Three Ways Clinical Surveillance is Helping Prevent Patient Care Problems

Clinical surveillance can help healthcare systems more quickly identify clinical care problems, such as those related to medication errors and poor usage of antibiotics. But it can also help healthcare systems prevent problems from occurring in the first place.

That’s according to Bart Abban, PhD, director of analytics and data science at VigiLanz, who spoke about predictive analytics and clinical surveillance at the recent HIMSS Conference in Orlando.

“We’ve fully integrated a machine-learning platform into our real-time system,” said Abban, during his presentation. “We can look forward [at potential events], look in real time, and look back at historical data. It’s a fully closed-loop.”

Firm foundation needed

Much of the foundation of predictive analytics, Abban noted, comes from creating rules and alerts based on historical data. “You need a data repository,” he said. “We have vast amount of rich data, years and years of data.”

To view Abban’s full presentation, click here.

Health systems have many predictive analytics solutions to choose from. But Abban said VigiLanz stands apart because it provides a broader spectrum of alerts and customizations related to all types of patient care problems.

“With our platform you can do readmissions today, tomorrow you can start looking at mortality risk, you can look at adverse events, glycemic control,” he said. “We are currently developing a model on C. diff to alert clinicians to patients who are at high risk of getting C. diff. The sky is the limit.”

For more on how health systems are using clinical surveillance to enhance patient care, read “Clinical Surveillance: The Next Step in Value-Based Care.”

Three applications

Abban shared three examples of how VigiLanz is providing predictive analytics to health systems: 

  1. Sepsis

Since many hospitalized patients have symptoms that resemble sepsis, it can be difficult for providers to identify sepsis cases or identify patients who are most at risk. VigiLanz created a rules engine so that hospitals can use certain criterion—such as vital signs, labs, microbiology, comorbidities, and medications—to identify patients at risk. VigiLanz can then alert providers when patients are at risk, and providers can monitor these patients more closely and treat them proactively. Since data is updated in near real time, providers always have access to the most up-to-date information related to patients at risk.

  1. Acute kidney injury

Certain medications are essential for patients, but they can also lead to acute-kidney injury. The conventional approach is to monitor patients via labs, however, that means providers can only intervene after injury has already occurred. VigiLanz created a series of risk factors that can help providers more closely monitor patients, and proactively adjust medications as needed.

Risk factors include:

  • High risk nephrotoxic medications
  • Other drugs administered
  • Age, race, chronic morbidities, ICU stay or surgery
  • Specific labs
  1. Anomaly detection

VigiLanz created a rules-based engine to help health systems monitor the likelihood of a cluster or outbreak of hospital-acquired infections.. VigiLanz created alerts based on algorithms for various types of infections, and health systems are able to configure their own alert thresholds depending on their needs, areas of concern, and priorities.

Health systems using the VigiLanz platform to improve patient care and prevent patient care problems can rest assured that critical alerts won’t be missed by providers, said Abban. He noted that VigiLanz can track whether providers are taking actions related to the alerts they receive. If not, alerts can be reissued or the health system can follow up with providers directly. “It’s a whole ecosystem where you can extract the value of predictive analytics,” he said.

Top 4 Ways Health Systems Benefit from An API Approach to Clinical Surveillance

Speed is one of the most essential attributes of an effective approach to clinical surveillance. The faster patient data can be pulled from the EMR and sorted by clinical surveillance technology, the more quickly physicians and pharmacists can receive targeted alerts that lead to more optimal patient care decisions.

These alerts might be related to the identification of potential medication errors, the inappropriate use of antibiotics, or a possible outbreak of an infection such as C. diff.

To read about how health systems are using clinical surveillance to enhance patient care, read  “Clinical Surveillance: The Next Step in Value-Based Care.”

At the recent HIMSS Conference in Orlando, Adam Klass, chief technology officer at VigiLanz, and Dave Levin, MD, chief medical officer, Sansoro Health, spoke about how application programming interfaces (APIs) can be a gamechanger in clinical surveillance because they help data flow between EMRs and clinical surveillance solutions more quickly.

To view their full presentation, click here.

“We’re dealing with really important clinical problems here, and the sooner we can get these solutions in place and begin to impact the outcomes, the better for everyone,” said Levin.

APIs vs. HL7

For many years, most healthcare systems have transferred data from EMRs to outside solutions, such as clinical surveillance technology, via HL7 interfaces. But there are some drawbacks to this approach.

According to Klass:

  • The HL7 standard is interpreted in many different ways, which can raise confusion.
  • Hospital IT departments must spend time validating transferred data to ensure it is exchanging properly.
  • The approach requires building interfaces and maintaining them, which can be costly and time-consuming.

API data acquisition and transfer, on the other hand, provides a “more unified” data model, Klass said.  Information is pulled from the EMR in near real time, in a standard format, and it’s always sent to partners the same way, regardless of the EMR from which it originates.

“The value as you build out a full API footprint is getting that full clinical model from Day 1, so you’re not having to circle back to healthcare organizations to gather more data over time,” Klass said. “The hospital IT team involvement becomes significantly less as you use these APIs. The cost is also significantly less because you remove the maintenance and support that goes into supporting interfaces.”

Growing movement

More and more hospitals are recognizing the benefits of the API approach to data transfer. In fact, 30 health systems are already using APIs to exchange EMR data with VigiLanz’s platform, and many more are starting to implement the technology, said Klass.

He cited the following four benefits:

  • Less hospital IT department time spent on clinical surveillance.
  • Reduced hospital costs associated with clinical surveillance (hospitals no longer need to build interfaces, oversee numerous file transfers, or bring in consultants to assist with the work).
  • Faster implementations.
  • Broader accessibility for providers to clinical surveillance tools immediately after implementation.

Levin agrees. “An API approach to integration greatly reduces the amount of time that’s required to deploy the [clinical surveillance] solution and that translates into a cost savings,” he said. “But more importantly, it translates into a better user experience, a richer data set that takes a product that’s already really good and makes it even better.”