Over the past decade, the University of Oklahoma College of Medicine has witnessed a significant rise in the number of highly complex infections. This is attributed to several factors such as the declining health of the Sooner State population, the increase in complex surgeries performed by surgeons at the Oklahoma City-based medical school, and the substantial growth in immunosuppressive therapeutics for various diseases. The health system has also noticed a surge in antimicrobial resistance, limiting therapeutic options to parenteral/intravenous antibiotics. In response to this need, the outpatient parenteral antimicrobial therapy (OPAT) program was established, allowing patients to receive intravenous antibiotics at home. However, the day-to-day operations and ensuring patient adherence pose challenges. Remote therapeutic monitoring (RTM) technology offers promising solutions in this regard.

How Remote Therapeutic Monitoring Works

The patented RTM device latches onto the tube coming out of the IV antibiotic bag/pump/IV push and detects the flow of medication through the tube using proprietary technology. It records the start and end times of infusion and transmits the data through cellular communication to the company's AI system called IVE Mind. This system compares the observed infusions with the expected infusions based on the patient's treatment plan prescribed by their physician and generates an adherence rate and a weekly adherence report. Accountability/monitoring occurs at two levels - the company provides a team of infusion case managers to monitor daily adherence data and communicate with the patient if there is any lapse in adherence. The weekly adherence reports are also scanned into the patient's medical record.

The software is capable of interfacing with the Epic EHR, ensuring seamless integration into the healthcare system. Upon consenting, the patient is given a monitoring device and receives structured follow-up support. The first phone call occurs the day after discharge to confirm enrollment and address any immediate questions. Weekly check-in calls are scheduled to monitor progress and encourage adherence. Additional calls are made if any adherence issues arise.

Results of the Clinical Trial

The University of Oklahoma College of Medicine conducted an interim analysis with 64 patients enrolled on RTM and 95 contemporaneous controls. The two groups were similar in terms of baseline demographic characteristics, type of infection, insurance coverage, comorbid conditions, prior healthcare utilization, duration of outpatient therapy, and number of antibiotic doses per day. The results showed a sharp decrease in infection-related readmissions in the RTM group. At 30 days, there was a 74% reduction (4.7% versus 17.9%), at 60 days a 72% reduction (7.8% versus 28.4%), and at 90 days a 56% reduction (14.1% versus 31.6%). When a multivariable logistic regression model was built, controlling for various factors, the odds of infection-related readmissions were decreased in the RTM group by 76% at 30 days, 80% at 60 days, and 68% at 90 days.

The sustained response is significant, showing that RTM can break the vicious circle of never-ending infections and hospital readmissions. The median overall adherence rate in the RTM group was 94%, but the range was 18% to 100%, indicating that some patients need more support. More than half of the patients in the RTM group needed an extra intervention from the study team, and two-thirds of these interventions happened within the first week after hospital discharge. This early identification of issues allowed for better patient care and set them up for success.

Advice for Others

Remote therapeutic monitoring is a major technological breakthrough that has the potential to transform healthcare. It can change clinical outcomes in a tangible and beneficial way, as demonstrated by the University of Oklahoma College of Medicine's clinical trial. Healthcare organizations and physician practices should evaluate how RTM can be incorporated into their clinical practice and value-based care models. It has a wide range of applications in healthcare delivery, not only within OPAT but also in other home infusion models and pharmaceutical research.

The data generated by RTM has driven the University of Oklahoma College of Medicine to simplify some antibiotic regimens for some patients, increasing their adherence to 100%. Patients enrolled in the trial also reported feeling supported during their transition of care and throughout their antibiotic course, which contributed to their success.