mHealth ROI

The Role of Predictive Analytics & mHealth in Tackling Sepsis

July 11, 2016 | Uniphy Health

The recent death of Muhammad Ali is a solemn reminder of the life-threatening nature of sepsis. Sepsis arises from an infection and, if left undetected, can damage multiple organ systems, causing them to fail. Sepsis is a leading cause of death in acute care settings; the elderly and those in poor health are most vulnerable. Unchecked, sepsis is deadly: According to the Centers for Disease Control, nearly a million cases of sepsis occur every year, and up to half of those who get sepsis will die.

The good news is that the vast majority of sepsis deaths can be prevented through early detection and aggressive treatment. Advances in digital health will offer new and better methods of early detection and management. Clinical systems today already can monitor patient data and analyze symptom clusters to identify patients at risk. The challenge, however, is to bring together the patient data and analytical capabilities with an intelligent alerting system that notifies the right members of the care team and – and continues monitoring to ensure that necessary sepsis countermeasures have been performed.

Digital health tools that layer real-time data sharing, predictive analytics and mHealth onto hospitals’ existing EHR systems will enhance the effectiveness of sepsis prevention initiatives. Here is a look at the future of sepsis early detection:

Maximizing the value of EHR data capture
Relevant patient data will be collected and added to the EHR. Data relevant to signs of infection typically includes body temperature, heart rate, respiratory rate, white cell count and plasma glucose. To scan for signs of organ failure, additional data will be collected including mean arterial pressure, creatinine and bilirubin levels and platelet count. The EHR will also record time of sepsis identification, time of alert, response times, lactic acid order, bolus fluids ordered and administered and antibiotics ordered and administered.

Optimizing sepsis treatment plans with predictive analytics
Sophisticated analytical software continually monitors the clinical parameters to detect patterns indicative of sepsis and even to determine how advanced the condition may be. By feeding back outcome results into the system, the algorithm driving the analytics continues to evolve, becoming increasingly accurate. Typically, the algorithm tracks best-in-class evidence-based sepsis protocols such as lactate levels, fluids, antibiotics, vasopressors and cultures as well as response times.

Speeding sepsis response times with mHealth
Just as collecting the right data and analyzing it quickly and correctly are important, so too is delivering that analysis to the right person, fast. Data without a delivery system is not useful. Of course, the more intelligently that data is distributed, the better the entire solution will perform. Systems that send out too many alerts result in alert fatigue, causing the staff to become inured to them, assigning them lower priority or even ignoring them. The smartest systems will implement predetermined rules and policies under which only the care team members in the best position to respond are alerted, reducing alert fatigue and cutting response times.

Monitoring task performance and completion
The protocols for treating sepsis are well understood but also complex; treatment can last days or weeks before a patient is out of danger. The aggressiveness of the treatment varies based on how widespread the condition is. And follow-up steps depend on whether prior steps were successful. Thus the ability to track a patient’s progress, ensure that critical tasks are being performed – and send out additional alerts if needed – will also be a crucial element of and advanced sepsis alerting solution.

Reporting to regulatory bodies
In addition to saving lives, future sepsis alert solutions will also help healthcare organizations comply with government regulations for reporting the incidence of sepsis in their facilities and the outcomes of those who contracted the condition, a requirement dating to the passage of the Affordable Care Act. Such reporting – facilitated by automated systems for detection, alerting and response management – will eventually be incorporated into healthcare system ratings, allowing healthcare consumers to make better-informed care decisions by evaluating care options, in part, by how well they prevent sepsis.

Muhammad Ali’s family released the news that sepsis was the cause of death in the hope that bringing attention to the condition would help save lives. With automated processes for detecting sepsis, alerting the appropriate care team members and tracking the response to ensure critical tasks are performed, that noble purpose can become reality.