providers in today’s increasingly connected world.
The efficacy of AI use cases, including automated documentation and predictive modeling, will be highly dependent on the quality of data feeding the models on which these processes run. What’s more, the speed at which data is shared across the continuum will be augmented with the help of AI and fueled by a complete picture of each individual patient. As such, we will see more frequent intersection points between interoperability and AI, with one hand feeding the other to improve patient outcomes at scale in 2025. Providers will also demand a more responsible infrastructure and expect more fluid, bi-directional learning between humans and technology to ensure safer and more secure interoperable data.
Mitesh Rao, MD, Founder and CEO at OMNY Health
We’ll continue to find that the biggest priorities in data lie within security, compliance, and patient safety. As an industry, we’re beginning to see a real increase in the scale of use for data in healthcare, and AI is at the center of that movement. Looking at the vast supply of healthcare data, a large portion remains greatly disorganized, or unstructured. But within the unstructured data, buried deep down, you’ll find powerful insights that could be transformative in R&D. Unlocking the hidden world of healthcare data that people traditionally overlook is where some of the greatest insights can be found.
Sanjay Subramanian, SVP and Head of the Healthcare Payer Business Unit at Cognizant
Emerging technology will connect payers and providers more seamlessly to drive real-time workflows and decisions. By bridging clinical, administrative, and business data with secure, standards-based technology platforms, payers and providers can reduce data silos, administrative burdens, delays, stakeholder friction, and cost, and empower providers and payers to make decisions in real-time rather than days, months, or weeks later. Employers and payers will need to develop the API technology that will connect systems between employers/payers, the federal government, and providers to enable the data transparency CMS will require. Significant spending in healthcare IT budgets and partnerships between healthcare and technology companies is likely on the horizon to support digital transformation efforts.
Ryan Chapin, Executive Director, Strategic Solutions at AGS Health
In 2025, I anticipate that healthcare providers will increasingly adopt predictive analytics to stay ahead of increasing payer denial trends. By analyzing data before and after billing, they’ll work to prevent denials before they happen and/or proactively prioritize denials with the highest return on investment. We’ll also see more payer-facing AI calling technology, with the ability to gather complex information from payer representatives, whether they’re bots or humans. This will streamline tasks like denial overturns and authorization checks. On the automation front, I expect continued advancement for AI handling both clinical and non-clinical appeals, drafting appeal packets that humans review before submission.
Elad Walach, CEO at Aidoc
In 2025, we anticipate an accelerated adoption of clinical AI across health systems, driven not only by new guidelines but also by a deep body of clinical evidence that addresses longstanding barriers to implementation. This momentum will go beyond incremental gains given health systems are increasingly consolidating AI solutions into cohesive platform strategies, moving away from single-purpose point solutions. Foundation models are emerging as the backbone of this shift, fundamentally transforming healthcare’s digital landscape. These models will enable earlier detection of complex conditions.
By the end of 2025, we expect foundation models to unlock unprecedented clinical insights from vast, untapped datasets, fully realizing AI’s potential in healthcare. This shift will allow care teams to scale their expertise more effectively, transforming even the most complex imaging data into precise, actionable insights tailored to each patient. As these advancements take root, AI will drive healthcare toward a more predictive, personalized, and preventive model, setting a new standard in patient-centered care.
Thank you so much to everyone who took the time out of their day to submit a prediction to us and thank you to all of you for taking the time to read this article! We could not do this without all of your support. What do you think will happen for Data and Analytics in 2025? Let us know on social media. We’d love to hear from all of you!
Be sure to check out all of Healthcare IT Today’s Data and Analytics content and our other 2025 Health IT Predictions.
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