Current Health, a Scottish healthcare technology company, has received clearance from the Food and Drug Administration (FDA) for its machine learning device, which is designed to remotely monitor and analyze vital signs. This wearable device aims to enhance home monitoring systems for chronically ill patients and reduce hospital admissions.
The device, known as Current, is already being used in hospitals and has now been approved for monitoring patients at home between doctor visits. It measures a patient’s respiration, pulse, oxygen saturation, temperature, and mobility, providing continuous updates to doctors. By analyzing the collected data through machine learning, Current can alert doctors of any concerning changes in a patient’s condition via their mobile devices or electronic health records.
Christopher McCann, CEO of Current Health, explains that the device is most commonly used by patients with heart failure and chronic obstructive pulmonary disease. These conditions often result in frequent hospitalizations and significant costs. In an effort to reduce expenses, healthcare officials in the US have targeted the care of such patients, encouraging the implementation of remote monitoring tools to track their conditions. Additionally, health systems are increasingly incorporating data from these technologies into electronic health records and other IT systems.
Dr. Daniel Cantillon, a cardiologist at the Cleveland Clinic, views these advancements as positive. He believes that if devices like Current increase patient connectivity without overwhelming healthcare professionals with excessive data, they will be welcome additions to the medical field.
Current Health’s device is part of a growing number of wearable devices designed to monitor heart and lung function, as well as other vital signs like weight, body temperature, and activity levels. Products such as those developed by AliveCor and Apple have also received FDA approval for detecting atrial fibrillation, an irregular heart rhythm that increases the risk of stroke.
Current Health’s CEO, McCann, emphasizes that the device is intended to be used in collaboration with doctors who determine the thresholds for notifications based on the collected data. However, the company aims to automate this process further in the future by using predictive analytics to anticipate a patient’s decline before it occurs, rather than relying solely on threshold data.
To achieve this goal, the company will need more data from users to refine its algorithms. Despite this potential for increased automation, physician oversight will continue to be crucial.
Current Health’s clearance from the FDA showcases the positive impact and potential of machine learning devices in healthcare. By integrating wearable technology with advanced analytics, healthcare professionals can effectively monitor and intervene in the care of chronically ill patients, providing them with better quality of life and potentially reducing hospital admissions and associated costs.
In conclusion, the FDA’s clearance of Current Health’s machine learning device marks a significant step towards improving home monitoring systems for chronically ill patients. By leveraging wearable technology and advanced analytics, patients can be continuously monitored, and doctors can quickly intervene if necessary. This approval demonstrates the increasing potential of machine learning devices in healthcare and their ability to positively impact patient outcomes.
