Author:
Nourani Aynaz,Ayatollahi Haleh,Solaymani-Dodaran Masoud
Abstract
Abstract
Background
Data management system for diabetes clinical trials is used to support clinical data management processes. The purpose of this study was to evaluate the quality and usability of this system from the users’ perspectives.
Methods
This study was conducted in 2020, and the pre-post evaluation method was used to examine the quality and usability of the designed system. Initially, a questionnaire was designed and distributed among the researchers who were involved in the diabetes clinical trials (n = 30) to investigate their expectations. Then, the researchers were asked to use the system and explain their perspectives about it by completing two questionnaires.
Results
There was no statistically significant differences between the users’ perspectives about the information quality, service quality, achievements, and communication before and after using the system. However, in terms of the system quality (P = 0.042) and users’ autonomy (P = 0.026), the users’ expectations were greater than the system performance. The system usability was at a good level based on the users’ opinions.
Conclusion
It seems that the designed system largely met the users’ expectations in most areas. However, the system quality and users’ autonomy need further attentions. In addition, the system should be used in multicenter trials and re-evaluated by a larger group of users.
Funder
Iran University of Medical Sciences
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Health Policy,Computer Science Applications
Reference52 articles.
1. Leroux H, McBride S, Gibson S, editors., editors. On selecting a clinical trial management system for large scale, multi-center, multi-modal clinical research study. In: Proceedings of the Australian national health informatics conference. 2011 Aug 1–4, Brisbane.
2. Lu Z, Su J. Clinical data management: current status, challenges, and future directions from industry perspectives. Open Access J Clin Trials. 2010;2:93–105.
3. Chow SC, Liu JP. Data management of a clinical trial. Design and analysis of clinical trials. Hoboken: Wiley; 2013.
4. Gazali S, Kaur S, Singh I. Artificial intelligence based clinical data management systems: a review. Inf Med Unlocked. 2017;9:219–29.
5. Krishnankutty B, Bellary S, Kumar NBR, Moodahadu LS. Data management in clinical research: an overview. Indian J Pharmacol. 2012;44(2):168–72.
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