Features
Practising Clinical Medicine Under a Mask and at a Distance Utilising Available Technologies, Developing New Ones The demands of the pandemic have fast-tracked the uptake of digital health and the development of new technologies, or simply new ways of utilising existing technologies. The integration of digital health into our healthcare systems needs to go beyond the ‘emergency fix’ and be set against the long durée of its implementation in a complex system with the accompanying set of puzzles regarding access, security, privacy, workflow integration. It remains to be seen which technological innovations will outlive the pandemic and whether, for instance, populations will still be as willing to relinquish as large a degree of privacy as they have been during the crisis. Whether e-prescriptions are here to stay, whether wearables can continue to be adapted and repurposed for diagnosis as well as tracking. Whether telehealth is reimbursed at parity. What to do about an app that is manufactured for collection of health data by a company that falls outside the regulatory sphere that encompasses healthcare providers themselves.
The pandemic has not miraculously delivered a perfectly formed digital health system, however the exigencies of providing care ‘under a mask and at a distance’ have meant that data have been shared across the globe, as seen in the collaborative work of Dr Yuranga Weerakkody, and carers have come to be involved in consultations despite geographical distance as highlighted by Dr Sid Baxi.
What has been your experience practising your profession during the pandemic?
The necessary social distance of a clinical consultation during COVID-19 has been offset by the time and effort saved for patients in getting to appointments, the reduction in exposure to the risk of COVID-related illness for clinicians and medical staff, greater access to more complete health metrics provided by wearables and apps. There has been increased adoption of lifestyle and wellbeing apps in 2020, perhaps leading to ‘more prevention, less cure’ in a future where their use is commonplace.
We have had patients cancel and delay treatment, trying to balance up the relative seriousness of their tumour versus the risk of COVID-related illness.
We spoke to Dr Sid Baxi, Genesis Cancer Care, about his experience as a radiation oncologist in the past year.
Whether a deep learning based model to detect and classify COVID-19 cases from X-ray images can be used in remote places in countries affected by COVID-19 to overcome a shortage of radiologists.1
Dr Sid Baxi
10
Inside News
During the pandemic we have had to tackle a number of unique challenges not faced by us in the past. We have had to tackle patient fears of coming for treatment and patient fears of contracting the virus in high-risk hospital environments.
We have had to keep our staff safe and consider their safety with patients coming in and out of hospital from various regions and states. Having been part of a practice on the border, the cross-border issues and the closure and opening of borders ad hoc and quickly has resulted in us needing to be nimble and working out how to get our patients access to care when they lived across the border. Practising clinical medicine under a mask and at a distance has been challenging, practising it over the phone and via video consultations has been challenging.
Reference 1. Ozturk, Tulin et al. “Automated detection of COVID-19 cases using deep neural networks with X-ray images.” Computers in biology and medicine vol. 121 (2020): 103792. doi:10.1016/j. compbiomed.2020.103792
