The simple act of entering a building and pressing a button to reach your desired floor feels so mundane today. However, there was once a time when this act would have seemed strange, even disconcerting. This story of the elevator’s evolution offers a fascinating analogy for the challenges faced by the healthcare sector in adopting digital technology and AI. I call this the “The Elevator Effect.”

When the first elevators were introduced, they weren’t the automated, button-pressed systems we know today. Elevators required manual operation, typically by an elevator operator who would control the elevator’s movement, ensuring passengers reached their desired floors safely. With the advent of automated elevators, one might have expected a swift transition. Instead, the shift was gradual, met with suspicion and resistance. It took decades and a significant event—the elevator operators’ strike of 1945 in New York City, where operators protested for more pay and shorter weeks—for building owners to consider the financial and operational benefits of automation. This period of vulnerability led to a more widespread adoption of automated elevators.

A Modern Parallel: COVID-19 and Telehealth

Much like how the elevator operator strike highlighted the vulnerability of a human-operated system, the COVID-19 pandemic unveiled cracks in our traditional healthcare setup. With hospitals overwhelmed and face-to-face consultations posing risks, there was an urgent need for alternative healthcare delivery. Enter telehealth. The pandemic acted as a catalyst, accelerating the adoption of telehealth and telemedicine, services that had previously seen slow uptake due to regulatory, technological, and trust barriers.

For numerous years, the buzz surrounding the integration of digital technologies and artificial intelligence in healthcare has been palpable. Yet, despite the FDA’s endorsement of hundreds of digital health technologies and medical AI systems, discussions about theses often relegate it to the realms of science fiction or a distant healthcare future. This slow pace of AI and digital adoption in the healthcare sector has left many experts pondering the reasons for the lag and contemplating strategies to expedite the embrace of these novel technologies.

Reasons for the Slow Adoption: The Elevator Effect in Healthcare

• Resistance to Change: Just as with elevators, humans have an inherent resistance to change, especially when it replaces a familiar human touch. Medicine’s essence lies in the personal bond between doctor and patient, and the idea of integrating technology can seem cold and impersonal. It’s essential that as we integrate technology, this human essence remains central.
• Safety and Trust Concerns: The initial reluctance to automated elevators stemmed from concerns over safety. Similarly, any new medical technology, including AI, undergoes scrutiny regarding its safety and reliability. Additionally, building trust was crucial for the acceptance of automated elevators. Similarly, for AI-driven solutions like telehealth to gain traction, there’s a need for transparency, ethical considerations, and public awareness. Both practitioners and patients need confidence in these new systems.
• Economic Implications: Elevator operators, through their strikes, indirectly sped up the adoption of automated systems. Similarly, while technology promises streamlined operations, it raises fears of job displacement. The emphasis should be on technology as an augmentative tool, reshaping roles but not eradicating them. The fear of job displacement looms large. Just as elevator operators feared losing their jobs to automation, there’s apprehension about technology replacing various roles within healthcare.
• Regulatory Hurdles: Every new technology in healthcare must navigate a complex web of regulations to ensure patient safety and data security. With evolving policies, ensuring that AI solutions remain compliant is a continuous challenge.
• Technical Challenges: Integrating technology into existing systems requires a complete overhaul of infrastructure in many cases, demanding significant investments of time and resources.
• Lack of Understanding and Training: Healthcare professionals need to be trained to leverage AI tools effectively, a process that requires time, patience, and dedication.

The journey of automated elevators—from skepticism to acceptance—offers valuable lessons for the healthcare sector. The “Elevator Effect” encapsulates the multifaceted challenges that innovations face in their path to widespread acceptance. By understanding and addressing these challenges head-on, we can usher in an era where digital technology and AI in healthcare become as ubiquitous and trusted as the elevators we use without a second thought today.