A NOVEL SYSTEM TO ADDRESS ADHERENCE BARRIERS IN CLINICAL PRACTICE DECREASES ALLOGRAFT REJECTION FOR KIDNEY TRANSPLANT PATIENTS

BackgroundPatient-identified barriers to taking immunosuppressive medications are associated with rejection and allograft loss in kidney transplant patients, yet interventions targeting adherence barriers are rarely integrated into clinical practice.ObjectivesTo decrease occurrences of allograft rejection by improving immunosuppressant adherence through development and implementation of an integrated in-clinic system to address adherence barriers in our population of 105 kidney transplant patients.MethodsUsing the Model for Improvement and iterative Plan-Do-Study-Act cycles, we implemented system components to identify and address barriers to adherence including: (1) pre-clinic automated screening for adherence risk using data from the electronic health record, (2) in-clinic assessment of 14 common barriers to adherence using a standardized checklist, (3) shared decision aids for barrier-specific, patient-centered interventions, and (4) optional electronic adherence monitoring. Using statistical process control, we performed time series analysis of process measures, individual patient adherence using electronic monitoring and our primary outcome measure of active patient days between late-rejection episodes (G-chart).ResultsWithin 5 months of implementing all system components, we achieved 10,451 active patient days between rejection episodes, nearly twice the previous high of 5,943 and above the upper control limit (7,939), indicating special cause. The reduction in expected rejections compared to the median (1,345) resulted in estimated savings of $680,000 in hospital charges.ConclusionsAn integrated system to address adherence barriers in the clinic was associated with reduced late-rejection episodes in kidney transplant patients. This approach may help address adherence barriers in other chronic conditions thereby improving health outcomes while reducing cost.Figure 1Key driver diagram.Figure 2 Patient days between late rejection episodes.Figure 3N of 1: Patient data over time.