Abstract
Introduction: Cardiac telemetry is an in-hospital monitoring tool intended for ischemia surveillance, monitor QT-interval prolongation, and detect arrhythmias. It is a costly and limited resource that is frequently misused. Inappropriate telemetry use can lead to prolonged hospital stays, patient discomfort, alarm fatigue, and increased healthcare costs. We designed and implemented a telemetry guideline independent of the electronic health record (EHR) in an attempt to increase appropriate telemetry use in non-intensive care unit (ICU) setting Objectives: To design and implement a telemetry guideline. To increase appropriate use of telemetry. To practice cost-conscious, high-value care Aim: Primary Aim: Implement a telemetry guideline using pocket cards and educational conferences and monitor telemetry assignments Secondary Aim: Assess patient outcomes as reflected by the number of codes before and after the intervention Methods: We adopted telemetry criteria based on the American Heart Association guidelines from 2004 and other published literature. Baseline data was collected in November 2015 for all medicine teaching team admissions at our institution that came through the emergency department. Exclusion criteria were ICU transfers, step-down units, and direct admissions. Guidelines were then implemented via educational conferences and pocket card distribution to ED physicians, admitting hospitalists and medicine residents. Post-intervention data was collected from February through March 2016 Results: Of 180 admissions prior to guideline implementation, 93 patients (52%) went to non-telemetry beds and 87 patients (48%) to telemetry beds. Of the telemetry admissions, 60 patients (69%) were appropriately assigned to telemetry while 27 (31%) were not. After the guideline was implemented, 255 patients were reviewed. Of these, 110 (43%) went to telemetry beds, and 86 patients (78%) were appropriately assigned while 24 patients (22%) were not. There was no significant increase or decrease in the number of codes post intervention. Cost analysis revealed 103 telemetry-bed-days saved per month Conclusion: Our intervention resulted in a large (9.1%) but statistically insignificant increase in appropriate telemetry use. Although statistically insignificant, this improvement was durable across two months. Cost analysis revealed 103 telemetry-bed-days saved per month with an estimated savings of $100,000 in unnecessary charges. The relatively simple and cost-effective intervention of creating and implementing a telemetry assignment guideline was effective in changing telemetry ordering behavior. This was done without telemetry assignment logic in the EHR, which can be a tedious and time-consuming endeavor. Future efforts will include the implementation of a telemetry auditing tool, and ultimately the embedded logic to facilitate ordering practices.
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