Hop on just about any website these days, and you are bound to meet a chatbot before you interact with a live human. Patients can log into Sensely, the company that partners with the Mayo Clinic, and enter their symptoms to receive self-care advice or a referral to care services just by chatting with the bot. Doctors also benefit from similar tech, with platforms offering quick access to drug information and conditions that are sure to keep their knowledge base current.
Using AI tools like chatbots and other machine learning makes sense for diagnosis and treatment. The success of AI in healthcare has researchers curious if it could change the future of disease prevention as well. Big data has become a significant part of the future of medicine. It can help identify a patient’s risk of developing specific diseases and even enhance patient engagement.
So, what are the experts saying about the future of AI and predictive medicine? Here are a few areas of healthcare you need to watch to see AI’s role in disease prevention.
Preventing the Spread of STDs
Healthcare has been in a constant state of treatment for years. However, when you dive into statistics about some long-term or life-altering conditions, it’s easy to understand why experts are urging the shift to prevention.
Let’s review the current state of sexually transmitted diseases (STDs) as an example. In 2017, there were 1.7 million new cases of chlamydia, which was a 22% rise from 2013. Gonorrhoea cases increased by 67% in the same period. Syphilis had a whopping 76% increase. These infections are contagious. If not treated, they can result in long-term pelvic pain, pregnancy complications, and even increase the risk of spreading or getting HIV.
These concerning statistics are precisely why the Centers for Disease Control and Prevention turned to search giant Google for big data. Google allowed access to their search term data to predict outbreaks of infections in specific geographical locations across the United States. If search phrases for symptoms like ”’painful urination’ spike in one city or region, local health authorities are alerted. This knowledge helps them predict new outbreaks of infections and even get ahead of treatment needs. Local health departments and providers can then become more vigilant in recognizing the symptoms of the STD on the rise in their area.
Analyzing Big Data
If you’ve ever worked in research, you understand the challenge of analyzing even a small set of data. However, recent advancements in cognitive computing are changing the way healthcare companies review, analyze, and use big data. Experts estimate that 2,314 exabytes of healthcare data will be produced in 2020. In case you’re wondering, this is more than one billion gigabytes. Our medical data footprint is expected to double every 73 days. It’s not humanly possible for doctors to keep up with this type of data creation, but it’s imperative that they do to treat the disease effectively.
Machine learning can compute all this data and deliver it in usable, smaller sets. Healthcare professionals can predict a patient’s needs and even increase their engagement in health-related care and behaviors. With mental health illness on the rise, experts in psychiatry use artificial intelligence to improve the classification of diseases and even predict treatment outcomes.
The University of California Los Angeles, for example, started mining electronic health records for a cost-effective and accurate way of detecting Type 2 diabetes. The team of researchers found more than they expected when they accidentally discovered previously unknown risk factors for all forms of diabetes. This discovery reminds us that using cognitive computing is powerful and can impact patient outcomes faster than using human power alone.
Expanding the Role of the Nurse
If you’ve ever been a patient in a hospital, you know that nurses are the ones at the bedside, making critical assessments and providing information to physicians for treatment orders. Tech-savvy nurses may even be better positioned to spend more time at the bedside performing life-saving care and assessments. Experts believe that the internet of things offers significant impacts on the future of nursing and patient care, especially for those with long-term conditions.
It’s no secret that you can hop on a telehealth visit with a physician for treatment of an acute health-related issue. Nurses can use this same type of technology to prevent exacerbations of chronic health issues by remotely monitoring the patient’s symptoms. They can also send reminders to patients sitting at home about taking medications, sticking to diet restrictions, and even taking their vital signs.
All of this information helps nurses analyze the control of chronic conditions. With better disease management of conditions like congestive heart failure, diabetes, and hypertension, patient outcomes can improve, and patients can live healthier lives into the future.
Predicting the Future
Healthcare will always need humans. It’s an industry built on compassion, empathy, and the ability to provide hands-on care to people when they need it the most. However, embracing technology like AI for cancer diagnosis and treatment, patient engagement, and analyzing big data sets can provide doctors and nurses with more knowledge than ever before. Keep an eye on these areas of the healthcare industry to see the impact of AI on disease prevention in the future.
