PO-03-054 OPTIMIZING REMOTE MONITORING ALERTS FOR CIED PATIENTS TO REDUCE RESOURCE UTILIZATION WITHOUT COMPROMISING CLINICAL CARE

Abstract

The benefits of remote monitoring (RM) have been demonstrated in multiple clinical studies and have become the standard of care for patients with cardiovascular implantable electronic devices (CIEDs). Benefits include fewer hospitalizations, reduction in mortality and improved clinical workflow by reducing in-office visits. As RM utilization increases, the amount of transmitted data can become a resource burden for responsible caregivers. To evaluate RM alert burden from actively monitored CIED patients within US-based integrated healthcare system to identify opportunities to optimize RM and a reduction of provider workload. We conducted an epidemiologic descriptive study using data from 9,781 CIED Patients from 7 healthcare centers within Kaiser Permanent who were monitored using BIOTRONIK Home Monitoring® (HM) from 1/1/22 through 7/31/22. Frequencies and proportions were used to describe alerts during the study period, as well as occurrence by device type. Patterns were identified that suggest specific alert programming differences leading to unnecessary alerts from a given healthcare centers or device type. In total, 9,781 active CIED patients enrolled in HM were analyzed. A total of 8,519 (87%) patients had ≥1 alert in the given timeframe. The distribution of device types in the patient population with an alert was: 5,725 (67%) implantable pulse generator (IPG), 132 (2%) cardiac resynchronization therapy pacemaker (CRT-P), 1,718 (20%) implantable cardioverter-defibrillator (ICD), 715 (8%) cardiac resynchronization therapy defibrillator (CRT-D) and 229 (3%) implantable cardiac monitors (ICM). A breakdown of alerts per patient per month shows that the majority (65%) of all alerts are generated by a minority of patients (20%). In conjunction with this finding, the alert per patient rate in this timeframe was the highest for ICM (15/patient) and CRT-D (13/patient) which represents 10% of all patients. Alert optimization is essential to reduce the work burden associated with RM. As shown in this analysis a limited number of patients (20%) are responsible for a significant portion of the overall alert burden (65%). We plan to target those high-volume alert sites as well as the specific alerts and specific patients to create server-based alert “templates” to optimize patient care and decrease alert burden for clinicians. A subsequent analysis will determine impact on patient outcomes and reduction in the burden of work.