Vijayashree Natarajan is senior vice president and chief technology officer at Omega Healthcare, which produces financial, administrative and clinical systems for healthcare organizations.
Given her extensive expertise in healthcare information technology, we recently asked her to look ahead to 2025 and describe three key trends and imperatives she will be watching that will also be of great interest to senior systems executives healthcare and other healthcare IT experts. She chose three: cybersecurity, cancer informatics and agentic artificial intelligence.
Q. Why do you think there is a need to emphasize data security in 2025?
AND. As healthcare continues its digital transformation, we will see clinical data, revenue cycle operations and patient care become increasingly interconnected. Organizations that can effectively leverage these data streams while maintaining data security will be best positioned to thrive as healthcare continues to change and become more patient-centric.
The journey into this future will require continued collaboration, innovation and an unwavering commitment to patient safety and data security.
As the healthcare IT industry increasingly leverages artificial intelligence and other digital technologies, the importance of forceful cybersecurity measures cannot be overstated. The healthcare industry faces unique challenges due to the sensitivity of data – from personal data to electronic health records to electronically protected health information.
Healthcare organizations need comprehensive micro-segmentation of applications, server workloads, and users of all types of resources.
Q. Cancer informatics is an compelling choice for 2025. Why this area HIT?
AND. The demand for cancer informatics will grow as the CDC says the total number of cancer cases is expected to enhance by 50% by 2050.
As cancer rates continue to rise, there will be an increasing focus on the need for high-quality data, or “cancer informatics,” to support cancer-related public health initiatives.
However, the exponential growth and increasing complexity of cancer data pose significant barriers to treatment. Data come from a variety of sources, including clinical records, pathology reports, imaging studies, and genomic data.
Skilled professionals must take a comprehensive approach to accurately integrate these disparate data sets and extract valuable information. This information then influences key follow-up actions such as precision medicine techniques, public health surveillance, recent treatment guidelines and policy recommendations, clinical trial enrollment, and clinical trial ideas.
The growing importance of solid clinical data cannot be emphasized enough. As we move forward, the focus will be on developing solutions that not only improve data processes, but also generate recent insights that drive clinical and operational excellence.
By integrating creative technologies with deep industry knowledge and keeping people up to date, we can set the stage for a recent era in health care – one in which data-driven decisions pave the way for better patient outcomes and more effective and accessible health care services.
Q. Finally, you suggest that agent-based AI will be crucial in 2025. How so?
AND. For providers and payers, AI is becoming key to minimizing fraud, improving value-based care, and creating insights to assess risk and identify gaps in care. The development of generative AI is expanding these capabilities, improving everything from patient interactions to physician documentation and even improving the AI algorithms themselves.
In the future, we anticipate that technologies such as agent-based AI will play a key role in increasing efficiency, adapting therapies and improving patient outcomes.
When implementing artificial intelligence systems, healthcare organizations should prioritize:
- Establishing a dedicated AI oversight team
- Developing contingency plans in the event of potential system disruptions
- Providing comprehensive staff training and support
- Implementation of timely monitoring and reporting tools
- Establish solid data management policies
- Using predictive analytics to anticipate potential problems
While these developments are electrifying, implementing AI in healthcare comes with its own set of challenges and considerations. Organizations must carefully manage risks related to data privacy, security and the integration of AI into existing workflows.