Originating from Wuhan City, China, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to over 200 countries and regions, infecting over 20 million individuals as of 12th August. Life as we know it has come to a screeching halt with extensive disruptions to every industry, and healthcare has not been spared. Even advanced health systems in Italy and New York have buckled under the pressure of the surge in high risk patients with respiratory illnesses, while others struggle with the need to constantly re-organise workflows and manpower to tackle the evolving pandemic situation.
These challenges have been further amplified by rampant misinformation and online falsehoods pertaining to the virus. The World Health Organisation (WHO) has labelled this phenomenon an “infodemic”, that has caused paranoia and fear-driven behaviors such as hoarding of protective masks and even toiletries like toilet paper in some regions. For those with active illnesses, a spectrum of behaviors has been observed. Many anxious-well patients have poured into primary care services for insignificant complaints. While at the same time, many with symptoms and high risk of SARS-COV-2 unnecessarily delay or refuse to seek medical care, placing others around them at risk.
The role of digital health and the pandemic crisis
These factors have created an immense communication challenge: how does one fine-tune messaging to these two very different abovementioned groups of individuals? Furthermore, healthcare providers have had to sift through large groups of at-risk and incoming patients to triage and identify those requiring urgent attention for non-SARS-CoV-2 illnesses as well as those at high risk of SARS-CoV-2 to prioritise their care. At the same time, they have to observe public health measures such as cohorting at-risk patients separately from those at low risk of SARS-COV-2, and manage the flow of patients within physical healthcare premises to minimise risk.
Fortunately, digital health solutions such as big data, artificial intelligence, telehealth, and online health communities (OHCs) have risen to this challenge. Many of these gained prominence over the past decade through clinical validation pilots and regional trials at the level of the clinical micro- or meso-system. Moreover, teams around the world have been able to leverage their limited experience with these trials to develop responses to the pandemic, and rapidly share experiences in a globally collaborative manner. The following sections delve deeper into each of these digital health categories, several applications in COVID-19, and limitations that need to be addressed, concluding with the road ahead.
Data about human populations and infrastructure has always been there, albeit readily available in analogue or disseminated piecemeal datasets. However, with the revolution in digital data management platforms, these large repositories of data can now be aggregated to create value. In healthcare, these can provide new insights of trends at the level of clinical macrosystem or triangulate on individual patients to better understand factors contributing to their outcomes and develop targeted solutions. During COVID-19, applications of big data that have been described include informing public health recommendations, generating informative visualisations of outbreak clusters for providers to triage patients, and identifying high risk individuals. They were even used to identify potential gaps in the detection of imported infections to bolster our surveillance systems.
Moreover, they were used by scientists in many countries to identify potential molecular targets for new tests and treatments using digital repositories of respiratory viruses (such as virological.org) and/or that of FDA-approved drugs, even before they had biological samples from their first confirmed cases to work with. Limitations that will need to be addressed to enhance the spectrum of applications include design enhancements to highlight pertinent trends and draw the attention of human users to key data points such as travel history amidst all the noise.
Artificial Intelligence (AI)
After surmounting the hype cycle’s infamous “trough of disillusionment” clinical AI has made tremendous leaps in various real-world applications throughout healthcare. Its applications have progressed in the past decade due to improvements in computing power as well as the availability of large big data repositories for training data, permeating all levels of clinical systems. At the level of the clinical macrosystem, AI has been used in COVID-19 for the prediction of potential therapeutic targets (such as Exscientia AI) as well as the surveillance of compliance to public health measures using data on human mobility as well as online behaviour such as google search trends.
There are also promising applications for individual healthcare services at the level of clinical mesosystem, whereby AI can triage of high risk patients and automate the monitoring of low risk patients, to direct the attention of healthcare professionals to those that need treatment the most. This has proven particularly useful for providers struggling to cater to the surge of in-bound patients with respiratory illnesses, whereby AI has been used to triage and identify high risk cases for SARS-CoV-2 using data such as pulmonary scans.
Finally, between individual patients and their healthcare providers at the level of the clinical microsystem, AI can leverage medical big data to make personalised recommendations to optimise treatment based on individuals’ biophysiological markets and phenotype. These various applications have great promise for translation to create value throughout healthcare. However, limitations of AI that still need to be addressed include the robustness of classification and exception handling, whereby studies have exposed abnormal behaviors or errors in classification that can be instigated by variations in input data.
Telehealth has been increasingly popular in healthcare with many of its embodiments such as video consultation platforms and mobile health apps playing a critical role in various responses to the SARS-COV-2 pandemic. From enabling remote triage of patients at high risk of SARS-CoV-2, to facilitating the continuity of care for patients with other unrelated illnesses, telehealth has greatly cushioned the disruptive impact of this pandemic on the provision of clinical services.
In many regions, the only barrier to large scale adoption had been regulatory restrictions and payment reforms. These were quickly addressed early in the pandemic in many nations including America and India. Subsequently, providers of these platforms have accordingly reported sky rocketing adoption providing millions of patients access to desperately needed care, creating massive value in the industry such as the recent announcement of the Livongo acquisition by Teladoc in America for a record 18.5 billion dollars.
As other operational barriers are similarly addressed in other regions, the use of telehealth will likely grow exponentially worldwide. However, even following adoption, many telehealth providers have struggled to expand beyond superficial applications as an alternative communication modality to the telephone. In order to attain deeper penetration within clinical care, telehealth providers will need to adopt participatory approaches with clinician experts to develop digital models of care that assimilate into practice and become embedded in professional clinical guidelines.
Online health communities (OHCs)
International organisations and governments have used static websites to convey regular outbreak-related updates, providing a channel for regular communication of evolving recommendations to citizenry as the situation evolves. However, the “infodemic” has seen a parallel propagation of misinformation in other digital communication platforms such as social media that has inundated populations and drowned out official communications. This has prompted calls for digital tools to counter the spread of misinformation and amplify official, reliable sources of information instead.
Fortunately, online health communities (OHCs), that have been gradually growing for niche applications such as patient peer-to-peer support in healthcare, have emerged as potential tools to address this need. Unlike telehealth solutions which provide avenues for private communication between providers and/or patients that are visible only to those involved, OHCs enable open communication that is visible to anyone who enters the website or application. Examples in the pandemic include Healthline in America as well as predecessors such as MedHelp, an early pioneer of web-based patient peer-to-peer support.
However, limitations of OHCs include a lack of regulatory oversight and variable quality of the digital platforms on the market. Caution should be exercised as these can just as easily become avenues for misinformation to spread. Therefore, this has created a persistent unmet need for open solutions that empower verified providers, whom are themselves regulated by professional medical bodies, as moderators of content and usage of these applications. Emerging solutions seeking to address this need include AskDr, a provider-managed platform launched in response to the pandemic in collaboration with volunteer doctors in Singapore.
The road ahead
Healthcare organisations in general have resisted the digitisation of clinical care for many reasons ranging from the risks to patient data and privacy, to unresolved questions about the quality of digital models of care in comparison with traditional practice. This has made the implementation of any form of digital care a tremendous challenge up until now, with only operational solutions and piecemeal clinical care applications filling the ranks of prominent digital health solutions.
However, Digital health, and telehealth in particular, has been a critical tool for responses in the SARS-CoV-2 pandemic. It was only availed to providers just in time during this crisis, with many health systems passing expedited regulatory approvals and payment reforms to facilitate adoption at the 11th hour. Reports of just-in-time solutions being developed to address the barriers to adoption have already been emerging, with more to come as front-line providers recuperate and have the opportunity to consolidate and share their experiences. The crisis has revealed the potential of these solutions to all key stakeholders in healthcare, and most important among them, patients.
The road ahead will likely involve more large scale implementation of these digital health solutions for healthcare services at the level of the clinical macrosystem, such as population screening programs and health behavioral modification. Other enabling technologies that are more recently gaining prominence will likely play a bigger role. These include 5G networks for low cost and high fidelity data transmission to improve telehealth applications and even telesurgery. Moreover, blockchain solutions may play a larger role for cybersecurity and access control in the context of growing healthcare data sets used in clinical care and/or used to develop enhanced digital health solutions.
Time will tell the winners and losers of this crisis, as organisations too slow to react to this paradigm shift in operations and consumer demand become obsolete in favour of those that quickly assimilate key solutions to enhance efficiency and maximise value for their current and prospective patients. The worst is still not over, with resurgences in several regions like Australia, the ensuing economic fallout, and impending surge in anxiety-related mental health disorders. However, many front-runners have already emerged, replacing conservative advisors with knowledgeable and digitally-literate leaders for digital projects to respond to the disruption of the pandemic. Ultimately, future generations will likely look back on SARS-CoV-2 as the historical moment that healthcare as a global industry finally crossed the rubicon to comprehensive digital transformation of clinical care.
About the author:
Dr. Dinesh Visva Gunsekeran
Senior Lecturer (Medical Innovation), National University of Singapore,
Physician Leader (Telemedicine), Raffles Medical Group, Singapore
Dr D.V. Gunasekeran reports investment in digital health solutions AskDr, Doctorbell (acquired by Mobile Health), VISRE, and Shyfts. He holds appointments as Physician Leader (Telemedicine) in Raffles Medical Group, as well as Senior Lecturer & Faculty advisor (Medical Innovation) at the National University of Singapore (NUS).
Further relevant readings:
A detailed overview of digital technology for COVID-19: https://www.nature.com/articles/s41591-020-0824-5
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