Osei Isaac, Young Benjamin, Sarwar Golam, Olatunji Yekini A, Hossain Ilias, Lobga Babila G, Wutor Baleng M, Adefila Williams, Mendy Emmanuel, Adeshola Banjo, Isa Yasir Shitu, Olawale Yusuf A, Lamin Keita M, Nyimanta Ebrimah, Baldeh Bubacarr, Nyassi Abdoullah, Drammeh Momodou M, Ousman Barjo, Molfa Minteh, Salaudeen Rasheed, Mackenzie Grant A
Medical Research Council Unit, The Gambia at London School of Hygiene & Tropical Medicine, Fajara, The Gambia.
Faculty of Infectious & Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Trials. 2024 Dec 18;25(1):836. doi: 10.1186/s13063-024-08677-7.
Randomized controlled trials are considered the "gold standard" for evaluating the effectiveness of an intervention. However, large-scale, cluster-randomized trials are complex and costly to implement. The generation of accurate, reliable, and high-quality data is essential to ensure the validity and generalizability of findings. Robust quality assurance and quality control procedures are important to optimize and validate the quality, accuracy, and reliability of trial data. To date, few studies have reported on study procedures to assess and optimize data integrity during the implementation of large cluster-randomized trials. The dearth of literature on these methods of trial implementation may contribute to questions about the quality of data collected in clinical trials. Trial protocols should consider the inclusion of quality assurance indicators and targets for implementation. Publishing quality assurance and control measures implemented in clinical trials should increase public trust in the findings from such studies. In this manuscript, we describe the development and implementation of internal and external quality assurance and control procedures and metrics in the Pneumococcal Vaccine Schedules trial currently ongoing in rural Gambia. This manuscript focuses on procedures and metrics to optimize trial implementation and validate clinical, laboratory, and field data. We used a mixture of procedure repetition, supervisory visits, checklists, data cleaning and verification methods and used the metrics to drive process improvement in all domains.
随机对照试验被视为评估干预措施有效性的“金标准”。然而，大规模的整群随机试验实施起来复杂且成本高昂。生成准确、可靠和高质量的数据对于确保研究结果的有效性和普遍性至关重要。强大的质量保证和质量控制程序对于优化和验证试验数据的质量、准确性和可靠性很重要。迄今为止，很少有研究报告在大规模整群随机试验实施过程中评估和优化数据完整性的研究程序。关于这些试验实施方法的文献匮乏可能会引发对临床试验中收集数据质量的质疑。试验方案应考虑纳入质量保证指标和实施目标。公布临床试验中实施的质量保证和控制措施应能增强公众对这类研究结果的信任。在本手稿中，我们描述了正在冈比亚农村进行的肺炎球菌疫苗接种计划试验中内部和外部质量保证与控制程序及指标的制定和实施情况。本手稿重点关注优化试验实施以及验证临床、实验室和现场数据的程序和指标。我们采用了程序重复、监督访问、清单、数据清理和验证方法的组合，并使用这些指标推动所有领域的流程改进。
