A time-and-motion approach to micro-costing of high-throughput genomic assays.
Curr Oncol
; 23(5): 304-313, 2016 Oct.
Article
em En
| MEDLINE
| ID: mdl-27803594
ABSTRACT
BACKGROUND:
Genomic technologies are increasingly used to guide clinical decision-making in cancer control. Economic evidence about the cost-effectiveness of genomic technologies is limited, in part because of a lack of published comprehensive cost estimates. In the present micro-costing study, we used a time-and-motion approach to derive cost estimates for 3 genomic assays and processes-digital gene expression profiling (gep), fluorescence in situ hybridization (fish), and targeted capture sequencing, including bioinformatics analysis-in the context of lymphoma patient management.METHODS:
The setting for the study was the Department of Lymphoid Cancer Research laboratory at the BC Cancer Agency in Vancouver, British Columbia. Mean per-case hands-on time and resource measurements were determined from a series of direct observations of each assay. Per-case cost estimates were calculated using a bottom-up costing approach, with labour, capital and equipment, supplies and reagents, and overhead costs included.RESULTS:
The most labour-intensive assay was found to be fish at 258.2 minutes per case, followed by targeted capture sequencing (124.1 minutes per case) and digital gep (14.9 minutes per case). Based on a historical case throughput of 180 cases annually, the mean per-case cost (2014 Canadian dollars) was estimated to be $1,029.16 for targeted capture sequencing and bioinformatics analysis, $596.60 for fish, and $898.35 for digital gep with an 807-gene code set.CONCLUSIONS:
With the growing emphasis on personalized approaches to cancer management, the need for economic evaluations of high-throughput genomic assays is increasing. Through economic modelling and budget-impact analyses, the cost estimates presented here can be used to inform priority-setting decisions about the implementation of such assays in clinical practice.
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Coleções:
01-internacional
Temas:
Geral
Base de dados:
MEDLINE
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
Idioma:
En
Revista:
Curr Oncol
Ano de publicação:
2016
Tipo de documento:
Article