Guest Columns

Digital practice in LTC: Impact of AI, AR and digital technologies

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James Lomastro
James Lomastro

Many of us working on reform since the advent of Medicare and Medicaid in the turbulent 1960s witnessed reform in the guise of reworking, re-engineering, redevising, recreating, redesigning and refashioning. Currently, much of the effort squeeze what they can out of the resources that we have. It often betrays a lack of resourcefulness.

Many of the tools remain the same, with electronic versions of manual processes and systems. Most of the thinking is not critical or creative with few innovations that will substantially change the system.  

Indeed, even when we made progress, cost consumed a good part of the nation's resources. While most other systems became efficient and the costs dropped, healthcare plows along, and for the first time since we recorded life expectancy we did not have a rise in it and experienced a decline.  

This situation is about to change and not from inside healthcare, medicine or long-term care. Instead, it's outside forces, causing us to radically alter the way in which we operate the system and the methods that providers, practitioners, and professional practice. For many, it may initially resemble a brave new world with the accompanying fears and resistance.  

The recent emergence of Amazon, Berkshire, and ChaseMorgan represent companies transformed by technology and AI (artificial intelligence) entering healthcare and indicating a change in perspective.

At the same time that Medicare was developing, the study of AI began as a defense project in the 1960s with the goal of understanding how humans process information. The concept was to replicate that processing with machines and devices that will do it more reliably and without error. This concept would then be simulated and adapted to “logical systems.”

Development did not progress for a while given the “secret” nature of defense work -defense contractors and countries do not share as a matter of course innovations and knowledge.  In the 1980s, changes in technology propelled advances in artificial intelligence. Much of this development paralleled the development of the Internet, non-commercial and defense applications, which inventors widely shared. The result was that expansion in these areas became exponential. These advances because they make our lives easier and safer began to have broad commercial application and acceptance.

AI and digital technologies have already enabled many task-specific systems and functions to aid human activities with faster and more accurate execution. Computers recognize speech, natural language, and images. When we speak to the issue of driverless cars and trucks, we realize that we have had pilotless drones, which utilize AI and its controllers AR (Augmented Reality). Robots do summersaults, and land on their legs and rocket come back to their launch pad.

These advances have helped banks develop tighter security systems and provide consumers with account protection, which detects fraudulent activities or irregularity in a user's behavioral pattern. They have also made using social media easier by auto-suggesting names of people that you should tag on Facebook based on photo recognition technology. Even mattresses and chairs come preprogrammed. (Think of a bed or chair detecting pressure making adjustments).

Computers have become more adept at processing not only a significant amount of data quickly and without error. Today they are able to anticipate, detect, and offer suggested actions in response to a given set of conditions. Big data, which was the bane of many people's existence is now smart. Artificial intelligence in healthcare provides both practitioners and the persons they serve a chance at better care, with more efficiency and precision.  

Computers, whether they are small chips implanted in other devices or many of the more familiar ones to us (desktops, laptops, smartphones, and tablets) perform flowcharting, making decision trees, pattern recognition and deep learning. AI finds uses in decision support, laboratory devices, financial applications, robotic surgery, exoskeleton devices for spinal care patients, medication dispensaries and in education to name a few.

Unless practitioners improve themselves, there will become victims with the advancement of artificial intelligence in healthcare. Those who do not choose to invest in understanding AI and adapt to it will not only face increased competition with those who do. They will lose patients and revenue, and eventually, they will become obsolete as they will not be capable of keeping up.

To date, this threat does not reverberate with many practitioners. Many feel that they could not be replaced with a robot and in many ways, they are correct to an extent. However, they failed to see the many other systems that AI will impact and necessitate their adapting and work with it. We have self-driven cars – what about self-driving wheelchairs, carts, dispensing machines and other devices?

Five Factors underscore the importance of the AI in healthcare and the reasons for its emergence and prominence.

1. The magnitude of the problem – Healthcare generates about 20% of our gross national product. It is an economic engine in every community. While the US represents about five percent of the world's population, we consume 30% to 40% of the world's healthcare resources. The rate of growth is not sustainable and reducing services as recent events indicate is not politically feasible. Much of healthcare reform has failed. Much of it moves the pieces around but does not result in any new techniques, systems, and processes. Digital technology not only promises but also threatens to change this situation.

2.   Impact — If the care system fails, then the effect may be, catastrophic to the system making the addressing it crucial. It is not just that we consume more per capita than any western country. There is little way that we fail to adopt the efficiencies and changes that digital technology provides. Many have embraced parts of digital changes and incorporated them into there practice in an incremental way. However, once digital technologies become established in the system, they begin to develop a life of their own. Once AI takes hold, it feeds on itself and contains within itself processes to make the system even better and more efficient.

3.   Urgency — The medical model as a hierarchical, practitioner-centric system dominates healthcare does not work with digital technologies. The model remains in place because it serves in the short term many of the powerful and influential interests. The system will move to a more social system model. Many practitioners are becoming fatigued and stressed finding it challenging to manage increasing load and need of patients. The medical model is incompatible with the way that digital technologies operate. Digital models are not linear and causative but interactive and reiterative. They learn not only from their mistakes but make fewer of them by detecting patterns that we may not be able to perceive. In short, they are smart.

4.   Availability of smart solutions — There are compelling evidence-based solutions that if applied by organizations practitioners and providers will address the issues.  Even if the system itself lags in retooling its resources, there are models, practices, and methods, which the practitioner can use. The field is rapidly growing and increasing the resources and techniques available. As we recently witnessed the emergence of new players will change the situation and accelerate the process.

5.  Availability of Resources — The task becomes more than a retooling of resources. Even given the dysfunctional nature of the system, there appear to be sufficient resources that practitioners and providers can utilize to become digital practitioners and providers.  

AI and digital technologies are not the solutions to the healthcare issues.  They are tools, resources, and means of addressing problems in healthcare. The proliferation of smart devices, the development of smart data, and the ability to connect provides a different platform on which to operate and restructure the system. Given relative inexpensive nature of smart devices and connections, relatively small investments will yield considerable results.

The real change occurs when new players are working digitally, they will find that the old model does not work with the digital technologies and gains a competitive advantage. However, the present change is nothing short of a transformation.  While we have not reached the inflection or tipping point, the critical mass continues to grow.

James Lomastro, Ph.D., has worked in a variety of acute, community-based and long-term care in healthcare for 35 years. He has held an administrator license since 1991. Before involvement in administration, he held academic and research appointments at Boston University School of Medicine and Northeastern University.
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