Abstract
ObjectiveWe 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. MethodThe 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. ResultsThe 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. ConclusionThis 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.
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