Kelly L Covert1, Caitlin R Mardis2, James N Fleming3, Nicole A Pilch3, Holly B Meadows3, Benjamin A Mardis3, Prince Mohan4, Maria Posadas-Salas4, Titte Srinivas4, David J Taber5,6. 1. Department of Pharmacy Practice, Bill Gatton College of Pharmacy, East Tennessee State University, Johnson City, Tennessee. 2. Transplant Service Line, Medical University of South Carolina, Charleston, South Carolina. 3. Department of Pharmacy Services, Medical University of South Carolina, Charleston, South Carolina. 4. Department of Transplant Nephrology, Medical University of South Carolina, Charleston, South Carolina. 5. Department of Surgery, Medical University of South Carolina, Charleston, South Carolina. 6. Department of Pharmacy, Ralph H. Johnson VAMC, Charleston, South Carolina.
Abstract
STUDY OBJECTIVE: Drug-related problems (DRPs) are associated with increased rates of infection, rejection, and graft loss in kidney transplant recipients. This study aimed to develop a model to predict which patients are at highest risk of DRPs to streamline pharmacists' workflow in a chronic kidney transplant clinic. DESIGN: Prospective observational study. SETTING: Chronic kidney transplant clinic at a large, tertiary care, academic hospital. PATIENTS: Two hundred thirty-seven adults seen in the kidney transplant clinic between September 16, 2015, and November 30, 2015, who were at least 90 days posttransplantation at the time of their clinic visit. MEASUREMENTS AND MAIN RESULTS: Prospective data detailing DRPs and a survey assessing baseline characteristics and patient-related outcomes were used to generate a predictive model to identify patients at risk of having six or more DRPs; the cutoff of six DRPs provided a threshold for identifying a subset of high-risk patients on whom the transplant pharmacists could focus their efforts. DRPs were categorized as nonadherence, overdosing or underdosing, duplication of therapy, preventable adverse drug reaction, missing medication, erroneous medication, conflicting provider information, undermonitoring or lack of monitoring, and wrong medication received. In total, 865 unique DRPs were identified, and the most common were erroneous medication, missing medication, and nonadherence, accounting for 38%, 21%, and 16% of the DRPs, respectively. A nine-variable model with a sensitivity of 62.5% and specificity of 66.7% (area under the receiver operating characteristic curve of 0.720) was developed to identify patients at risk of having six or more DRPs. The model included the following variables: age, Medicaid for prescription insurance, current employment status, medication affordability, difficulty or lack of difficulty obtaining medications from the pharmacy, negative impact of medications on quality of life, medication nonadherence, poor rating of current health status, and moderate or poor medication understanding. CONCLUSION: These results demonstrated that a straightforward, 5-minute survey completed by renal transplant recipients prior to their clinic visit may be capable of effectively determining those at risk of having six or more DRPs, potentially allowing use as a screening tool for transplant pharmacists' workflow prioritization. External validation is needed before this tool can be used in the outpatient setting.
STUDY OBJECTIVE: Drug-related problems (DRPs) are associated with increased rates of infection, rejection, and graft loss in kidney transplant recipients. This study aimed to develop a model to predict which patients are at highest risk of DRPs to streamline pharmacists' workflow in a chronic kidney transplant clinic. DESIGN: Prospective observational study. SETTING: Chronic kidney transplant clinic at a large, tertiary care, academic hospital. PATIENTS: Two hundred thirty-seven adults seen in the kidney transplant clinic between September 16, 2015, and November 30, 2015, who were at least 90 days posttransplantation at the time of their clinic visit. MEASUREMENTS AND MAIN RESULTS: Prospective data detailing DRPs and a survey assessing baseline characteristics and patient-related outcomes were used to generate a predictive model to identify patients at risk of having six or more DRPs; the cutoff of six DRPs provided a threshold for identifying a subset of high-risk patients on whom the transplant pharmacists could focus their efforts. DRPs were categorized as nonadherence, overdosing or underdosing, duplication of therapy, preventable adverse drug reaction, missing medication, erroneous medication, conflicting provider information, undermonitoring or lack of monitoring, and wrong medication received. In total, 865 unique DRPs were identified, and the most common were erroneous medication, missing medication, and nonadherence, accounting for 38%, 21%, and 16% of the DRPs, respectively. A nine-variable model with a sensitivity of 62.5% and specificity of 66.7% (area under the receiver operating characteristic curve of 0.720) was developed to identify patients at risk of having six or more DRPs. The model included the following variables: age, Medicaid for prescription insurance, current employment status, medication affordability, difficulty or lack of difficulty obtaining medications from the pharmacy, negative impact of medications on quality of life, medication nonadherence, poor rating of current health status, and moderate or poor medication understanding. CONCLUSION: These results demonstrated that a straightforward, 5-minute survey completed by renal transplant recipients prior to their clinic visit may be capable of effectively determining those at risk of having six or more DRPs, potentially allowing use as a screening tool for transplant pharmacists' workflow prioritization. External validation is needed before this tool can be used in the outpatient setting.
Authors: Steven Craig Vranian; Kelly L Covert; Caitlin R Mardis; John W McGillicuddy; Kenneth D Chavin; Derek Dubay; David J Taber Journal: J Surg Res Date: 2018-02 Impact factor: 2.192
Authors: David J Taber; Mulugeta Gebregziabher; Aurora Posadas; Caitlin Schaffner; Leonard E Egede; Prabhakar K Baliga Journal: J Am Coll Clin Pharm Date: 2018-06-21