How interventional analytics can help reduce readmission rates
Imagine you’re driving to the beach. It’s supposed to be a two-hour drive, but traffic and construction can affect your journey—sometimes by a lot. Ten years ago, you might have used a store-bought map or even directions printed from the internet. That provided plenty of information, but it was static. If there was a wreck causing a bottleneck 20 miles ahead, you wouldn’t know until you got there. Today, though, you use an app that tells you the most efficient way to go. The app updates conditions on the fly, so you find out about that bottleneck when it happens. And you learn how to avoid it. Your drive to the beach is smooth sailing because you have access to real-time data.
Interventional analytics is a lot like that app. It provides you with real-time data so you can avoid adverse situations and know when it’s smooth sailing. Only instead of bad traffic, you’re heading off clinical issues, improving patient care, reducing readmissions, and managing the length of stay by guiding clinicians to provide proactive care.
Predictive analytics vs. Interventional analytics in healthcare
It wasn’t long ago that predictive analytics represented the cutting edge of statistics usage in healthcare. By mining data and modeling likely outcomes, we could assess risk for large numbers of individual patients and make informed decisions. But predictive analytics relies on dated, static information and provides generalized predictions of “what could” happen.
Interventional analytics goes beyond predictive analytics. Using complex algorithms, interventional analytics uses software that “sits on top” of any electronic health record (EHR). Interventional Analytics sifts through vast amounts of data points, finds a correlation between them, and determines possible outcomes. It uses this real-time data to push live patient alerts to clinicians, informing them that something adverse is happening. Not only that, it also provides suggested interventions based on national standards of care (ex. AMDA and INTERACT 3.0) that prevent readmissions and improves quality outcomes.
Using interventional analytics to reduce readmissions
Interventional analytics has been proven to reduce readmissions by 50% in three key ways:
- Live Interventional Alerts. Using live data within the EHR, interventional analytics detects a patient’s change in condition as they occur. When the data indicates the potential for a negative outcome based on predefined parameters, a clinical alert is immediately sent to the clinician. This alert adds the diagnosis and provides specific intervention recommendations so assessment and treatment can be performed immediately-avoiding readmission to the hospital.
- Optimize Nurse Time. By delivering live clinical insights from the EHR system, you can focus on patients who are at high risk for readmission. By automating standup meetings, you reduce what can sometimes require multiple hours of time and lots of reports down to about 15 minutes – allowing nurses to focus on the patient’s care.
- Enterprise Dashboards. Getting the right data, to the right person, in real-time is imperative for healthcare facilities. Through interventional analytics, Enterprise dashboards are generated utilizing the live data within the EHR, searching nursing notes, and flagging keywords (e.g. impaction, dehydration, wandering, etc.).
All these tactics help reduce readmission rates by focusing on specific patient needs, ultimately delivering improved clinical outcomes, reduced systemic cost, and increased patient care.
Creating a coordinated care network
According to Scott Rifkin, superior patient care shouldn’t end at any hospital’s or facility’s doors. Patients are best served when hospitals and skilled nursing facilities work together to provide coordinated care. If both skilled nursing facilities and hospitals are using an interventional analytics system, they can effectively provide customized care and reduce readmissions by up to 50%.
If you are interested in learning more about interventional analytics and how it can reduce your readmissions, contact us to schedule a demonstration.
About Real Time Medical Systems
Real Time Medical Systems is the leading healthcare interventional analytics company helping to improve the patient care continuum by connecting long-term care facilities, hospitals, ACOs, payers, and affiliated providers in building an integrated preferred care network.
Empowering a proactive approach to patient-centered care, Real Time’s interventional analytics platform was developed for skilled nursing facilities to easily identify patients who had a change in care condition and intervene immediately before re-hospitalization occurred – helping to improve clinical and financial performance while reducing readmission rates by 50%. Since launching their interventional analytics platform in 2012, Real Time has expanded their solution offering to include fully-integrated applications which allow hospitals, ACOs, payers, and affiliated providers to connect and collaborate with their post-acute care networks.
Operating in 800+ facilities and monitoring over 100,000+ lives – Real Time continues to ensure patient-centered care is at the forefront for its clients.
For more information or to request a demonstration of the Real Time ProACT HS application, contact Tommy Pfeiffer, Director of Health System Solutions at [email protected]