AI-driven telemedicine: emerging trends in 2024

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Since the COVID-19 pandemic was declared in 2020, the world, and in particular the healthcare sector, has undergone significant transformation. To curb the spread of the virus, healthcare providers were suddenly challenged to find new ways to diagnose and treat patients. Telehealth emerged as a critical tool, enabling providers to manage an increased volume of patients remotely. According to the latest report from MarketsandMarkets, the telehealth and telemedicine market is projected to grow at a compound annual growth rate (CAGR) of 23.2% between 2023 and 2028. This remarkable growth is being driven by advances in technological infrastructure, evolving regulations and increasing acceptance among patients and healthcare professionals. As of 2024, the leading countries in telemedicine development include the United States (40% of total market volume), China (15%), the United Kingdom (8%), Germany (6%), Japan (5%) and France (4%). ‘The integration of artificial intelligence (AI) and telemedicine […] boosts medical care accessibility, efficiency, and quality’, states Sachin Sharma, associate professor in the Department of Computer Science and Engineering at Indrashil University, Mehsana, Gujarat, India. This synergy creates substantial opportunities for personalised healthcare solutions, including in teleconsultation, tele-expertise and telecare, by addressing specific patient needs. The goal is to overcome the limitations of restricted accessibility, fragmented records and communications, uneven quality of care, and challenges such as doctor shortages, expensive emergency care visits and high administrative costs.

AI-powered systems are transforming how medical data are collected, analysed and utilised, leading to more personalised, efficient and effective healthcare. According to the International Data Corporation (IDC), the healthcare industry is projected to generate approximately 2.5 zettabytes of data globally this year, following the generation of over 2.3 zettabytes last year. AI tools are increasingly automating the transcription and summarisation of doctors’ notes and patient records, significantly reducing the time spent on administrative tasks. Machine learning algorithms can process vast amounts of patient data – ranging from medical histories to diagnostic images – and identify patterns and anomalies that may elude human experts. The integration of wearable and implantable devices with Internet of Things (IoT) technologies enables real-time transmission of health data to clinicians, significantly enhancing remote patient monitoring. In the United States, approximately 41% of the population owns a smart wearable device designed to continuously monitor vital signs and other health indicators. This compares to about 30% in Europe and 25% in China, according to recent reports. Statista also estimates that there are currently around 300 million smart homes globally, which supports the integration of telehealth services with smart home devices and generative AI.

Using AI and machine learning technologies, remote patient monitoring (RPM) has become more integrated, making it possible to continuously monitor aspects such as blood pressure, blood glucose and ECGs in patients for chronic diseases. The ability of AI to analyse huge datasets supports predictive analytics that can be used to identify potential health risks, or even anticipate complications and personalise treatment remotely. AI is taking on a critical role in employing predictive risk models that leverage medical history and lifestyle factors to identify individuals at risk of specific health conditions. 

Thirty-five percent of telemedicine platforms now integrate AI functionality in order to improve diagnosis, patient management and operational efficiency. Chatbots and virtual assistants can be used by healthcare professionals to give patients information, remind them to take their medication, provide lifestyle guidance and improve patient engagement and adherence to therapy.  

As of 2024, AI-based telemedicine platforms are increasingly being used to monitor acute conditions, offering enhanced real-time assessment and intervention capabilities. According to Sharma, ‘AI plays a crucial role in enabling telemedicine to monitor acute conditions by analyzing patient data and providing timely alerts, ensuring faster and more precise responses to critical health changes.’ 

These platforms leverage advanced machine learning algorithms to detect early signs of deterioration, predict complications and optimise treatment protocols, reducing the need for in-person visits. This approach not only improves patient outcomes but also alleviates the burden on healthcare systems by enabling remote management of acute conditions such as heart attacks, strokes and infections.  

Tele-intensive care units (ICUs) represent a significant advance in modern healthcare, facilitating remote monitoring and management of critically ill patients by sharing crucial health data across hospitals. According to Sharma, ‘the potential of AI to enhance the capabilities of tele-ICU is considerable, as it can provide real-time analysis of patient data and aid in scientific decision-making.’ This integration allows AI algorithms to detect abnormal patterns in patient data, sending alerts for timely interventions and potentially preventing adverse events. AI can also be used to project patient outcomes, optimise resource allocation and predict the need for interventions such as mechanical ventilation. 

Similarly, telestroke systems enable neurologists to provide critical care to stroke patients in underserved areas. AI helps identify the severity and location of strokes through analysis of radiology images, guiding treatment decisions such as endovascular therapy. In telecardiology, AI enhances the remote diagnosis of cardiac conditions by analysing ECGs and imaging. As Sharma observes, this is of particular benefit to patients in rural areas, or those with limited mobility. 

In 2021, the global telemedicine market, which encompasses telemedicine software, hardware (such as kiosks and connected stations), associated services and technological infrastructure, was valued at approximately $67 billion. According to Mordor Intelligence, it is projected to surpass $185 billion by 2026, reflecting a CAGR of 20%. This significant growth is being driven by advances in technology, including in AI, wearables and virtual care models. By 2030, the market could exceed $350 billion as these innovations continue to expand. 

Currently, over 3,000 players operate within this market. Of these, 40% are platform providers, 25% are specialist software developers, 20% are manufacturers of connected medical devices, 10% are telecommunications operators and 5% are integrators and consultants. This diverse range of stakeholders underscores the maturing landscape of telemedicine, bolstered by AI, and its ongoing potential for innovation. 

The major players in telemedicine include Teladoc Health Inc. (New York, USA), Amwell Corp. (Boston, MA, USA), Doctor on Demand Inc. (San Francisco, CA, USA) and Sheba Medical Center (Ramat Gan, Israel). Collaborations between technology firms and healthcare providers are growing. For example, Carbon Health Inc. (San Francisco, CA, USA) and OpenAI Inc. (San Francisco, CA, USA) have collaborated on using AI for medical note generation, while Epic Systems Corp. (Verona, WI, USA) is working with data science companies to use patient data for enhancing healthcare outcomes.