Entering 2024, the healthcare sector is witnessing significant changes, largely driven by rapid advancements in AI technologies.
Current predictions indicate a substantial growth in the global AI healthcare market, expected to rise from $15.1 billion in 2022 to an estimated $187.95 billion in 2030, with a compound annual growth rate of 37 percent. In this context, AI is more than just a tool; it’s becoming an integral part of healthcare, enhancing everything from diagnostic processes to the creation of personalised treatment plans. As we move through 2024, what emerging AI technologies in healthcare should we look out for?
The integration of AI into the healthcare value chain promises significant advancement across three areas:
Population health management: AI is set to revolutionise the way health systems manage and analyse population health data, such as identifying at-risk populations.
Improving operations: From automating administrative tasks to optimising supply chain management and resource allocation, AI can enhance efficiency, reduce costs, and improve patient experiences.
Strengthening innovation: Watch out for AI-driven advancements in drug discovery, personalised medicine, and advanced diagnostic tools. AI algorithms are becoming more adept at analysing complex medical data.
Within these areas, here are a few key trends to watch for in 2024:
Personalised treatment plans:
AI’s role in healthcare is becoming increasingly focused on personalisation. By leveraging individual health data, AI can provide customised treatment plans and lifestyle suggestions. This includes precision medicine, which tailors treatments to a person’s age, genetics and risk factors.
A notable area of promise is genomics, as highlighted by Forbes. Here, AI will be used to analyse DNA to diagnose and treat diseases and to create medicines that are fine-tuned to an individual’s genetic makeup. This approach promises more effective utilisation of medical resources and improved patient outcomes.
Generative AI
This game changer offers multiple applications. One of its key uses includes generating synthetic data that aids in training medical AI algorithms, thereby safeguarding patient privacy and helping in areas that lack real-world data.
In addition, generative AI not only powers chatbots but also guides virtual assistants, which are shaping up to be a major trend in 2024’s healthcare. Their roles are expanding to cover a wide range of tasks, such as handling queries about patient care and linking patients with the information they need to make informed decisions. These assistants are also streamlining healthcare management by interfacing with health records for easy appointment scheduling. Beyond logistics, they play a crucial role in ensuring patients stick to their medication schedules and health routines, like exercise and diet, by sending timely reminders. Interestingly, they're also stepping into a more empathetic role, offering companionship to those grappling with mental health issues or loneliness.
Remote-patient monitoring
AI-powered wearables are set to revolutionise remote patient monitoring by offering real-time health data to healthcare providers. This advancement is especially advantageous for managing chronic conditions. This trend extends to telehealth technologies, including video consultations, message-based communication between doctors and patients, health education, and seamlessly integrated electronic health records, making the management of healthcare issues more accessible and efficient.
Assisting with mental health
The World Health Organization reports that one in eight people globally are affected by mental health disorders. AI is becoming an essential resource in this field. It can help with diagnosing conditions, developing therapies, and crafting more personalised treatment strategies.
The 2024 Trends Report by the American Psychological Association highlights intriguing possibilities and raises some important issues, such as the potential of tools like ChatGPT in training mental health professionals through simulated patient interactions.