As global healthcare systems strive for improved patient outcomes, efficiency, and equitable access to advanced treatments, AI looks set to redefine healthcare as we know it. The AI market in healthcare is forecast to increase by USD 30.23 billion, at a CAGR of 33.1% between 2024 and 2029. The AI opportunity to transform the healthcare market is significant, from AI-powered models for improved diagnostic accuracy and more advanced procedures, to wearable sensors enhancing patient care, optimised hospital information systems and drug discovery.
Hospital and healthcare leaders realise they must embrace AI technology for increased efficiency and improved patient care. As an indicator of its importance, the UK Government has launched a £150 million procurement drive for AI solutions.
More specifically, Generative AI (GenAI) and advanced machine learning models have emerged to empower medical consultants and their teams and to unleash advanced research, diagnosis and patient care.
By exploring the opportunities of next-generation AI tooling and the potential application areas, healthcare leaders can build a roadmap for viable integration into consultant-led care and benefit from automation and insight.
Challenges facing today’s healthcare
There are mounting pressures on healthcare consultants today. They must stay abreast of an ever-evolving body of medical knowledge, handle increasingly complex patient populations, manage increasing amounts of information and deliver patient-centered care.
They face challenges across diverse areas of medicine. One minute they are advising junior doctors in complex decision-making and offering prognostic insights in oncology or cardiology, the next they are working to optimise orthopaedic recovery, pain management, rehabilitation, or fall prevention. AI provides an exciting route to drive efficiency and innovation.
However, taking advantage of AI technology means healthcare organisations must have their data in order. The sector is renowned for its disparate data sources and lack of secure data connectivity, which can result in information silos. Being data-ready isn’t simple, and there is a skill to reshaping the future of healthcare data, in harnessing and transforming raw data into actionable insights.
Getting data-ready for AI
Healthcare data is often fragmented, stored in electronic health records (EHRs), lab systems, insurance claims and more. Providing a single view of patient care means integrating these diverse data sources into a unified platform, offering multiple benefits. Seamless data integration provides a single view of data, real-time analytics offers patient insights and predictive modelling identifies trends to improve patient care and resource allocation. With a unified data source, teams across the entire healthcare organisation can work with the same data, fostering better communication and alignment.
While robust data governance is important, a data integration, analytics and decision-making platform enables healthcare organisations to make data-driven decisions that improve patient outcomes, enhance care coordination, streamline operations, and increase accessibility through data-driven decision-making.
This intelligent health platform leverages next-gen technologies such as AI, cloud computing, IoT, and advanced data analytics. Its flexibility makes it ideal for healthcare organisations looking to harness the power of their data and can be applied across various healthcare systems such as biopharma and medtech ecosystems, medication management, remote patient monitoring and virtual care.
How AI is enhancing medical consultant care
In progressive medical settings, AI-powered solutions are already in place supporting consultant-level care and being technically implemented within clinical workflows.
Here are five ways in which AI can support the role of healthcare consultants:
- Augmenting Clinical Decision-Making
AI-driven decision support systems can provide junior doctors and consultants with real-time summaries of relevant guidelines, emerging therapies, and complex clinical protocols. Gen AI models can distil huge volumes of literature, highlight dedicated treatments for rare diseases, and identify medication programmes tailored to the patient’s genomic and clinical profile.
- Streamlining Administrative Burdens
AI tools are able to retain extensive documentation, from distilling patient history into succinct notes to flagging regulatory guidelines. This means consultants can focus on priorities, such as complex decision-making and direct patient interaction. For instance, innovative tools such as FPT’s AI Scribe, a generative AI-powered Speech-to-Text solution, can transcribe spoken medical information into structured EHRs, a critical time-saver for consultants.
- Prognostic Modelling and Specialist-Level Insights
Advanced AI models can enable consultants to forecast patient trajectories and planning long-term care. For instance, in cardiology, AI algorithms can pre-empt arrhythmic episodes or detect orthostatic hypotension risk factors, preventing dizziness-related falls. In fact, FPT’s eCarePlus is an AI-powered solution that can analyse ECG and patient activity data to detect early signs of syncope and fall risks and improve patient safety.
- Next-Generation Care for Rare and Complex Therapies
To help consultants find breakthrough treatments, AI systems can continuously monitor research, clinical trials, and guidelines. These systems can highlight newly approved biologics for rare bone disorders and integrate personalised genomic data for dedicated therapies.
- Patient Engagement and Communication
GenAI can rapidly produce educational materials for patients, design treatment plans and increase adherence. Chatbots can support routine queries and appointment reminders, freeing up staff to focus on more complex patient requirements.
By integrating patient-reported outcomes, biometrics and system data, consultants have the right information to forecast episodes or predict complications, suggest interventions and review and revise care plans to improve patient care.
Considerations for ethical and successful AI
As AI technology advances, there are key considerations for building trustworthy AI in healthcare environments.
Adhering to ethical and regulatory considerations, such as the UK GDPR and Data Protection Act 2018, is essential for a healthcare organisation to build trust in its AI systems. Transparent algorithms and interpretability features are important to maintain clinician trust and auditable decision-making paths will ensure AI’s role remains advisory and accountable.
Supervision and validation by consultants will serve to enhance system performance over time. Continuous feedback loops can enable clinicians to endorse or reject AI suggestions, ensuring AI is optimised for optimal patient outcomes.
Above all, clinician training is essential for successful AI adoption, to be able to effectively interpret AI outputs, manage device interfaces, and discuss AI-guided recommendations with patients. With a clear remit for augmenting their capabilities, AI will work alongside its consultant experts to streamline workflows, personalise treatments, and improve patient safety and quality of life.
Mark Scrivens, FPT Software UK Chief Executive Officer, FPT Corporation
