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The Future of Work in Healthcare: How AI Can Be a Transformative Force

“(The pandemic) is a portal, a gateway between one world and the next. We can choose to walk through it, dragging the carcasses of our prejudice and hatred, our avarice, our data banks and dead ideas, our dead rivers and smoky skies behind us. Or we can walk through lightly, with little luggage, ready to imagine another world. And ready to fight for it.”

Arundhati Roy, Author

Hospitals and healthcare took a severe beating during this COVID-19 pandemic. Media pictures of hospitals and healthcare systems being completely overwhelmed with critically-ill patients and cemeteries and crematoria overflowing with corpses of the deceased have left indelible images in our minds. We must convene and plan now to plan for the future of work in healthcare and how artificial intelligence can be leveraged as an invaluable resource for this paradigm shift. The following are some of my thoughts for an upcoming talk for MIT Technology Review’s EmTech Next virtual conference in June (10th):

Clinicians and Healthcare Workers: Clinicians are very poorly prepared for the AI tsunami that is already here

Need for Actionable Intelligence. It was months before information about simple therapies (such as proning or steroids) were demonstrated to be effective. Clinicians are simply overwhelmed with medical knowledge doubling every few months. We clinicians also need an AI-enabled brain and nervous system for expedient delivery of healthcare services in all venues, so real-time agile clinical research will need to be implemented to deliver actionable medical intelligence.

Transition to Hybrid Models. This is not only about working centrally vs virtually, but a better balance between clinicians and patients. The morale especially amongst senior clinicians after this pandemic will be at its nadir and patient care will be impacted as there will be a significant generational shift. Due to an anticipated severe shortage, healthcare workers will transition into a gig as well as virtual mindset for their work so machine learning will be essential for this era.

Innovation in Medical Education. Doctors need to be at least conversational in their understanding of artificial intelligence to be able to adopt future use of these AI tools. The era of AI is here but very few doctors, including the younger medical students and trainees, have the education or experience using this resource. Innovations in medical education and clinical training are also needed with AI-enabled tools in virtual intelligent reality.

Hospitals and Health Systems: Health systems are in dire need of a future-focused AI strategy to become more intelligent

Accommodation of Exponential Technologies. The hospitals are not able to leverage AI to its fullest potential simply because the foundational layers of data and IT infrastructures were inadequate. This linear-to-exponential technology mismatch is not only in deployment, but also in regulatory guidelines and ethical considerations. AI, however, can be the North Star to inspire health systems to upgrade their infrastructures so that AI projects can be much more easily executed.

Automation of Tedious Tasks. Many tedious tasks can be automated in healthcare with tools such as robotic process automation to reduce the administrative burden of healthcare. This area remains under-leveraged but will allow all the workers to upskill into better jobs with higher satisfaction and also be better prepared for the next global public health emergency. In particular, areas such as revenue cycle management and human resources are ripe for AI-enabled automation.

Delivery of Virtual Healthcare. Much of the primary and even subspecialty care saw an exponential rise in telehealth during the pandemic, but much of the diagnostic testing and interventional procedures have also been delayed. In addition, we need a panoply of intelligent wearable devices to be coupled to this distributed, continual virtual healthcare so that chronic and complex diseases can be more effectively managed, especially with a growing aging population.

Patients and Public: All aspects of future of work in healthcare should be securing the tenets of the Quadruple Aim

Access to Health Intelligence. The general public should have ready access to accurate and reliable healthcare information wherever they are with all the relevant information that is AI-enabled. This can be accomplished with streaming health data and application of machine and deep learning for public health modeling specific for the individual and area. Any AI project needs to be coupled with improved health outcome or at least clinical relevance.

Crisis in Patient Experience. During the pandemic, the public dissemination of information has been woefully inadequate and inaccurate, so each individual citizen should have an individualized risk and exposure profile that will recommend the appropriate action in a precise manner. The patient experience needs to be substantially upgraded with continual communication and feedback with current promising natural language processing tools.

Innovations in Intelligent Therapies. There has been impressive preliminary work using AI for drug repurposing as well as vaccine design and this needs to be supported more by the public as well as commercial sector. AI methodologies such as deep learning for protein structure determination from genomic sequence, for instance, can continue to play a major role future biomedical research and drug development in a myriad of diseases.

This highly regulated, high volume, and high risk healthcare industry simply cannot afford to be in status quo with insufficient innovation and intelligence (artificial and human). The healthcare industry is slow to change historically as it delicately balances new technology with ethical implementation, but there should be a concomitant discussion on the losses of human lives without the benefit of these exponentially emerging technologies on a global scale.

The aforementioned lessons learned in this environment can serve as both productivity prescriptions for organizations across all industries as well as a clarion call for even more expertise and resources to assure equity of healthcare delivery around the world.

The Healthcare Data Conundrum (Part I)

“It’s the economy, stupid.”  James Carville, Bill Clinton’s strategist for 1992 presidential campaign   The above battle mantra during the presidential campaign of Bill Clinton

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