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Article

A Time-and-Motion Approach to Micro-Costing of High-Throughput Genomic Assays

1
Canadian Centre for Applied Research in Cancer Control, BC Cancer Agency, Vancouver, BC, Canada
2
Department of Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada
3
School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
4
Centre for Lymphoid Cancer, BC Cancer Agency, Vancouver, BC, Canada
5
Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
6
Department of Medicine, University of British Columbia, Vancouver, BC, Canada
7
Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC, Canada
8
Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
9
Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
*
Author to whom correspondence should be addressed.
Curr. Oncol. 2016, 23(5), 304-313; https://doi.org/10.3747/co.23.2987
Submission received: 12 July 2016 / Revised: 15 August 2016 / Accepted: 12 September 2016 / Published: 1 October 2016

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.
Keywords: Personalized medicine; micro-costing; time-and-motion analyses; genomic technology; economic evaluations Personalized medicine; micro-costing; time-and-motion analyses; genomic technology; economic evaluations

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MDPI and ACS Style

Costa, S.; Regier, D.A.; Meissner, B.; Cromwell, I.; Ben-Neriah, S.; Chavez, E.; Hung, S.; Steidl, C.; Scott, D.W.; Marra, M.A.; et al. A Time-and-Motion Approach to Micro-Costing of High-Throughput Genomic Assays. Curr. Oncol. 2016, 23, 304-313. https://doi.org/10.3747/co.23.2987

AMA Style

Costa S, Regier DA, Meissner B, Cromwell I, Ben-Neriah S, Chavez E, Hung S, Steidl C, Scott DW, Marra MA, et al. A Time-and-Motion Approach to Micro-Costing of High-Throughput Genomic Assays. Current Oncology. 2016; 23(5):304-313. https://doi.org/10.3747/co.23.2987

Chicago/Turabian Style

Costa, S., D.A. Regier, B. Meissner, I. Cromwell, S. Ben-Neriah, E. Chavez, S. Hung, C. Steidl, D.W. Scott, M.A. Marra, and et al. 2016. "A Time-and-Motion Approach to Micro-Costing of High-Throughput Genomic Assays" Current Oncology 23, no. 5: 304-313. https://doi.org/10.3747/co.23.2987

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