Design and implementation of an online tool for managing the availability of high-cost perishable medicines.

Introduction: Due to their impact on healthcare systems, the sustainability and optimization of high-cost drugs is an issue of concern for several countries. Different strategies have been implemented such as centralized purchasing to optimize budgetary resources. However, there is still a need for a mechanism to optimize these drugs further. Methods: We conducted this prospective multicenter intervention study in five hospitals in the Andalusian Public Health System of Cádiz (Spain) between July 2019 and September 2021. We developed an online website (Farmastock) and implemented it to determine the availability of high-cost, low-use, and near-expiry medicines in each hospital. We used a simple analysis using operational variables to assess the project intervention's savings impact on managing these high-cost drugs. Results: The implementation of Farmastock in Cádiz resulted in savings of 675,757.52 € for the Andalusian Public Health System, with 238 medicines transferred out of the 373 available. Of these medicines offered, the most considerable percentage were medicines used for pathologies with high clinical instability and accounted for nearly 80% of the medicines optimized by the tool. Conclusions: Farmastock allowed the Andalusian Public Health System to make substantial financial savings by not making new purchases of high-cost drugs available in other centers of this health network that were not being used. Therefore, this tool is a very efficient measure to contribute to the sustainability of the APHS and could be implemented in more hospitals soon.

Risk stratification model for the pharmaceutical care of oncology patients with solid or hematologic neoplasms. / [Artículo traducido] Modelo de estratificación de riesgo de atención farmacéutica para pacientes oncológicos con neoplasias sólidas o hematológicas.

OBJECTIVE: We aimed to develop of a risk stratification model for the pharmaceutical care (PC) of patients with solid or hematologic neoplasms who required antineoplastic agents or supportive treatments. METHOD: The risk stratification model was collaboratively developed by oncology pharmacists from the Spanish Society of Hospital Pharmacy (SEFH). It underwent refinement through three workshops and a pilot study. Variables were defined, grouped into four dimensions, and assigned relative weights. The pilot study collected and analyzed data from participating centers to determine priority levels and evaluate variable contributions. The study followed the Kaiser Permanente pyramid model, categorizing patients into three priority levels: Priority 1 (intensive PC, 90th percentile), Priority 2 (60th-90th percentiles), and Priority 3 (60th percentile). Cut-off points were determined based on this stratification. Participating centers recorded variables in an Excel sheet, calculating mean weight scores for each priority level and the total risk score. RESULTS: The participants agreed to complete a questionnaire that comprised 22 variables grouped into 4 dimensions: demographic (maximum score =11); social and health variables and cognitive and functional status (maximum = 19); clinical and health services utilization (maximum = 25); and treatment-related (maximum = 41). From the results of applying the model to the 199 patients enrolled, the cutoff points for categorization were 28 or more points for priority 1, 16 to 27 points for priority 2 and less than 16 for priority 3; more than 80% of the total score was based on the dimensions of 'clinical and health services utilization' and 'treatment-related'. Interventions based on the pharmaceutical care model were recommended for patients with solid or hematological neoplasms, according to their prioritization level. CONCLUSION: This stratification model enables the identification of cancer patients requiring a higher level of pharmaceutical care and facilitates the adjustment of care capacity. Validation of the model in a representative population is necessary to establish its effectiveness.

Risk stratification model for the pharmaceutical care of oncology patients with solid or hematologic neoplasms.

OBJECTIVE: We aimed to develop of a risk stratification model for the pharmaceutical care of patients with solid or hematologic neoplasms who required antineoplastic agents or supportive treatments. METHOD: The risk stratification model was collaboratively developed by oncology pharmacists from the Spanish Society of Hospital Pharmacy (SEFH). It underwent refinement through 3 workshops and a pilot study. Variables were defined, grouped into 4 dimensions, and assigned relative weights. The pilot study collected and analyzed data from participating centers to determine priority levels and evaluate variable contributions. The study followed the Kaiser Permanente pyramid model, categorizing patients into 3 priority levels: Priority 1 (intensive PC, 90th percentile), Priority 2 (60th-90th percentiles), and Priority 3 (60th percentile). Cut-off points were determined based on this stratification. Participating centers recorded variables in an Excel sheet, calculating mean weight scores for each priority level and the total risk score. RESULTS: The participants agreed to complete a questionnaire that comprised 22 variables grouped into 4 dimensions: demographic (maximum score=11); social and health variables and cognitive and functional status (maximum=19); clinical and health services utilization (maximum=25); and treatment-related (maximum=41). From the results of applying the model to the 199 patients enrolled, the cut-off points for categorization were 28 or more points for priority 1, 16-27 points for priority 2, and less than 16 for priority 3; more than 80% of the total score was based on the dimensions of "clinical and health services utilization" and "treatment-related." Interventions based on the pharmaceutical care model were recommended for patients with solid or hematological neoplasms, according to their prioritization level. CONCLUSION: This stratification model enables the identification of cancer patients requiring a higher level of pharmaceutical care and facilitates the adjustment of care capacity. Validation of the model in a representative population is necessary to establish its effectiveness.