Telehealth has been expanding for years. We’re seeing more and more primary care providers, hospitals, and medical researchers embracing the option of treating patients remotely. Now, the next generation of telehealth is bringing Artificial Intelligence to the table to help advance healthcare options in a variety of ways. We’re rounding up the latest news in AI and three main advantages are emerging.

• Accessibility
• Cost Reduction
• Long Term Management

Accessibility

The most obvious advantage to Artificial Intelligence in telehealth is the level of accessibility it allows. Patients living in rural areas or those without reliable transportation are lucky to see a doctor once a year. That is hardly the amount of care it takes to treat a short term or long term chronic condition. A recent article from Electronic Component News features a simple observation from primary care physician Lyle Berkowitz,

 

“Many patients do not have easy access to a brick and mortar facility, but they all have access to a computer or mobile device, so we make it easy for them to use either to connect with us.”

Chatbots help connect doctors and patients.

 

Dr. Berkowitz is part of the MDLIVE Medical Group. The practice is one of the few in the nation handling patients across all 50 states, 24/7, year-round. They’ve developed an AI Chatbot called Sophie that can help register and connect patients with their doctor. MDLIVE is hopeful that in the future Sophie will also be able to help with diagnosis and treatment options. Some practices are even predicting that Artificial Intelligence will bring care and treatment options to developing countries with little to no access to healthcare at all.

Cost Reduction

Health care spending in the U.S. is a major concern. Evidence shows the U.S. spends more on healthcare than other countries, yet our nation’s health outcomes are often worse. This is largely due to administrative costs and slow intake processes. With AI the future does not have to be so sluggish. Chatbots like Sophie can not only guide new members through the registration process but also help users to recover usernames and passwords. Better yet, Bots can analyze patients’ insurance offerings and make recommendations to suit their needs and coverage.

 

These are examples of what is called Robotic Process Automation or RPA. This model helps put healthcare organizations’ focus back on patients, enabling them to navigate the intense healthcare ecosystem and find the best possible care options.

 

Long Term Management

Perhaps one of the most promising areas of development in Artificial Intelligence is analysis of long-term diagnoses. With the use of algorithms and predictive analytics, AI can alert clinicians to problems more quickly. Certain algorithms may even be right at our fingertips. Smartphone selfies have become powerful diagnostic tools. We generate millions of terabytes of data every day by simply taking selfies. AI can use that data to provide personalized, faster, and smarter services. A smart phone tool in the UK can identify developmental diseases by analyzing images of a child’s face. It can then match these images to more than 90 disorders to provide clinical decision support. AI makes it easier to sort through all the data. As Brandon Westover, Director of the MGH Clinical Data Animation Center, states:

 

“…if you have an AI algorithm and lots and lots of data from many patients, it’s easier to match up what you’re seeing to long-term patterns and maybe detect subtle improvements that would impact your decisions around care.”

 

From chatbots to genomics to remote sensors, we’re getting a sense of what to expect from the future of AI in telehealth.

 

At Behavior Imaging, we are all too familiar with the autism care gap and the long wait times most families face during or before diagnosis. Lack of brick and mortar facilities contributes to these issues. We’re constantly searching for innovative ways to shorten the gap and limit the wait time. AI’s promise of reduced spending, a focus on the patient, and a streamlined process can mean the world to those families. Especially to a family discovering the complexities of autism and the many care options available. The prospect of adding AI to streamline the process of connecting families with clinicians is incredibly exciting.

 

We hope to offer our own AI developments in the future

 

 

Sources:

https://www.ecnmag.com/article/2018/11/breaking-borders-patient-centric-medicine

https://jamanetwork.com/journals/jama/article-abstract/2674671?redirect=true

https://www.healthcareitnews.com/news/where-ai-has-most-promise-reducing-healthcare-costs

https://hitconsultant.net/2018/02/05/artificial-intelligence-focusing-on-care-not-cost/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298703/

https://www.genome.gov/27552451/what-is-genomic-medicine/

https://medicalfuturist.com/top-12-health-chatbots

https://behaviorimaging.com/2018/08/05/autisms-care-gap-when-resources-dont-meet-demand/

https://healthitanalytics.com/news/top-12-ways-artificial-intelligence-will-impact-healthcare