In the last blog, we discussed how Artificial Intelligence is poised to become a game changer for the healthcare industry. We illustrated how chatbots are getting transformed into digital assistants and how they can address patient’s questions, suggest steps to cure illness and provide alerts for physician interventions. The potential application of AI goes beyond the patients. Today, we’ll look at how AI has a big impact on the hospital and clinic management systems.
Most hospitals/clinics have some sort of a HIS software through which they manage their administrative and clinical operations and maintain patient health records. These records have wealth of information that can be mined in order to provide faster and better health services. Google’s Deepmind Health project is geared towards that direction. The team is working with NHS hospitals to get patients from test to treatment as quickly and accurately as possible using mobile tools and AI. They have developed a secure and instant alert app, that connects patients with serious issues to the right nurse and physicians on time by analysing their test results. AI can also be used to design treatment plans that can reduce the treatment cost and improve the success rates. IBM Watson has a program for oncologists that provides clinicians evidence based treatment options. It analyses the structured and unstructured data in clinical notes and reports and identifies the most effective treatment plans for the patients. Similar use case is applicable to IVF hospitals/clinics where an AI engine can be used to mine through the treatment cycles data to come up a personalized treatment plan that guarantees IVF success. This can reduce the treatment costs for the patients and subsequently increase his/her confidence in the clinics.
From a physician’s perspective, the most critical factor that affects his/her productivity is the time he/spends using the software. If that time is brought down, he can see more patients which can lead to increased revenue. Machine learning, which is a method of data analysis that iteratively learns from data using algorithms can be used to study the physician’s response for various symptoms/diagnosis. It can subsequently provide him/her suggestions based on previous cases to optimize the time he/she spends in updating the EMRs. IBM has developed an algorithm called “Medical Sieve” that can analyze radiology images to spot and detect problems faster and in a more reliable manner. This will save a radiologist a lot of time as he/she will only have to focus on complicated cases where human supervision is required.
By building AI into their solutions, the HIS can improve the operational efficiency and success rate for critical treatment plans. In some cases, it could potentially save patients’ lives. Over the next couple of years, AI in healthcare will start playing a big role in supporting prevention, diagnosis, medication management, precision medicine, treatment plans and drug creation. A quote from Alan Turing seems so relevant – “We can only see a short distance ahead, but we can see plenty there that needs to be done.”
CTO – Palash IVF