STATISTICAL QUALITY-CONTROL AND SOCIAL PROCESSES - A DRUG-TESTING APPLICATION

Traditional acceptance sampling procedures have been used to monitor t he quality of outgoing items from a production process within a manufa cturing environment. Generally, however, this has represented a reacti ve, rather than a proactive, approach to quality control. Importantly, the manufacturing sector has refocused itself on more proactive techn iques that attempt to improve item quality by repairing the process at the closest feasible point of intervention. This type of intervention is less possible, however, in most social service environments since: (1) the process may not be visible; and (2) the relationship between intervention and outcome is not well-understood and/or well-defined. L argely because of the complexity of social services, statistical quali ty control procedures have not generally been applied to improve proce ss quality or to otherwise affect process outcomes. Because of these d ifficulties, the benefits of statistical quality control procedures an d their ability to make processes more efficient and/or effective have largely been ignored in the literature on quality control. However, p rovided one can identify an objective outcome measure from a process ( regardless of the complexity of that process), and make some assumptio ns about the prior distribution, acceptance sampling can be an appropr iate and useful technique for monitoring process outcomes. Indeed, for many social processes, acceptance sampling, or testing ''after the fa ct'' may be the only approach available for monitoring shifts in proce ss quality. We here demonstrate the utility of Bayesian acceptance sam pling in the context of a timely social process, testing a population for the use of illegal drugs. The use of drugs, and the desire on the part of businesses and the criminal justice system to control or deter use has been a major focal point for policy and decision makers for m ore than a decade. Given that budgets to institute drug testing and/or screening programs are not unlimited, a technique that reduces the co st of a drug treatment program while maintaining deterrence and monito ring effects would indeed be useful to practitioners. We thus propose an application within the framework of an economic model of drug use, and show that adoption of the testing approach can reduce the expected cost of testing. (C) 1997 Elsevier Science Ltd.