The use of patient monitoring has surged during COVID-19. Here’s what health providers should know about patient monitoring during a pandemic, and beyond.
In an era where nearly all our digital messages are carefully recorded and analyzed; the medical sector is experiencing a drought of continuous patient data documentation. Facebook and Google use big data to further their enterprise goals, but the medical industry lags behind even though its data could save lives and serve as the foundation of many powerful medical technologies.
The Challenge of Medical Big Data and Automated Compliance Data
As medical data is so important, it is strange that much of our hospital data is still collected using “spot checking,” a method that is highly outdated and problematic for three reasons.
Firstly, spot checks happen intermittently, usually only every 6-8 hours, creating a “data desert.” Clinicians and health staff are not being fed the latest patient data, impacting their decision-making process.
Secondly, when patients are undergoing spot checks, many experience “White Coat Syndrome,” which occurs when patient readings go awry due to the patient being aware that they are being measured. For instance, blood pressure and heart rates can rise suddenly during the check making the data gathered inaccurate.
Third, infrequent spot-checking leads to a lack of reliable data points. Without consistent and dependable data points, true big data generation is unattainable, preventing quality data analytics.
Rather than using spot checks, we should strive to collect data with volume, velocity and variety. This means collecting a large amount of data, quickly and at great range to ensure accuracy.
A Solution in Automated Compliance Data
Fortunately, new technologies such as automated compliance data (ACD) is making this big data solution a possibility in hospitals. ACD provides a constant stream of quality data without inputs from patients or staff.
Subsequently, the data can be fed into systems for analysis and help guide medical professionals in their treatment of the patient. By tracking key vitals like heart rate, respiratory rate and movement, automated reliable data generation can provide more than 100 data readings per minute, giving health staff a more complete picture of a patient’s condition. With this data, trends in patient status as well as baseline changes can be easily tracked, analyzed and detected helping to create new opportunities for effective intervention.
The key to generating successful data collected for analytics also depends on the algorithms that gather these patient readings and filter out the ambiguous data. Only then can the reliable and accurate patient readings be digested by big data systems.
Many hospitals and skilled nursing facilities that opted to use EarlySense ACD have seen several positive outcomes. Hospitals reported reductions in code blue events by over 85%, pressure ulcers by 64% and a significant reduction in ICU and overall patients stays.
The world is accepting big data analysis as a standard. The healthcare industry should be leading this shift for the sake of both patients and doctors.
Guy Meger is the CTO and VP of Research & Development at EarlySense, the global leader in contact-free, continuous monitoring solutions for the healthcare continuum. He received his B.SC in Computer Engineering from the Technion Israel Institute of Technology and his MBA from Tel Aviv University. Guy is also the author of several issued and pending patents.
Read the full article at “Inside big data”
Particularly in post-acute settings, patient monitoring is crucial to preventing adverse events and rehospitalizations. And among the widely acknowledged five most important patient vital signs — body temperature, heart rate, blood pressure, respiratory rate, and SpO2 — researchers agree that respiratory rate may be the most important.
Topics: continuous monitoring
Contact-free continuous monitoring (CFCM) holds a significant amount of untapped potential for post-acute care centers and skilled nursing facilities: In a new white paper, research firm Frost & Sullivan calculates that the average U.S. post-acute care facility “could expect to see revenue increase by 22% and its net profit margin grow by 12.8%” by leveraging the technology to treat high-acuity patients.
Hospital referrals are essential to the post-acute business model, and becoming more so. As the industry continues to evolve towards value-based care and bundled payments, hospitals “are being pushed to assume greater risk for care episodes [that] can extend well beyond the acute care discharge” and onto their post-acute care partners, as H&HN Magazine points out.
The post-acute care market is more competitive than ever, with more and more facilities finding themselves pressed to not only increase their level and quality of patient care, but also their operational efficiencies and relationships with referring hospitals.
How Contact-Free Continuous Monitoring Can Help Post-Acute & Skilled Nursing Facilities Reduce Alarm Fatigue and Improve the Nursing Work Environment
For post-acute care and skilled nursing facilities looking to stay competitive in an industry with an ever-growing number of players and increasingly razor-thin margins, the implementation of contact-free continuous monitoring (CFCM) can be a key differentiator for ensuring long-term success.
Using an evidence-based model of healthcare delivery, the authors of a recent white paper argue that the typical American post-acute facility could experience double-digit increases in revenue and net profit growth by implementing contact-free continuous monitoring (CFCM) in just a portion of its beds.
Though predictions as to its severity fluctuate, America’s nursing shortage remains an ongoing concern for many healthcare facilities - and particularly among post-acute care centers and skilled nursing facilities, where market competition is intense and labor costs more acutely felt.
If you manage a post-acute center or a skilled nursing facility, you know only too well that a high rate of hospital readmissions means lost revenue, for a number of reasons: