Predictive Analytics, Continuous Monitoring Cut Medical Costs by $535K

Using continuous monitoring and predictive analytics can cut medical costs by nearly $535,000 annually, according to an economic data model from Medtronic.

Specifically, continuous pulse oximetry and capnography monitoring of high-risk patients receiving opioids could significantly reduced annual hospital costs for mid-sized hospitals.

Data was collected from the PRODIGY (PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY) trial.

According to the study, continuous monitoring could result in $535,531 annual hospital cost savings for a median-sized US hospital. Additionally, monitoring could decrease the cumulative patient length of stay by 103 days per year.

"Although respiratory depression occurs in 46% of patients receiving opioids on the general care floor, the cost-benefit of capnography and oximetry for continuous monitoring of patients had not yet been examined," Ashish K. Khanna, MD, primary study investigator and an associate professor of Anesthesiology, vice-chair for Research, and intensivist at the Wake Forest School of Medicine, said in a press release.

"Our findings suggest that compared to intermittent monitoring, investing in continuous monitoring of high-risk patients receiving opioids could reduce the cost burden and length of patient stay while potentially increasing patient safety. Our model suggests that a mere reduction of 1.5% in the incidence of respiratory depression would allow hospital systems to recover costs associated with the investment in monitoring. The expected reduction from deployment of continuous monitoring on hospital floors is way more," Khanna continued.

The economic model was created using a decision tree framework assessing how predictive analytic methods can improve clinical quality, outcomes, and ultimately costs.

The model simulates costs and outcomes of continuous pulse oximetry and capnography monitoring, compared to intermittent pulse oximetry monitoring for patients at high risk. The respiratory depression risks were based on the patient’s PRODIGY score.

The scores were developed from five independent patient characteristics, including age, gender, sleep-disordered breathing, opioid nativity, and chronic heart failure. The model then applied those results to the PRODIGY study to simulated a median-sized US hospital with 2,447 patients receiving opioids on a medical surgical floor each year.

"Respiratory compromise is a common, costly, potentially deadly — and preventable — condition. RC is a leading cause of ICU admissions and is one of the key contributing factors for code blues," Frank Chan, president of the Patient Monitoring business, which is part of the Medical Surgical Portfolio at Medtronic, said in a press release

"Medtronic has a deep-rooted history of discovering, developing, and commercializing transformative treatment options for patients globally. As RC continues to be studied, we are able to analyze these learnings and design innovative solutions to help physicians better care for their patients who may experience OIRD," Chan continued.

The PRODIGY trial also worked to develop and validate a risk stratification tool to help clinicians identify high risk patients receiving opioids.

“The PRODIGY risk stratification tool may support the recent updates from The Joint Commission on monitoring of post-operative patients receiving opioids with the requirement of putting in place a mechanism to identify high risk patients,” the press release concluded.