Efficient Source Data Verification Using Statistical Acceptance Sampling: A Simulation Study

Bor, Rutger M. van den; Oosterman, Bas J.; Oostendorp, Martinus B.; Grobbee, Diederick E.; Roes, Kit C. B.

doi:10.1177/2168479015602042

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Our search strategy and keywords resulted in the 5 full-text articles as per MEDLINE [6][7][8][9][10], 2 full-text articles from COCHRANE [4,11] search, and 17 full-text articles from Web of Science [6][7][8][9][12][13][14][15][16][17][18][19][20][21][22][23][24]. The search resulted in a total of 19 publications from MEDLINE, COCHRANE, and WEB OF SCIENCE, after removing duplicates from the total of 24 articles as shown in Figure 1.…”

Section: Resultsmentioning

confidence: 99%

A Systematic Review to Observe the Impact of Risk-Based Monitoring as Compared to Conventional On-Site Monitoring in Randomised Clinical Trials and Quality Management in Large Cohort Studies

2022

TIJAR

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International Council for Harmonisation, Good Clinical Practice R2 (ICH GCP R2) focuses on quality management as per risk-based methodology, and there has been a lot of focus on monitoring strategy, which is a mixed method of on-site and centralised monitoring. This systematic review was planned to search for the articles providing the evidence for the impact of risk-based monitoring methodology and monitoring standards for cohort studies. A literature search was performed on MEDLINE, COCHRANE, and WEB OF SCIENCE were as per the keyword’s searches. All the publications were reviewed for the data that provides evidence risk-based monitoring for randomised clinical trials and its impact to ensure that data integrity, patient safety, and results obtained were reliable. The search resulted in four articles that were qualified that discussed about the comparison between monitoring techniques and the risk-based monitoring methodology in randomised control trials and other interventional trials. Two publications suggested that the SDV% can be <8% and range from 20-50%, respectively, depending on the assessed factors and risks. Although there is research being conducted to generate the evidence for risk-based monitoring and reduced SDV linked to data errors, further empirical quantitative research should happen to show the impact of risk-based methodology for clinical trials. There is a lack of systematic and empirical data for monitoring as part of quality management in cohort studies.

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Section: Resultsmentioning

confidence: 99%

A Systematic Review to Observe the Impact of Risk-Based Monitoring as Compared to Conventional On-Site Monitoring in Randomised Clinical Trials and Quality Management in Large Cohort Studies

2022

TIJAR

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“…It is generally accepted that the use of SPC theory and sampling inspection has greatly improved the process of quality control in manufacturing systems. 19–22 However, these theories statistically set the control boundary of the quality target as an external variable, and they do not provide a detailed explanation from the viewpoint of economics. Researchers such as Hald have emphasized that many factors such as the testing fee, prior distribution of the quality characteristics of the inspected product, economic loss of accepting unsatisfactory products, and effect of rejecting satisfactory products could influence sample inspection.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Taguchi’s on-line quality feedback control system

Zhang

Chen

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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A feedback control system for quality characteristics is one of the most crucial components in Taguchi’s on-line quality management. In this article, three problems in Taguchi’s on-line quality feedback control system are discussed. Furthermore, countermeasures for improving the system are proposed. First, the quality loss of products that are out of control is reestimated by approximating the probability density of their quality characteristic value to a linear distribution. Second, the quality loss of products that are under control is reestimated by approximating the probability density of their quality characteristic value to a normal distribution. Third, the decreased profit resulting from a process shutdown, which is excluded in Taguchi’s on-line quality feedback control system, is considered in calculating the adjustment cost. The management cost and quality loss constitute the total quality cost. In the improved on-line quality feedback control system, the optimal measurement interval and optimal administrative boundary are calculated by minimizing the total quality cost using an iterative method. An example of the adjustment of the administrative boundary and the measurement interval for manufacturing automobile parts is presented to illustrate the effectiveness of the improved on-line system.

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A Statistical Model for Risk-Based Monitoring of Clinical Trials

Hather

2016

Statistical Applications From Clinical Trials and Personalized Medicine to Finance and Business Analytics

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Efficient Source Data Verification Using Statistical Acceptance Sampling: A Simulation Study

Abstract: Our results suggest that major reductions in workload can be achieved, while maintaining acceptable data quality levels. However, the results also indicate that the proposed strategy is conservative and further improvement is possible.

Cited by 3 publications

References 12 publications

A Systematic Review to Observe the Impact of Risk-Based Monitoring as Compared to Conventional On-Site Monitoring in Randomised Clinical Trials and Quality Management in Large Cohort Studies

A Systematic Review to Observe the Impact of Risk-Based Monitoring as Compared to Conventional On-Site Monitoring in Randomised Clinical Trials and Quality Management in Large Cohort Studies

Optimization of Taguchi’s on-line quality feedback control system

A Statistical Model for Risk-Based Monitoring of Clinical Trials

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