Greg Samios, President and CEO of Clinical Effectiveness at Wolters Kluwer, leading customer-led innovation and a transformed workforce.
The start of a new year is an ideal time for reflection and growth. In my world, this is an opportunity to think about the care continuum and how we can foster strong clinician-patient relationships, build on achievements and address areas that need improvement.
The healthcare sector is constantly evolving, with advancements largely driven by technology—particularly AI—alongside a heightened emphasis on patient-centered care. As AI continues its integration into healthcare, the conversation has shifted from potential to practical impact as we gain a clearer understanding of its advantages and challenges. In 2025, healthcare organizations and technology companies should consider these three things when embracing AI and generative AI (GenAI) to support a more efficient, accurate and patient-centered ecosystem.
AI Hitting The Mark In Some Areas Of Healthcare
When considering the integration of technology in healthcare, the priority is ensuring that clinicians receive the right information, in the right channels, at the right time. Clinicians seek speed when it comes to accessing accurate information and answers, as delays can directly impact care and, ultimately, patient outcomes. These fundamental principles help maximize the relevance and impact of clinical decision support, ensuring that information is received in a clear, actionable way at the moment when it’s needed most.
AI has identified new opportunities for healthcare organizations, and the focus has been on assessing how we’re adding value today. The applications are broad, from streamlining non-clinical administrative tasks to serving as a second set of eyes in the diagnostic process and lowering operational costs, among other things–all with an eye toward enhancing efficiencies and helping clinicians. Looking ahead, with care teams managing more patients than ever, dependable tools that help them with clinical decision making will be invaluable and should continue to be a focus.
A Bright Spot: Alleviating Clinician Burnout
AI holds significant potential in helping reduce clinician burnout, which remains a critical issue driving the healthcare workforce shortage. Burnout contributes to high turnover rates, which places greater strain on the remaining staff, perpetuating the cycle. For patients, clinician burnout can lead to decreased quality of care, longer wait times and increased healthcare costs.
Improving day-to-day workflows to maximize clinician efficiency is key. Health systems can enhance provider satisfaction by reducing time-consuming tasks such as notetaking, reimbursement, and documentation, therefore reducing pajama time or after-hours work. Intuitive, contextual and responsible content enhances provider satisfaction and enables effective patient communication. For example, ambient AI and other clinician benefits like EHR UI applications have been recognized as game-changers for clinicians. I believe these solutions will continue to evolve in the coming year and show promise in enabling better patient-clinician interactions and combating burnout.
The Path To Clinical Readiness For GenAI
GenAI shows potential for supporting clinical decisions, yet its full adoption depends on healthcare providers’ confidence in the reliability and rigor of its underlying data and recommendations. I don’t see this confidence quite there yet in the patient care setting, as there are reliability concerns relating to underlying content sets. In one survey, 91% of U.S. physicians indicated wanting to know clinical AI is sourced from medical experts. GenAI inaccuracies, or “hallucinations”—where models may produce incorrect or misleading information—underscore the need for reliable data and precision with a human in the loop.
Concerns are likely to arise the closer GenAI gets to the patient in the care continuum. Provider hesitancy reflects the priority for high-quality, consistent information that meets the critical standards required in patient care, which begins by identifying what responsible GenAI looks like. We must balance our excitement with caution when it comes to implementing GenAI in a healthcare setting. Human involvement builds patient trust, which is a vital component of patient adherence and satisfaction. Trusted clinical decision support content, when combined with active clinician involvement, is the only way forward.
Conclusion
Overall, I’ve noticed a general sense of optimism about the future of technology in healthcare. Realizing the benefits of AI in its various forms will rely on exploring current perceptions and taking advantage of opportunities to build trust in, and understanding of, this evolving technology.
As we embrace the innovations sparked by technology, the dual benefits of time savings and improved accuracy will work to enhance the landscape of patient care, paving the way for a more efficient and effective healthcare environment. The focus on reliable clinical decision support tools in 2025 will be a vital component to improving care for all.
Real action is needed from the entire healthcare ecosystem to develop and adopt tools that maintain clinical excellence while prioritizing innovative collaborations. Patients deserve the best care and support possible this year and every year.
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