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Published on: May 3, 2012
Automation in an addiction treatment research clinic: computerised contingency management, ecological momentary
Massoud Vahabzadeh1, Jia-Ling Lin, Mustapha Mezghanni
1Biomedical Informatics Section, Administrative Management Branch, Intramural Research Program, National Institute on Drug Abuse, NIH/DHHS, Baltimore, Maryland 21224, USA. massoudv@nih.gov
Introduction And Aims:
A challenge in treatment research is the necessity of adhering to protocol and regulatory strictures while maintaining flexibility to meet patients' treatment needs and to accommodate variations among protocols. Another challenge is the acquisition of large amounts of data in an occasionally hectic environment, along with the provision of seamless methods for exporting, mining and querying the data.
Design And Methods:
We have automated several major functions of our outpatient treatment research clinic for studies in drug abuse and dependence. Here we describe three such specialised applications: the Automated Contingency Management (ACM) system for the delivery of behavioural interventions, the transactional electronic diary (TED) system for the management of behavioural assessments and the Protocol Workflow System (PWS) for computerised workflow automation and guidance of each participant's daily clinic activities. These modules are integrated into our larger information system to enable data sharing in real time among authorised staff.
Results:
ACM and the TED have each permitted us to conduct research that was not previously possible. In addition, the time to data analysis at the end of each study is substantially shorter. With the implementation of the PWS, we have been able to manage a research clinic with an 80 patient capacity, having an annual average of 18,000 patient visits and 7300 urine collections with a research staff of five. Finally, automated data management has considerably enhanced our ability to monitor and summarise participant safety data for research oversight.
Discussion And Conclusions:
When developed in consultation with end users, automation in treatment research clinics can enable more efficient operations, better communication among staff and expansions in research methods.
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