The Future of Work and Developing the Kidney Care Workforce – Young Nephrologists Take the Leadjbrown
By Siddiq Anwar, ISN Young Nephrologists Committee and Middle East Regional Board member
End-Stage Renal Disease (ESRD) management has become a huge economic burden even in industrialized countries. In the USA, there are 750 000 Medicare members with ESRD, that’s 1% of the Medicare population that costs $42 billion per year – almost 10% of the Medicare budget. The Advancing American Kidney Health initiative, launched in 2020, was partly designed to control the burgeoning costs of managing ESRD.
There is a pressing need for a paradigm shift in nephrology where a limited workforce focuses energy on kidney disease prevention. Automation, machine learning (ML), and artificial intelligence (AI) have the potential to bridge the existing manpower gap and help free up the limited available workforce to do just that. It can also bring high-quality renal care to areas lacking trained personnel to help manage patients with renal disease.
In-center hemodialysis care is process-heavy and requires a lot of human input. Automation and other system engineering processes offer significant advantages, such as reducing data entry and analysis steps to help medical decision-making.
Our research groups collaboration with Dr. Mecit Simsekler, Assistant Professor in Khalifa University, explores innovative approaches and emerging technologies to help healthcare organizations transform their operation strategies, risk management processes, and organizational culture. Himanshu Upadhyay, a member of Dr. Simsekler’s research group, studied the impact of the COVID-19 pandemic on job hires by healthcare organizations in the West. This study indicates a shift in job hiring patterns that suggest health care organizations are shifting to telehealth and investing in data analysts.
Telehealth provides tremendous opportunities for regions and patients currently unable to access kidney health care. Predictive analytics and data modeling will help direct limited renal resources to patients who most need medical attention. Embracing new models of care improves disease detection, early access to specialist renal care, and disease surveillance, which, in turn, reduces costs for patients, hospitals, and taxpayers – improving overall health care outcomes.
Machine learning and artificial intelligence don’t just provide another avenue to improve the current care; they have the potential to bring high-quality renal care to regions where there are no trained renal specialists. Dr. Mohammad Yaqub, Assistant Professor at the Mohamed bin Zayed University of Artificial Intelligence, Dr. Simsekler, Mr. Upadhyay, and I are working on building the platform, RenAIssance to help implement ML and AI into Acute Kidney Injury (AKI).
Embracing emerging technologies and automation can help radically transform how renal care is delivered in the western world. Furthermore, it can bring high-quality renal care to parts of the world where it is currently unavailable. Renal training programs should help equip the next generation to become familiar with these technologies and embrace them in their daily practice to simplify the highly complex ESRD process, reduce costs, and improve renal care worldwide.