Predicting specific developments in health care informatics for 2024 is challenging, but trends suggest continued advancements in AI-driven diagnostics, personalized medicine, and enhanced interoperability for seamless data exchange among health care systems. The emphasis on cybersecurity to protect sensitive health data will also likely increase.

AI-driven diagnostics are likely to see advancements in accuracy and efficiency. Improved algorithms will enable faster and more precise analysis of medical data, such as diagnostic results and patient histories, to enhance the accuracy and precision of diagnostic suggestions. Integrating AI into diagnostic tools may lead to earlier detection of diseases and personalized treatment recommendations, contributing to more effective health care outcomes. Additionally, clinicians can leverage AI in their decision-making processes.

Personalized medicine is expected to progress, leveraging genomics, AI, and data analytics advancements. Integrating comprehensive patient data may enable more precise treatment plans tailored to individual genetic makeup and lifestyle factors. Innovations in targeted therapies and the development of biomarkers could enhance the effectiveness of treatments, leading to improved patient outcomes. Ethical considerations and regulatory frameworks may also evolve to accommodate the growing field of personalized medicine. It would be interesting to see ethical dynamics in genetic information, disparities in access to personalized therapies among different populations, and the possibility of unintended consequences from targeted treatments that include:

Off-target efforts. Targeted treatments might inadvertently affect healthy cells or other biological pathways, causing unintended side effects or complications.

Incomplete understanding. Incomplete knowledge of the complex interactions within biological systems may result in unforeseen consequences when manipulating specific targets, potentially causing unintended outcomes.

Enhanced interoperability is likely to become more prevalent in electronic health record ecosystems. Improved standards and protocols may facilitate seamless communication and data exchange between systems and devices. This progress could lead to more integrated and interconnected technologies, fostering collaboration and synergy across diverse platforms. The potential risks of interoperability ecosystems can bring several risks, including:

Privacy concerns. Increased data sharing across systems may lead to privacy issues if not correctly managed, risking unauthorized access or breaches.

Data accuracy and quality. There is a potential risk for inaccurate or incomplete information transfer between systems, impacting the quality of patient data and clinical decision-making.

Workflow disruptions. Implementing interoperability features disrupts an organization’s workflow, leading to inefficiencies or resistance from health care professionals.

Legal and regulatory compliance. Adhering to various regional, national, and international regulations can be complex when sharing health information across diverse EHR systems, and there could be legal challenges.

Integration costs. The initial investment and ongoing costs associated with integrating diverse EHR systems can be substantial, posing financial challenges for health care organizations.

Developments in AI and cybersecurity in 2024 will rapidly evolve the field. Several trends and potential directions can be considered in the health care IT world.

Privacy-preserving AI. With increased focus on privacy, advancements in privacy-preserving AI techniques could allow organizations to leverage AI for cybersecurity without compromising sensitive data.

Collaborative defense platforms. Collaborative defense platforms that enable the sharing of threat intelligence and coordinated responses among organizations may become more prevalent. AI could facilitate the rapid sharing and analysis of threat data.

Regulatory changes and standards. As AI in cybersecurity becomes more integral, regulatory frameworks and industry standards may evolve to address AI technologies’ ethical and security implications. Compliance requirements may be refined accordingly.

Afua Aning is a physician informaticist.