Purpose: Resource modeling aims to explicitly quantify the effects of adopting new health care technologies in settings with capacity-related constraints. The aim of this analysis was to use resource modeling to explore the effects of the uptake of first-line treatment with daratumumab on wait lists and wait times in patients with untreated multiple myeloma. Two formulations were compared: the standard IV formulation (DARA-IV) and a recently approved SC formulation (DARA-SC). Methods: First, semi-structured interviews at six oncologic centers were used to retrieve data on the management of patients given a DARA-IV regimen. Second, a discrete event simulation (DES) model was built to estimate the effects on resource consumption, wait lists, and wait times in scenarios with different incident numbers of patients treated with either DARA-IV or DARA-SC. Findings: In all of the simulated scenarios with more incident patients initiated on first-line treatment with DARA-IV, the actual capacity of infusion chairs was not enough to meet the demand, leading to increases in wait times and wait lists. In the highest-demand scenario, 17 more infusion chairs per center would be required to avoid such increases. Treatment with DARA-SC would allow centers to meet the demand with their actual capacity. Implications: DES modeling can effectively be used to formally explore the effects of different formulations on the use of limited resources, wait lists, and wait times at the facility level. Based on the findings from this analysis, DARA-SC may free up resources and prevent short- and long-term costs to infusion centers.

Use of resource modeling to quantify the organizational impact of subcutaneous formulations for the treatment of oncologic patients: the case of daratumumab in multiple myeloma

Federici, Carlo
Writing – Review & Editing
;
Rognoni, Carla
Data Curation
;
Costa, Francesco
Funding Acquisition
;
Armeni, Patrizio
Conceptualization
;
2022-01-01

Abstract

Purpose: Resource modeling aims to explicitly quantify the effects of adopting new health care technologies in settings with capacity-related constraints. The aim of this analysis was to use resource modeling to explore the effects of the uptake of first-line treatment with daratumumab on wait lists and wait times in patients with untreated multiple myeloma. Two formulations were compared: the standard IV formulation (DARA-IV) and a recently approved SC formulation (DARA-SC). Methods: First, semi-structured interviews at six oncologic centers were used to retrieve data on the management of patients given a DARA-IV regimen. Second, a discrete event simulation (DES) model was built to estimate the effects on resource consumption, wait lists, and wait times in scenarios with different incident numbers of patients treated with either DARA-IV or DARA-SC. Findings: In all of the simulated scenarios with more incident patients initiated on first-line treatment with DARA-IV, the actual capacity of infusion chairs was not enough to meet the demand, leading to increases in wait times and wait lists. In the highest-demand scenario, 17 more infusion chairs per center would be required to avoid such increases. Treatment with DARA-SC would allow centers to meet the demand with their actual capacity. Implications: DES modeling can effectively be used to formally explore the effects of different formulations on the use of limited resources, wait lists, and wait times at the facility level. Based on the findings from this analysis, DARA-SC may free up resources and prevent short- and long-term costs to infusion centers.
2022
Federici, Carlo; Rognoni, Carla; Costa, Francesco; Armeni, Patrizio; Crovato, Elisa; Bellucci, Stefania
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4052166
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