Artificial Intelligence and Machine Learning (AI/ML) are making a major impact in the healthcare industry. It is estimated that Healthcare AI will be a $24 Billion market with a compounded annual growth rate (CAGR) of 38%. AI’s rapid progress was made possible because of advances in computing/storage, underlying technologies such as algorithms, and the availability of data to train these algorithms. As a result, many medical practices can actually begin to use these solutions to benefit on many fronts, such as reducing costs, increasing efficiencies, and actually growing their practices at a much more rapid pace.
Looking from a provider’s viewpoint, this article details the top AI use cases that a practitioner can potentially benefit from right away.
Patient Engagement and Customer Service
AI can assist with patient engagement and customer services across the entire patient lifecycle from initial scheduling to post-care management. A chatbot is an AI-driven application that has been deployed to engage patients to check on their symptoms, remind them about their medicine, and assist the medical staff in the overall engagement of the patients in their recovery phase. Here is an article on how Conversa Health used chatbots.
Healthcare Administration
Healthcare administrative costs could be up to 34% of the overall healthcare costs and any technology that could help reduce this cost would be very much welcome. AI applications are helping by reducing these costs with automation in clearing claims, identifying fraud, and optimizing revenue cycle management. AI solutions are also helping with the intelligent scheduling of medical professionals and also expensive equipment. Mayo, Baylor, and Cleveland Clinic have used AI solutions to manage their administrative expenses.
Medical Professional Support
AI solutions are helping medical professionals with decision support and effective patient care. AI-based solutions are helping physicians assess high-risk patients needing ICU treatment based on prior datasets and also supporting nurses by alerting them on patient needs based on changing or dangerous conditions. Solutions like Tempus, IBM Watson, KenSci, and H2o.AI help medical professionals deliver personalized patient care and help better assess operational and medical risks.
Remote Health / TeleHealth
Virtual Nursing Assistants (VNA), Remote patient monitoring and engagement, Apps to deal with mental Health, and Apps to prevent falls for elderly patients are a few of the ways AI is helping in the Telehealth area. All these applications process data from multiple domains and synthesize the data using sophisticated machine-learning algorithms to provide timely and accurate recommendations. Nursewise, MycheckIn, Teladoc, and Carepilot are some of the applications in this area.
Diagnostics
AI can assist with diagnosis in 2 ways. One is by increasing a physician’s efficiency with a faster and potentially proactive diagnosis by processing a lot more data than a human can. Another way is by reducing errors in diagnosis. Based on various studies, it is estimated that 1 in 20 diagnoses is an incorrect diagnosis and AI solutions can reduce these errors.
Medical Training
AI solutions are helping medical professionals with training, decision support, and effective patient care. For example, a medical school in Canada used AI Tutor to teach students safe surgical techniques and the students learned 2.6x faster and performed 36% better than being taught by a human tutor.
Apart from these use cases, AI is being used in many other Healthcare areas like Drug discovery, Medical research, and Robotic surgery for example. We’ll discuss those areas in another future article.
