COVID-19 has jolted the global discourse on public health into a rapid redo. To be or not to be is no longer a question or topic of debate for digital health. Embracing digital technology and data science for global health is the only way to reverse the pandemic in the short-term, and to make health systems combat-ready for the future ones.
Whether at the national or the global level, the game plan of each country will necessarily include technology-enabled defence and offence strategies to strengthen health systems. The paradigm of preparedness against future health threats will transform digital health; simultaneously, it shall also change the professional profile, skillset and toolbox of frontline health soldiers.
As governments across the world invest in expanding digital and mobile connectivity for integrating technology with health systems, an equally pressing question needs concurrent intervention. Is today’s healthcare workforce prepared to deliver a digital future? The answer is a straight ‘no’ on both dimensions of service preparedness, i.e., capacity and capability.
On global capacity, the total demand for health workers has always outpaced supply, with shortages varying between manageable to stark levels based on a country’s socio-economic status. With COVID-19 proving to be a brutal blow to the best-prepared health systems, health workforce capacity building has become a priority world over. An estimate by the World Health Organisation projects the global aggregate demand for 80.2 million health workers across 165 countries by 2030, whereas the current number is around 48 million.
Trained healthcare personnel, however, cannot be increased in a matter of months. It is a long-drawn process, which must begin soon enough to cover the shortage of millions of health workers. With economies slipping in a downward spiral, there is an added impetus to act quickly. It is well-established that investing in the health sector accelerates employment generation, especially for women and youth. There lies an opportunity to build the capability set of new entrants in health services based on future needs of health eco-systems. In years to come, the delivery and consumption of health will be more technology-driven than ever before. The profile of health workforce of each country must be aligned with the digital health priorities it sets for itself. While the exact construct will differ by country, the broad direction will be a combination of the principles outlined below.
For today’s health workers, digitalisation of health systems and implementation of the connected care blueprint in a localised manner will shape new ways of doing their jobs. It will be in a hybrid format, comprising physical and digital care of patients in varied proportions to maximise health outcomes.
Technology integration within clinical services and products will also create new types of jobs — to invent and handle public goods or medical products of future (new-age therapeutics, diagnostics and preventive health aides) using a combination of biology and computer science. They will fall at the intersection of medicine, genomics and engineering, using Artificial Intelligence (AI), Machine learning (ML), robotics, predictive analytics, and more.
It calls for urgent and parallel action by governments to kick-off upskilling and mindset rewiring of professionals in the medical and biopharma domains to adopt digital tools in their practice. The recent use case of telemedicine to deliver virtual care (force-started by COVID-19) is a glimpse into the future of model patient and physician behaviour on technology adoption. Yet, it is not fully reflective of the scale at which evolving trends in healthtech will define the speed and nature of skillset transformation for health workers in primary and tertiary care settings.
To drive the upskilling exercise, it is also critical to gauge the aptitude and willingness of today’s health workers to use technology in clinical decision-making.
Pre-covid times have seen stinging debates within the medical community and health policymakers on whether technology will strip healthcare off its essential nature — of being high-touch for effective patient care. Questions have been raised if AI tools will depersonalise medicine; if standard of care will dilute, or patient-centricity will be lost if AI/ML algorithms were to read radiology scans and vital signs to present clinical diagnosis or to predict disease prognosis. Legitimate doubts and ethical concerns on patient’s rights and data privacy have been brought forward. Most importantly, fair scepticism has been raised on safety and trustworthiness of algorithms due to inherent socio-ethnic biases and lack of situational context.
As a result, the digital health discourse has so far seen three types of participants: the Evangelists, who strongly believe that healthtech will catapult countries to meet sustainable development goals; the Cynics, who have raised many of the above questions; and the Opposers, who view technology as a threat to their careers or as an unwanted intrusion in the age-old, sacred practice of medicine.
Post covid, the narrative has stepped up considerably to gain the attention of the healthcare community around the world. The goings-on have led many Cynics and Opposers to shift their position into the solution-seeking quadrant, to coalesce into a new category of Constructive Critics. Together, the Evangelists and the Constructive Critics will form a powerful community to extract the most-balanced and effective benefits of digital and AI/ML technology in healthcare delivery, without diluting patient-centricity, data security and privacy rights. They will also be the change catalysts, who will lay down the foundation and constructs of the new system to work as inter-disciplinary teams, and to train and arm the workforce of today with digital skills.
As a long-term goal, cultivating aptitude and imparting new skills to create a digital-savvy health workforce of the future calls for considerable reform in the medical education system. This will need a redesign of curricula, training methods and skill evaluation techniques. In addition, student selection criteria and aptitude tests for clinical careers will have to be revamped.
Institutional frameworks of medical and nursing schools will have to create flexible claw-ins with technical education institutes to co-develop matrixed pedagogy programmes. For example, a medical science, nursing, or paramedical student would necessarily have to take credit courses in computer science, bio-engineering, mathematics or allied disciplines. Similarly, it will be essential for engineering and mathematics students to partake selective medical courses, to gain insights and orientation on experiences and challenges of patients and health workers in clinical settings — to conceive future digital products for the healthcare and life sciences sectors. Selection and training for primary health workers will also incorporate digital literacy as an essential requirement.
Few countries such as the UK and Australia had begun deliberation on their workforce strategy to enable digital health last year. For example, in 2019, the National Health Service, UK identified genomics, telemedicine and AI-based technologies as thrust areas to plan training and education of their future workforce.
To sum-up, the future will have inter-professional teams working in collaboration to co-create and monitor learning systems behind clinical decision making digital tools. Frontrunners for these roles will be the ones with a combination skillset in technology and clinical sciences or “techlinical”. All health workers will be digital-savvy to deploy these tools in care settings to improve patient outcomes. The combined effect of both will increase efficiency and effectiveness of delivery at a systemic level. As predicted by digital health evangelist, Dr.Eric Topol (Professor of Molecular Medicine, Scripps Research Translational Institute), use of AI and technology-aides in medicine will create time and space to deliver real healing to the patients.
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A biomedical researcher-turned-business leader: Columnist and Opinionator in health and policy: Start-up advisor and investor in Health and Life Sciences: Mentor at National Health Authoritys ...Read More +