An aging, sicker population will place ever more pressure on an already strained system. We expect to see further moves by CMS to incentivize innovation. The move toward predictive medicine represents a huge opportunity, which is why more and more established tech companies are entering the RPM technology space. This collection and analysis of all kinds of patient data will enable medical professionals to detect the deterioration of a patient’s condition at an earlier, proactive point, reducing the strain on the healthcare system and improving the patient’s outcomes.
For example, a study published in JAMA in 2006 showed providing patients with communication tools and coaching, and encouraging them to take a more active role in their healthcare, reduced readmissions at 30 days and 90 days. Studies confirm that RPM has been shown to reduce readmissions and improve outcomes.
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We’ve already seen this reduce readmissions, empower patients and free staff from manual tasks. Linking patient educational content to the objective insights generated on their health can also increase patient empowerment.
A platform continuously analyzes the data being collected to deliver sensitive and specific early warnings to physicians and healthcare staff. A patient app also enables them to report symptoms, receive medication reminders, review educational content and undertake video visits with their doctors.Īdvances in artificial intelligence (AI) allow actionable insights and early warnings to be generated from this data. There’s no time-consuming manual entry for either the patient or for healthcare staff. Acting as a hub, it seamlessly integrates with a range of peripheral devices, such as for weight or peak flow. For example, our wearable all-in-one wireless device provides continuous ICU-level monitoring in any setting. Rather than being left on their own, patients discharged from a hospital are monitored by wearable, passive devices that continuously communicate vital data to healthcare staff via the Internet. This ambiguous area makes it difficult, if not impossible, to identify problems at a stage where they can still be treated with ambulatory care. Patients don’t always know when they need to call their doctor, so physicians and healthcare professionals have little idea of their health trajectory. Even the move from a hospital to a nursing facility or care facility results in a significant reduction in support and monitoring. Once patients arrive home, they have minimal supervision and support, if any. The 48-hour period after patients leave the hospital is a risky period fraught with vulnerability and anxiety. Understanding how healthcare does not end once the patient leaves the hospital is critical to reducing readmissions. Consequently, payers, government and healthcare providers are now focused on reducing readmissions. The economic and clinical burden of readmissions is accompanied by emotional and financial strain on patients and their families, as well as poorer patient outcomes. This costs Medicare about $17 billion a year. More recent statistics show that 15 percent of Medicare patients - who generally require the most care and consume the most healthcare resources - are readmitted to hospitals for unplanned treatment within 30 days of discharge. In 2011, there were about 3.3 million 30-day hospital readmissions in the U.S., a figure associated with more than $40 billion in healthcare costs.
This support is highly encouraging, as RPM has the potential to address this country’s $40 billion problem - unplanned hospital readmissions of patients whose conditions deteriorate soon after treatment. With these moves, CMS has lent strong credibility to the use of RPM, and its support will help drive continued innovation. It has also taken a step toward considering RPM when it determines future payment rates. In a recent rule, CMS highlighted numerous studies that point out the potential benefits of RPM in reducing costs, decreasing re-hospitalization rates and improving outcomes. CMS defines RPM as the collection of physiologic data (for example, oxygen saturation, blood pressure, glucose monitoring) digitally stored and/or transmitted by the patient and/or caregiver to the home health aide (HHA).
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