This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.
IoT data from healthcare wearables and patient devices has only just begun to change the way hospitals treat patients, but advances will continue through the analytic insights they provide.
Many big healthcare and insurance companies have begun using analytics tools to help find the best “path to care” and reduce the cost of healthcare. For example, using big data pathing analytics allows healthcare providers to analyze clinical treatment over time, not only a small sample of patients but potentially all patients treated or insured.
The advent of the Internet of Things (IoT) is accelerating these advancements – promising to change the way patients receive personalized care by capturing patient behavioral data as well. Something as seemingly simple as having patients use wearable devices could make a huge impact on path to care, and doctors should take note.
Clinical data is being captured in much greater detail with prompted inputs and codes. Almost 80% of hospital executives believe the future of healthcare could be significantly improved using predictive analytics. Doctors collect data every time they see a patient -- each clinical visit results in notes and feedback that can be leveraged through analytics -- however, the trouble is collecting data between these visits. Information flow can be slow or incomplete, resulting in prolonged intervals between findings, actions, and subsequent impact. As a result, doctors often remain blind as to what happens in between patient visits, relying entirely on subjective interviews rather than objective data.
Many patients are fairly accurate on their pain feedback, however they may have a different perspective than the healthcare provider about how closely they’ve followed their treatment plans. Some patients may not want to admit that they didn’t follow the doctor’s orders while others may go overboard with physical therapy, for example, which could negatively impact their recovery. This is where IoT and healthcare wearables help provide a more accurate path to care by combining clinical data with patient behavioral data for a clearer picture of the patient’s progress.
Healthcare wearables can track several different types of patient activity, such as steps, heart rate and sleep, to accurately reflect adherence to recommended treatment. The number of behaviors that can be tracked by wearables is increasing, and as more clinical and behavioral IoT data becomes available to analyze, doctors can better monitor patient care and make informed recommendations. Healthcare providers are beginning to understand the benefit of compiling the data from wearables. For example, there are cases of elderly care facilities joining forces with wearable technology companies to remotely track biometric and behavioral data. The data is pulled from wearable devices to help doctors prevent falls, identify health declines and track diseases.
To illustrate, as people get older, degenerative knee osteoarthritis is one common contributor to pain and decreased mobility. Determining the best path to care for this condition isn’t clear cut and options could range from non-surgical treatments to a full knee replacement. By looking at the data collected from a wearable device and clinical records, treatment options can be tailored for each individual based on a 360-degree view of patient activity.
It is also possible to help senior patients avoid a clinical visit all together. For example, a common condition within elderly populations is urinary tract infections or UTIs. A simple treatment of antibiotics can usually cure the infection, but if undetected, it can lead to falling, a trip to the emergency room, a broken hip or worse. This situation could be avoided entirely if the wearable device had the analytical capability to monitor a person’s gait, thereby signaling an abnormal change that might indicate a loss of balance. An alert could then be given to the elderly person, healthcare provider or guardian to ensure they are checked for a UTI. If detected early, the remedy is relatively simple and low cost. If undetected, a UTI in an elderly patient typically results in a fall, a $1,000 ambulance bill, a $2,000 emergency visit and tests, or potentially a $20,000 broken hip or $40,000 hip replacement. It is one reason, healthcare insurance companies are very interested in incorporating IoT and healthcare wearables into treatment plans.
IoT data from healthcare wearables and patient devices has only just begun to change the way hospitals treat patients. By expanding the use of these devices and the analytic insights they provide, we can look forward to better paths to care and a truly personalized healthcare experience.
Randy Lea is Vice President, Americas Big Data Practice at Teradata.
The InformationWeek community brings together IT practitioners and industry experts with IT advice, education, and opinions. We strive to highlight technology executives and subject matter experts and use their knowledge and experiences to help our audience of IT ... View Full Bio
We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
The State of IT & Cybersecurity Operations 2020Download this report from InformationWeek, in partnership with Dark Reading, to learn more about how today's IT operations teams work with cybersecurity operations, what technologies they are using, and how they communicate and share responsibility--or create risk by failing to do so. Get it now!