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Khan JS, Jibb LA, Busse JW, et al. Electronic Versus Traditional Data Collection: A Multicenter Randomized Controlled Perioperative Pain Trial. Pain Res. Manag. 2019;3(2):16-25.
ABSTRACTBackground: Electronic data collection is increasingly available as a means to collect pain-related clinical trial data; however, effectiveness and costs relative to traditional data collection are uncertain.Aims: The aim of this study was to evaluate data quality, protocol adherence, satisfaction, and resource requirements of electronic data collection (i.e., Internet-based electronic submission) compared to traditional data collection methods (i.e., paper-based diaries and telephone interviews) in a perioperative factorial randomized controlled trial.Methods: This study was an open-label two-arm parallel randomized controlled trial. Women (18?75 years) undergoing breast cancer surgery were allocated to either electronic or traditional data collection and completed pain-related questionnaires at baseline, postoperative period, and 3-month follow-up (NCT02240199).Results: We acquired outcome data at all time points from 78 randomized patients, 38 in the electronic group and 40 in the traditional group. The number of data queries (e.g., erroneously entered data) per patient was higher in the electronic data group (4.92 [SD = 4.67] vs. 1.88 [SD = 1.51]; P \textless 0.001). No between-group differences were observed for compliance with medications, data completeness, loss to follow-up, or patient or research assistant satisfaction. More research assistant time per patient was spent collecting data in the traditional group (42.6 min [SD = 12.8] vs. 9.92 min [SD = 7.6]; P \textless 0.001); however, costs per patient were higher in the electronic group (\$176.85 [SD = 2.90] vs. \$16.33 [SD = 4.90]; P \textless 0.001).Conclusion: Electronic data collection is feasible for perioperative pain clinical trials. Additional trials, including different surgical populations, are needed to confirm our findings and optimize use of electronic data capture methods.Last updated on 03/02/2021