The pandemic: a spur for digital health tools and research

Increase in remote delivery of healthcare services

Before the pandemic, there was mounting interest in services enabling the remote delivery of healthcare. Technology companies were collaborating with pharmaceutical companies and healthcare facilities on the development of “Internet hospitals”, remote GP and pharmacy interactions, remote disease monitoring applications, remote rehabilitation services, and wearables to deliver healthcare services.

With the Covid-19 outbreak and associated social distancing measures, many countries have recommended that front-line healthcare personnel prioritise telephone or teleconference appointments. Policy changes have provided opportunities for a broader uptake of telemedicine solutions. The U.S. Federal Communications Commission (FCC) has established a programme of funding to help healthcare providers provide connected care services to patients in their homes and other locations. The U.S. and Australian governments have approved reimbursement for telemedicine consultations. The UK Government has launched a coronavirus “chatbot” to reduce in-person contact and relieve pressure on the National Health Service (NHS).

In addition to the rapid and widespread adoption of these technologies generally, we are seeing Covid-19 specific applications. For example, in England, the NHS has partnered with a tech start-up to study patients recovering from Covid-19 at home using remote-monitoring technology.

The outlook for tech companies in the remote healthcare space is strong. Now established, for many patients a digital delivery of healthcare will be a preferred route going forwards. It will be in the interests of all stakeholders that regulatory frameworks are fit for the long term and appropriately address issues such as qualification/licence requirements, adverse drug reaction, reporting obligations, liability concerns, interoperability of local systems with public systems, reimbursement, data protection and cybersecurity, amongst others.

Accelerating deployment of advanced technologies in acute healthcare settings

Internet of Things (IoT) and Artificial Intelligence (AI) were already a focus for acute healthcare services before the pandemic. We have seen the development of e-health platforms and record systems, connected devices to remotely monitor patients and highlight any decline to clinicians and the use of AI as triaging “chatbots” and models for diagnosis (such as GoogleHealth’s Streams app) and prognosis.

The pandemic is accelerating these trends. A mix of IoT and AI techniques are being used for hospital room monitoring, patient tracking, device management, and hospital equipment tracking. Other, more novel, applications of AI including the triaging of Covid-19 patients – in China, Alibaba has launched an AI algorithm which can diagnose cases within 20 seconds (almost 45 times faster than human detection) with 96 per cent accuracy. Likewise, with healthcare systems understaffed and the volume of radiology scans sharply increasing with the peaks of the pandemic, AI is being used to diagnose Covid-19 patients by identifying pneumonia and lung damage from radiology scans. Not only are these AI algorithms often faster and more accurate, they facilitate social distancing and ease healthcare staff shortages.

Whilst certain applications are Covid-19 specific and will not outlast the pandemic, most will. Whilst there is a clear case for the efficiencies these tools bring to healthcare systems, technology providers must demonstrate their product’s compliance with the medical device regulatory framework (including being certified as a medical device) where relevant; even if the product is not a medical device, it may need to comply with various ISO standards to be adopted into the healthcare setting. In any event, technology providers must be mindful of the potentially more significant product liability risk associated with such products. Consideration will also need to be given to local legal and ethical requirements for healthcare technology, such as the NHS’ Digital, Data and Technology Standards (currently in draft form), new guidelines regarding the ethics of AI, and clinician and patient “buy-in” to continuous monitoring and surveillance.

Transforming regulatory approval processes

The shortcomings of procurement in many healthcare systems during the Covid-19 outbreak have provoked controversy. Many facilities have faced shortages of masks, gloves, and other personal protective equipment, as well as other medical devices such as ventilators. Different causes can be cited, such as a lack of strategic reserves, weak coordination between government authorities, logistical issues caused by lockdowns, and complex procurement processes.

Here too, novel technologies have helped. They have mitigated the impact of low equipment reserves through, for example, the use of 3D printing to produce masks, gloves, and ventilators. TMT and life sciences companies have worked collaboratively with regulators to develop new products to meet demand.

We have seen regulators re-examine their approval processes and flex these considerably to facilitate accelerated approval times; often relying on exceptional powers to relax existing laws, while still ensuring patient safety. These interim changes may have lasting effects – allowing regulators to learn from recent experience and to reshape regulations and approval mechanisms to provide more agile and flexible regulatory oversight.

Renewed impetus on TMT in R&D

Before the pandemic we were beginning to see AI used to facilitate drug discovery; likewise the development of remote clinical trials facilitated by IoT devices. The potential to use IoT devices and AI to predict disease outbreaks was perceived as something of interest only to certain physicians and researchers.

Now these technologies are taking the global centre stage. The race for a vaccine or meaningful treatment for Covid-19 has seen increased pressure on pharmaceutical companies, who are increasingly turning to AI to try to accelerate traditional drug discovery by mining existing compound libraries, clinical trial data and open data sets to identify new targets. Similarly, the use of AI to mine public health data sets to identify which patient populations are most at risk of Covid-19 is increasingly important to allow governments to protect those individuals, minimise outbreaks and allow society to continue to function. With trial subjects unable or unwilling to visit acute care settings for monitoring as part of clinical trials for Covid-19 vaccines or treatments or otherwise, the use of IoT devices for remote monitoring to minimise such interactions will be crucial.

Given the interest in such technologies prior to Covid-19 and the ongoing concern regarding a potential “Disease X”, the uptake of these technologies is likely to continue. Technology providers will need to consider carefully the different landscape in which life sciences technologies operate, from different approaches to intellectual property rights and product development timelines, to understanding a myriad of regulatory, legal and ethical requirements.

Frameworks supporting digital health and data-driven research

As is well documented, governments and health authorities have been developing a raft of mobile applications to combat Covid-19. As creatures of national legal and political systems, these vary in functionality and privacy-intrusiveness, from providing information about the virus and testing, to monitoring the effectiveness of social distancing measures, to tracking individuals at risk and enabling the reporting of symptoms.

Open data sharing for medical research has been a feature of the scientific response to the pandemic. Ongoing initiatives include the European Commission’s European Covid-19 Data Platform, and Nextstrain, an existing open source platform that has been compiling genome sequences from laboratories worldwide. Private initiatives, such as the collaboration between HCA Healthcare and Google Cloud, have also been launched. Privacy advocates will want to see governance arrangements for these projects restricting data use once the current crisis abates. Others will hope that they can showcase the open data concept and accelerate broader adoption.