ABSTRACT
Background: Inter- and intra-individual variability in tacrolimus dose requirements mandates empirical clinician-titrated dosing that frequently results in deviation from a narrow target range. Improved methods to individually dose tacrolimus are needed. Our objective was to determine whether a quantitative, dynamically-customized, phenotypic-outcome-guided dosing method termed Phenotypic Personalized Medicine (PPM) would improve target drug trough maintenance. Methods: In a single-center, randomized, pragmatic clinical trial ( NCT03527238 ), 62 adults were screened, enrolled, and randomized prior to liver transplantation 1:1 to standard-of-care (SOC) clinician-determined or PPM-guided dosing of tacrolimus. The primary outcome measure was percent days with large (>2 ng/mL) deviation from target range from transplant to discharge. Secondary outcomes included percent days outside-of-target-range and mean area-under-the-curve (AUC) outside-of-target-range per day. Safety measures included rejection, graft failure, death, infection, nephrotoxicity, or neurotoxicity. Results: 56 (29 SOC, 27 PPM) patients completed the study. The primary outcome measure was found to be significantly different between the two groups. Patients in the SOC group had a mean of 38.4% of post-transplant days with large deviations from target range; the PPM group had 24.3% of post-transplant days with large deviations; (difference -14.1%, 95% CI: -26.7 to -1.5 %, P=0.029). No significant differences were found in the secondary outcomes. In post-hoc analysis, the SOC group had a 50% longer median length-of-stay than the PPM group [15 days (Q1-Q3: 11-20) versus 10 days (Q1-Q3: 8.5-12); difference 5 days, 95% CI: 2-8 days, P=0.0026]. Conclusions: PPM guided tacrolimus dosing leads to better drug level maintenance than SOC. The PPM approach leads to actionable dosing recommendations on a day-to-day basis. Lay Summary: In a study on 62 adults who underwent liver transplantation, researchers investigated whether a new dosing method called Phenotypic Personalized Medicine (PPM) would improve daily dosing of the immunosuppression drug tacrolimus. They found that PPM guided tacrolimus dosing leads to better drug level maintenance than the standard-of-care clinician-determined dosing. This means that the PPM approach leads to actionable dosing recommendations on a day-to-day basis and can help improve patient outcomes.
ABSTRACT
BACKGROUND: Medication errors are one of the leading causes of complications and readmissions in healthcare and stem directly from inadequate medication lists. In transplantation, medication discrepancies can lead to fluctuating levels of immunosuppression, resulting in rejection, infection, or drug toxicity. METHODS: We implemented a pharmacist-driven intervention designed to improve the accuracy of outpatient kidney transplant patients' medication lists in the electronic medical record (EMR). Baseline medication error rates (Phase 1) were collected, and the intervention was a dedicated pharmacist (Phase 2) who performed medication reconciliation with patients. The primary outcome was the percent of patients with inadequate medication reconciliation determined by any one error in medication reconciliation (Phase 1 vs Phase 2). Secondary outcomes included the number of medication errors, of all medications and high-risk medications, identified per patient sample using statistical process control phase analysis. RESULTS: Pharmacist-driven medication reconciliation significantly reduced medication list discrepancies from 95% to 28% (P<0.05). There were a total of 398 errors in the control group and 49 errors in the intervention group. In addition, there were 73 high-risk medication discrepancies in the control group and three in the intervention group. The total number of medication errors decreased post-intervention with a marked reduction in the variation of control limits (LCL, UCL: phase 1, -34.3, 113.9; phase 2, -7.1, 15.3) and average number of medication errors per sample (phase 1, 39.8; phase 2, 14.1). For high-risk medications, phase analysis demonstrated a marked reduction in control limit variation between phases (LCL, UCL: phase 1, -10.4, 25.0; phase 2, -0.5, 0.7) and average number of medication errors per sample (phase 1, 7.3; phase 2, 0.1). DISCUSSION: A dedicated pharmacist improved medication list accuracy over conventional practice that utilizes transplant nurses and physicians. Further studies into the cost-effectiveness of this strategy should further justify this approach.
