RESUMEN
Clinical research faces complex and unpredictable budgetary challenges, despite its central role in the development of healthcare products. This retrospective study examines the estimated and actual costs of 13 trials managed by the Clinical Trials Coordinating Pharmacy at the University Hospital of Toulouse. It aims to assess the accuracy of estimates, identify trial-influencing events and identify budget adjustment variables. The results show that only two of the 13 studies stay within their initial estimates, with most exceeding their projected margins. Costs vary by area, with shipping and packaging in particular exceeding the initial budget, while distribution costs are more accurately estimated. Several factors influence costs, including study duration, centre locations, number of enrolments, product stability and protocol amendments. Extending the study duration leads to increased costs in all areas, while reducing the number of inclusions tends to be in line with the original budget. In conclusion, budget management in clinical trials is complex due to numerous influencing variables. Careful planning and consideration of the specifics of each trial are crucial for more accurate estimates and budget adherence. This study enhances the understanding of the financial challenges faced by institutional sponsors of clinical trials and contributes to the refinement of budgeting methods for future clinical trials.
RESUMEN
RATIONALE, AIM, AND OBJECTIVE: There are several ways to establish an accurate medication list in the hospital admission medication reconciliation (MedRec). The challenge for MedRec lies in the availability, reliability, and completeness of the data used. In France, the Electronic Pharmaceutical Record (ePR) was developed to register each medication taken by ambulatory patients, primarily to make dispensation in community pharmacies safe. We evaluated the suitability of this tool in the MedRec when patients were admitted to the hospital. METHOD: We conducted a 6-month pilot study of 249 MedRec files from a hospital diabetology department. The analysis was supplemented by the ePR for any patient for whom this information was recorded. The study evaluated the ePR as a new MedRec tool, as well as the clinical impact (CI) of the new data collected. RESULTS: The ePR was contributory for 28% of the patients. Discrepancies were associated with polypharmacy, most of which had a CI = 1. Medication omission was the most frequently found discrepancy (72%), but self-medication (8%) and lack of medication adherence (9%) were also observed. CONCLUSION: This tool provided added value for reconciliation, as it quickly identifies regular medications, adherence, and self-medication behaviour. The ePR is essential for conducting a thorough MedRec.
Asunto(s)
Sistemas de Información en Farmacia Clínica/estadística & datos numéricos , Registros Electrónicos de Salud/estadística & datos numéricos , Sistemas de Entrada de Órdenes Médicas/estadística & datos numéricos , Errores de Medicación/prevención & control , Conciliación de Medicamentos , Anciano , Femenino , Francia/epidemiología , Humanos , Masculino , Cumplimiento de la Medicación/estadística & datos numéricos , Conciliación de Medicamentos/métodos , Conciliación de Medicamentos/organización & administración , Administración del Tratamiento Farmacológico/organización & administración , Persona de Mediana Edad , Admisión del Paciente/estadística & datos numéricos , Proyectos Piloto , Reproducibilidad de los Resultados , Automedicación/estadística & datos numéricosRESUMEN
OBJECTIVES: Since 2007, a number of transplantation centers have been routinely using an expert system for tacrolimus (TAC) dose adjustment in kidney allograft recipients, based on PK modeling and Bayesian estimation for area-under-the-curve (AUC) determination. This has allowed the setting up of a large database of TAC pharmacokinetic profiles and AUC values, a part of which was analyzed here. METHODS: We retrospectively studied 2030 requests posted by 21 different centers for routine TAC dose adjustment in 1000 different adult renal transplant patients (not enrolled in any kind of concentration-controlled clinical trial). For each request, the following information was obtained: time elapsed since transplantation, TAC daily dose, calculated AUC, and trough concentration (C0). RESULTS: The dose-standardized exposure to TAC significantly and progressively increased in the months after transplantation: from month (M) 1 to M9 C0/dose increased from 2.33 to 3.44 mcg·L(1)·mg(1) and AUC/dose from 43.1 to 64.2 mcg·h(1)·L(1)·mg(1), respectively. On the contrary, in patients beyond the first year whose C0 or AUC was in the target range, the odds of remaining in this range were high for a long time period, suggesting a low intrapatient variability in the stable phase. Regression analyses showed that the correlation between C0 and AUC was better in the first 3-month period (r(2) = 0.76) than later on (r(2) ≤ 0.67). Using the regression equations obtained, AUC ranges corresponding to different applicable C0 targets were calculated. CONCLUSIONS: From a large number of kidney graft recipients, we have estimated the relationships between C0 and AUC, modeled the evolution of TAC exposure with time and defined AUC targets that could be useful to lead further controlled-concentration trials and improve routine TAC therapeutic drug monitoring.