Consumers are increasingly dictating what they want and demand personalized services with an opportunity to shape what they consume. While personalized services and products are not a new creation, Artificial Intelligence has enabled us to implement personalization in sectors and at a scale not thought possible before. The influence of personalization may also completely reform the way we approach healthcare − is this the end of the one size fits all era?

Personalization initially evolved as a consumer term and there is no denying the immense success of the movement. Companies that succeed in demonstrating ‘customer intimacy’ and ‘member engagement’ generate faster revenue growth and increase repeat purchasers, not to mention personalization has become an expectation amongst many customers (72%). Personalization is now being applied to healthcare, but we must be aware that healthcare by nature has always been personal. The movement is simply upscaling the personalized care that already exists, and aims to find the best treatments for a patient based on their individual qualities and makeup.

Healthcare systems worldwide are experiencing a crisis. Getting an appointment with a doctor is like finding a leopard in the wild: encounters are rare and brief, and when they do occur, eye contact is avoided at all costs. As Eric Topol put it “medicine [has] turned into a business.” Topol explains how health systems now prioritize efficiency over care. Time scheduling with patients has been decreased immensely from an hour per patient to a few minutes at most, and it is not just the patients that are frustrated by the time constraint: “the problem around the world is that doctors aren’t in control. This is run by administrators, the overlord.”

One solution proposed by the personalization movement involves AI assisting patients to take greater control of their own health. Personalized Health Planning aims to remedy time and money spent on chronic care by encouraging healthy behavior and planning. Using predictive technologies, a timeline for health improvements can be created through patient information such as nutrition, personal relationships, stress, exercise, mind-body connection, family history, genetic markers, lifestyle habits, and other biometric data during the appointment. AI technologies trained on behavioral analytics and behavioral economic incentives could also guide human behavior through unobtrusive nudges, reminding and incentivizing individuals to stick to their health plans or even guiding them through rehabilitative care.

Furthermore, through the use of wearable devices and other devices gathering sensory data, AI software exists which can monitor an individual’s health and suggest when to book a doctor’s appointment or when to call an ambulance. Experts suggest that the future of health may involve AI technologies taking care of routine health problems and diagnoses, with doctors’ time being saved for life-threatening health problems. Given the increasing prevalence of at-home testing kits and smart diagnostic devices, these predictions are becoming our reality.

However, AI designers have an important responsibility in ensuring that the systems created are not biased toward certain characteristics. For example, a program being developed to detect skin cancer through images taken on a mobile phone may have biases if it were trained predominantly on a Caucasian population, it may not be able to detect skin cancer accurately on other skin colors. While it can’t be helped that the datasets may be larger for Caucasian populations given its disproportionate effect, the software needs to be able to acknowledge and report low-confidence results where a doctor should take over.

A significant step forward in the world of personalized health would be the creation of digital twins. Digital twins are created entirely through your personal data and would include: a person’s long-term medical history, their digital patient record, a medical exam, and lifestyle data updated in real-time. It would basically be a virtual clone. The digital twin would allow doctors to use predictive AI technologies to determine what treatment is likely to work best for a patient based on their individual conditions. If these digital records are securely made available around the world, while ensuring individuals’ privacy rights (such as those established by the GDPR or HIPAA) are respected, information derived from individuals with similar conditions could provide guidance on what treatments might work best.

The potentials for personalized healthcare are impressive and likely not far into the future. We shouldn’t fear AI taking over certain areas of our healthcare because, if done responsibly, it will lead to better healthcare for us all. We will always need doctors, the use of AI might just mean that we see them when we really need them. But when that situation arises, they will have more time to devote to caring for us and be better informed.

Written by Celene Sandiford, smartR AI

 

 

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