C Zwerling1, J Ryan, E J Orav. 1. Department of Preventive Medicine and Environmental Health, College of Medicine, University of Iowa, Iowa City 52242.
Abstract
OBJECTIVE: This study provides a cost-benefit analysis of preemployment drug screening and evaluates the sensitivity of this analysis to variation in its underlying assumptions. DESIGN: Cost-benefit analysis, based on a cohort analytic study previously reported. SETTING: Employees of the US Postal Service in Boston, Mass. PARTICIPANTS: Estimates of costs and benefit are based on a cohort of 2533 postal workers in Boston and on average costs for the Postal Service in Boston and nationwide. RESULTS: Drug screening would have saved the Postal Service $162 per applicant hired. However, these results were sensitive to the assumptions in the model. If the prevalence of drug use in the population screened were 1% rather than 12%, the program would lose money. Similarly, if the cost per urine sample screened were $95 rather than the $49 assumed, then the program would lose money, even if the prevalence of drug positives was as high as 9%. CONCLUSIONS: Because of the sensitivity of this analysis to changes in its underlying assumptions, any company considering preemployment drug screening should carefully weigh the costs and benefits in its own industry.
OBJECTIVE: This study provides a cost-benefit analysis of preemployment drug screening and evaluates the sensitivity of this analysis to variation in its underlying assumptions. DESIGN: Cost-benefit analysis, based on a cohort analytic study previously reported. SETTING: Employees of the US Postal Service in Boston, Mass. PARTICIPANTS: Estimates of costs and benefit are based on a cohort of 2533 postal workers in Boston and on average costs for the Postal Service in Boston and nationwide. RESULTS: Drug screening would have saved the Postal Service $162 per applicant hired. However, these results were sensitive to the assumptions in the model. If the prevalence of drug use in the population screened were 1% rather than 12%, the program would lose money. Similarly, if the cost per urine sample screened were $95 rather than the $49 assumed, then the program would lose money, even if the prevalence of drug positives was as high as 9%. CONCLUSIONS: Because of the sensitivity of this analysis to changes in its underlying assumptions, any company considering preemployment drug screening should carefully weigh the costs and benefits in its own industry.