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Contingency management has been successfully used to reinforce abstinence in drug-dependent patients. The major challenge associated with this technique, however, is its likely prohibitive cost especially when the reinforcement follows an escalating amount schedule. At our clinic, we have implemented a less costly approach involving prize draws as the reinforcer. Workflow challenges of such an implementation are extensive considering varying conditions concurrently used in various protocols for meeting inclusion criteria, stratifying into various groups, tracking categories of prizes, determining eligibility for bonus draws based on laboratory results, etc. To address these challenges we implemented the automated contingency management (ACM) decision support system for dynamic reward reinforcement in the study of treatment of cocaine and opiates. A discussion of the results of our research as well as possible insight into some of our findings provided by ACM is presented in this paper.

Optimizing screening and evaluation process is essential in maximizing recruiting potential participants into clinical trials. We developed a clinical recruiting system used in the management of human research studies whereby recruiting for various protocols are conducted at multiple sites by different groups with process interdependencies. The system is developed based on a multi-tier architecture with a series of real-time and on-demand decision support systems to increase the efficiency of screening and evaluation of participants during a recruiting process. It simulates various conditions by using derivation rules and recruiting templates for automatic generation of checklists in order to recommend the optimum selection rules based on existing participants' data and is seamlessly integrated into our large human research information system, a comprehensive electronic health record (EHR) system for research participants.