Clinical Support With AI and Machine Learning
Diagnostic errors are one of the most prevalent issues in the medical field. That is why new healthcare technologies are being produced to increase accuracy among physicians. The use of AI in healthcare has become the focus for many healthcare technology manufacturers. Machine learning allows the algorithms to improve through use and experience. Some AI diagnostic tools run autonomously while others require prompting from the physician. The Food and Drug Administration (FDA) approved the first autonomous AI diagnostic tool to be sold to clinicians in April of 2018.
While some companies are beginning to get their software off the ground, there are still many whose software is only now approaching experimental phases. Alongside AI, there are also IT healthcare tools that assist physicians and healthcare researchers in a variety of ways. John Halamka, President of Mayo Clinic Platform, explains that some of these tools offer symptom searches and decision tree software. Others inform physicians on new breakthroughs and developments within the medical field. Even though AI medical technology is pioneering the modern age of medicine, there are many obstacles to overcome before it becomes the new normal among clinics.
Continue reading to find out more about some of the innovative ways that the medical field has implemented AI and IT technology.
Data Analytics in IT Healthcare
Medical data analytics have become much more accurate through new technology. The medical field encourages the use of this technology for medical research institutions because not only is it more accurate, it is also more efficient.
One healthcare app is revolutionizing breathing treatments through data. Propeller Health uses innovative technology to help asthmatics and those with COPD better regulate their health. The company utilizes sensors that attach to inhalers which track when and where an inhaler is used. This data is sent to and interpreted by the users app which allows them to better understand their triggers and symptoms. This data analytic software has dramatically reduced ER visits and flare-ups for those with asthma and COPD.
A second example of ways that the medical field is utilizing data analytic technology is Nemours Children's Health System in Orlando, Florida. Nemours has contributed to a shift in the way that the medical field utilizes data. They have employed Qlik Sense, an analytics tool, to bring all of their data to one, easy-to-use location. This allows employees to see macro and micro trends in the clinical and financial data of Nemours. This IT healthcare tool has dramatically increased productivity and revenue at Nemours.
Propeller Health and Nemours Children’s Health System are just two of the many innovative bodies that have contributed to more advanced technology and utilization within data analytics.
Artificial Intelligence: AI in Medicine
The use of artificial intelligence in healthcare has grown steadily as demands for more accurate technology have arisen. While some question the safety of the use of AI in the medical field, many believe that it is the next step for medicine.
At Beth Israel Deaconess Medical Center (BIDMC) in Boston, Massachusetts, researchers are using AI software to quickly identify blood infections. Researchers are inputting AI devices into microscopes which have been trained, through thousands of images, to accurately locate infections in blood samples. While this can be done manually, the amount of work for lab technologists exceeds the number of employed lab technologists. This technology will allow larger medical institutions to increase productivity in labs.
Another use of AI and machine learning in the medical field comes from Berg. Through extensively trained AI systems, Berg is able to identify biological factors of diseases that it then attributes to available drug trials, research and patents. These results are then used to create a plan for the patient. Berg’s AI software is also being used to predict which patients will react well or adversely to drug trials. Berg uses data analytics, AI software and diagnostic technology to enhance a patient's quality of healthcare.
While there is hesitation concerning the capabilities of some AI devices, medical devices implemented with AI technology will continue to be safely developed and commercialized. These technologies will revolutionize the medical field and increase efficiency and accuracy across the board.
Medical Technology and Your Diagnosis
Diagnostic technology is one of the best uses of AI and IT software in the medical field. Physicians are able to use healthcare apps, devices and software that provide rapid and more accurate diagnoses.
One company that is providing AI diagnostic technology is IDx-DR. IDx-DR has produced an autonomous system that is capable of analyzing images of the retina and diagnosing diabetic retinopathy. This system has been trained through viewing thousands of retinas with diabetic retinopathy. Now, it is able to diagnose in real time without physician oversight. Technology like this enables patients to receive results almost immediately. This reduces anxiety and allows the treatment and recovery process to begin right away.
Another use of AI and machine learning for diagnoses can be attributed to research done by bioRxiv. This company uses AI algorithms to diagnose acute kidney injury (AKI) early. AKI contributes to up to 7% of yearly hospital visits. The algorithm will be able to effectively predetermine the signs of AKI without physician interference. While this specific program is a long way from commercialization, it shows just how much can be done with this type of technology.
Are Clinics Using Machine Learning and AI in Healthcare?
The National Institute of Health reports that around 54% of physicians use a tablet in their practice and that 38% of their phone time is for using professional medical apps. Medical professionals use doctor apps for all sorts of reasons. Some use them for office management and others use them for diagnostic and reference assistance. 90% of physicians use apps for drug information so that they can ensure that there will be no adverse drug interactions. In general, GPs are not using machine learning and AI software to its fullest potential. This is due to the technology being widely unavailable and expensive. On the other hand, many hospitals and other large healthcare systems are looking into the use of AI systems to improve their quality of care.
Medical Apps for Patient Care
DocClocker is one of the apps that clinics are using to improve office management. This program offers real-time waiting time, remote check-in and online bookings. Users can also locate and review doctors on the app. DocClocker software increases productivity and efficiency in the office, producing the highest quality patient care.
Go to https://info.docclocker.com to learn more.