e-Clinical Trial Research Using Emerging Information Technology

임상연구(e-clinical trial)에서의 정보기술 활용

Clinical trials are the most expensive and time consuming stages in the process of drug development. It is widely accepted that e-clinical technologies will have the most immediate and noticeable impact on drug development by streamlining clinical trials. Although vast majority of clinical trials are still being conducted with paper-based process, information technology is contributing to improve the clinical trial research process. Internet allows real time data collection and enhanced interactivity between study participants and site personnel. Small handhold devices, such as Personal Digital Assistants (PDAs) and cell phones, are often used to collect subject information easily and directly from subjects. Wireless internet links handhold devices to a central computer at any time and any place. Our experiences of PDA developing clinical trial data collection system and XML based e-Clinical Report Form reveals the effectiveness of technology for clinical trials. Our PDA based clinical trial data collection system can enter the data on the PDA and simultaneously transfer to the database through wireless internet. This system aims to examine the feasibility of PDAs as an innovative method for efficient and effective clinical trial data collection. Sixty four irritable bowel syndrome patients are randomly selected and divided into two groups; the control group (paper based user) and the intervention group (PDA based user). Response rate, response completeness and input error are measured to evaluate the effectiveness of the PDA clinical trial management system. Response rate of the control group (595, 94.4%) is higher than the intervention group (487, 77.3%). In addition, electronic Case Report Form (e-CRF) system was developed using Acrobat Live Cycle Forms. This system intends to provide user friendly electronic data collection system Just like paper case report form. Our efforts show that the information technology is able to improve data quality, decrease data input error, and ultimately improve the effectiveness of clinical trial data management.