AI’s role in digital health 

AI’s role in digital health 

AI has drummed up excitement across all industries in recent months, particularly in the digital health industry. Shameem C Hameed, Founder and CEO of blueBriX, a digital health tool, shares his perspectives on the present state of HealthTech, highlighting the seamless integration of AI solutions within the pharmaceutical sector and envisioning its future role. 

What role do you foresee AI playing within the healthcare sector in years to come? 

I believe that AI will play an increasingly important and exciting role within the healthcare industry over the coming years and – if developed and used correctly – has the capability to transform vital functions and improve the standards of healthcare worldwide.   

For example, where AI algorithms can analyse medical imagery and other diagnostic data with high precision, it can also accelerate the process of drug discovery, development and trials, all leading to improved patient outcomes and reduced healthcare costs.  

Furthermore, AI also has the potential to deliver personalised healthcare by analysing genomic data and other relevant information to tailor treatment to individual patients, while helping to predict and improve patient outcomes when such data is reviewed on a larger scale.  

However, the use of AI within healthcare isn’t restricted to improving patient outcomes. The right AI-powered tools are also likely to be used to deliver enhanced patient care, with IoT, wearable devices and AI-powered healthcare assistants on hand to provide remote support and patient monitoring; thereby reducing the burden on providers without compromising standards of care.  

Finally, AI will also have its part to play in improving operational efficiencies within healthcare settings by optimising workflows and streamlining tasks such as appointment scheduling and billing, while also helping to detect and prevent security breaches in highly sensitive data systems.  

It’s important to note that while the future of the healthcare industry looks bright with AI, the successful integration of AI in healthcare will rely heavily on collaboration between technology developers, healthcare providers and regulatory bodies alike. Furthermore, as AI continues to advance, ethical considerations and data privacy concerns will also need to be addressed to ensure the responsible and equitable use of AI in any healthcare setting. 

The digital health industry has accelerated significantly in recent years, do you believe that AI will be the biggest driver of this growth?  

AI is and will continue to be one of the major drivers of growth in the digital health industry from 2023 to 2030. However, it is not the only factor.   

While AI has the potential to revolutionise various aspects of healthcare, such as diagnostics, personalised medicine, drug discovery and remote patient monitoring, there are a number of different factors that will contribute to or be considered key drivers for the accelerated growth in digital health, with a prime example being ageing populations. 

According to the latest data from the World Health Organisation, one in six people will be aged over 60 by 2030, with the number of people in this age category forecast to more than double to 2.1 billion by 2050. As such, the global healthcare industry will be required to adapt to this demographic shift, ensuring it can effectively care for growing numbers of people with conditions that commonly develop with age.  

Advances in digital health, like AI-based solutions, could play a fundamental role in delivering remote or tele-based care to those with ‘geriatric’ conditions, therefore ensuring patients receive the support they need without draining the time and resources of healthcare professionals within hospital settings.  

With rising healthcare costs, increased demand for IoT and wearable devices, advances in genomics and precision medicine and regulatory changes also considered as key drivers for growth, it could easily be argued that AI offers the solution and will, therefore, be part of a broader ecosystem of factors that contribute to the overall expansion of the digital health industry.  

Do you think both healthcare professionals and end patients will trust the integration of AI into the healthcare setting? 

I think that both healthcare professionals and patients alike may be hesitant to trust AI-driven systems, particularly when it comes to critical decision-making processes. For example, although many people are amazed at what AI can do, most remain sceptical and do not trust in its capability, as demonstrated by the concept of self-driving vehicles. That said, the introduction of platforms like ChatGPT have started to shift this opinion in recent months, with many people now using AI as a tool for research and inspiration in both their professional and personal life.  

Ultimately, there is a lot to gain from AI in healthcare, particularly in emerging countries like India, where AI-based tools could deliver healthcare support, information and guidance en masse and at an affordable cost. The key to success is ensuring that the use of AI remains positive and that it is not subject to evil or misuse. 

What do you consider the main challenges for the integration of AI into existing digital health solutions and the wider healthcare setting? 

There are many challenges to consider when integrating AI into existing digital health solutions and the wider healthcare industry and I believe that the following are the most common and problematic. 

  • Data privacy and security. Ensuring the privacy and security of sensitive patient information is crucial when integrating AI into healthcare systems. Strict regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in the European Union, must be adhered to, which can be complex and time-consuming 
  • Interoperability. Healthcare systems often involve multiple entities, including hospitals, clinics, laboratories and pharmacies, each with its own data formats and systems. Integrating AI solutions requires seamless communication and data sharing across these entities, which can be challenging to achieve 
  • Regulatory approval. Obtaining regulatory approval for AI-driven digital health solutions can be a lengthy and costly process. Regulators need to ensure that these solutions are safe, effective and compliant with relevant regulations 
  • Technical expertise. Most pharma or healthcare providers do not have the internal skillset, resources or expertise in both tech and healthcare to develop, implement and maintain AI solutions that will effectively connect and integrate with their existing healthcare ecosystem 

These challenges are the very reason why the blueBriX platform exists. As the world’s largest library of configurable and compliant digital health components, the blueBriX platform removes these barriers to building impactful digital health solutions and in doing so has already benefitted the lives of over two million patients worldwide.  

You have recently launched blueBriX into the pharma industry. How does blueBriX help pharma providers better engage with healthcare professionals and improve patient outcomes?  

Over the last 14 years, we have built configurable digital health solutions for some of the world’s top 50 health systems, having successfully virtualised and enhanced clinical workflows on a large scale. 
 
Many patient engagement solutions created and launched by Pharma lack integration with existing clinical workflows, leading to a lack of adoption by healthcare professionals [HCPs]. This is where blueBriX steps in. In recognising that the adoption of a digital health solution by HCPs is often critical to patient adoption, we strategically bridge the gap between HCP and patient engagement solutions.  

The key to overcoming the industry’s most prominent challenges is the development of more relevant and useful digital health solutions that improve the patient engagement and experience, by driving behaviour change in lifestyle and treatment adherence to driving better treatment outcomes.