Four ways adoption of AI is shaping the future of patient care

AI in healthcare is a market expected to hit $6.6 billion by 2021.

With additional applications emerging at an incredible pace, the technology is disrupting the healthcare sector for providers and pharma alike. Innovation in areas such as machine learning-assisted drug research is changing outcomes for those with chronic illness and improving life expectancies. Natural language processing technology is overhauling the medical landscape, helping doctors transcribe and record their consultations with patients. One thing is certain: AI has the potential to dramatically improve and shape patient care.

Companion robots and caregiving
Nearly 70% of Americans are on at least one prescription drug; ensuring that those patients adhere to treatment is critical. One solution that providers are implementing is the use of companion robots in the home. Applying psychology research, medical best practices and human-robot interaction principles, companion robots can assist elderly patients with aging in place, improve patient outcomes for those living with chronic illness and address issues of medication and treatment adherence. Using cutting edge software and AI algorithms, robotic patient engagement platforms securely relay vital patient information to healthcare teams, allowing providers to improve and adjust care plans on an individual basis.

During years of research at MIT, my colleagues and I found that human-robot interactions were more effective than screen-based alone in engaging patients to create lasting behavior changes. Patients build a connection with robots that have incorporated psychology principles to achieve effective interactions using tailored conversations, eye contact, relationship phases and even well-timed jokes. It’s proven to be more likely that patients will adhere to treatment with the support of social robots focused solely on their health, versus using an app that provides little more than medication reminders and access to provider communication.

AI-based patient engagement platforms also provide a flexible, scalable solution for providers, allowing them to improve care with a more significant impact on the communities they serve. By providing accessible technology to a robust number of patients, existing care teams are able to help many more patients. Rather than replacing humans in existing roles, which is causing fear in some industries, in healthcare, robots are augmenting people and extending their capabilities across patient care.

Wearable devices and remote health monitoring
Another area of rapid growth for AI is that of health monitoring via wearable devices. Wide adoption of consumer-grade wearables (like Apple Watches and FitBits), along with improved versions of wearables that include sensors and biometric patches, are both increasing accuracy and paving the way for trusted implementations within the medical community. Along with constantly evolving UX, enhanced functionality and improved data analysis, these factors are causing a rise in the usage and acceptance of wearables as part of a multi-faceted treatment plan.

This allows patients to play an active role in their treatment, providing care teams with valuable, real-world data gathered in everyday life, which was an expensive and painstaking option before. The use of continuous monitoring throughout a patient’s day also generates significantly more data than ever. Remote monitoring via wearable devices allows for a level of flexibility never previously available to patients. Take a use case such as a sleep study, for example. In the past, this meant that a patient had to sleep in a lab overnight. Today, this can be as simple as the patient taking home a kit of wearable monitors, increasing efficiency and avoiding further disruptions to patients already battling a chronic condition.

In turn, providers utilizing wearable devices within their treatment plans have access to a huge amount of patient data. They also gain knowledge regarding what’s going on with a patient’s health outside of the clinic, improving the patient experience and lowering the chances that a dangerous health event will occur

Digital management and integration of patient data
While it may not seem as groundbreaking as some uses of AI for patient care, machine learning-assisted digitization of patient records is a major advancement within the medical field. Applications in health records not only reduce time spent on administrative tasks - allowing patients more time with their provider - but can also put power and knowledge in the hands of patients. New startups on the scene are incorporating AI along with voice recognition technology to record and automatically transcribe doctor-patient conversations before seamlessly uploading the relevant information to the patient’s record.

As these solutions continue to catch on across many areas of medicine, the result for patients will be the integration of essential health data across platforms and providers, creating a more complete health picture. Machine learning and AI algorithms can also securely deliver patient data, reported symptoms and treatment adherence issues to a patient’s doctor, allowing them to address and evolve the treatment plan and improve outcomes.

Early disease diagnosis
Another promising and potentially hugely altering development of AI technology in medicine is the use of algorithms to assist doctors with early disease diagnosis. While still in early stages, such technology has been found to help detect conditions like heart and eye disease via retina scans and track other signs of fatal illnesses.

AI is also now being used within dermatology to analyze tissue at risk for skin cancer which, considering the data the shows one in five Americans will be diagnosed with skin cancer, is very promising. While in the early phases of adoption, AI has the potential to significantly aid doctors with early detection and treatment, saving individual patient lives and combating common illnesses on a global level.

Although the rate of adoption may be initially slow, as we witness with new technology across other traditional, highly regulated industries, we're already well into the process of AI overhauling patient treatment. It’s important for clinicians and healthcare administrators to understand where this type of technology is having an impact in medicine and caregiving today and where it’s likely going to change the way that they both care for patients and do business in the near future.

Dr. Cory Kidd is the founder and CEO of Catalia Health. Dr. Kidd has been working in healthcare technology for nearly two decades with his work focused on applying innovative technologies towards solving large-scale healthcare challenges. Dr. Kidd received his M.S. and Ph.D. at the MIT Media Lab in human-robot interaction. While there, he conducted studies that showed the psychological and clinical advantages of using a physical robot over screen-based interactions.

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