Key Takeaways & Executive Findings
- •• Developed a quantitative multi-indicator evaluation model for clinical trial management, integrating risk monitoring, quality management, and effectiveness. • Utilized analytic hierarchy process (AHP) to assign weights to indicators, ensuring objective and reliable assessment. • Validated the model across multiple trial centers, demonstrating its ability to discriminate between high and low management performance. • Provides a practical framework for continuous improvement in clinical trial operations, enhancing patient safety and data integrity.
Abstract
Purpose: This study aims to develop a quantitative evaluation model for assessing the management level of clinical trials, addressing the need for a comprehensive and objective framework. Design/methodology/approach: The model integrates a multi-level indicator system, including first-level indicators (risk monitoring, quality management, and management effectiveness) and second-level indicators (such as risk identification, quality assurance, and outcome assessment). A weighted scoring method is employed, with weights determined via analytic hierarchy process (AHP). The model was validated using data from multiple clinical trial centers. Findings: The evaluation model effectively differentiates between high-performing and low-performing trial management systems. Key factors influencing management level include risk monitoring frequency, quality management plan adherence, and management effectiveness metrics. The model provides actionable insights for continuous improvement. Originality/value: This paper presents a novel, systematic approach to clinical trial management evaluation, offering a practical tool for stakeholders to enhance trial quality and compliance.
1. Introduction
Clinical trials are essential for advancing medical knowledge and improving patient care. However, the complexity and regulatory requirements of trial management pose significant challenges. Effective management is crucial to ensure patient safety, data integrity, and compliance with ethical standards. Traditional evaluation methods often rely on subjective assessments, lacking a systematic and quantitative approach. This study addresses this gap by developing a comprehensive evaluation model that objectively measures the management level of clinical trials.
The proposed model is built upon a multi-level indicator system, encompassing key dimensions such as risk monitoring, quality management, and management effectiveness. By integrating these indicators into a weighted scoring framework, the model provides a holistic view of trial management performance. The use of analytic hierarchy process (AHP) ensures that the weights reflect the relative importance of each indicator, based on expert judgment. This approach enables stakeholders to identify strengths and weaknesses, facilitating targeted improvements.
The remainder of this paper is organized as follows: Section 2 reviews relevant literature on clinical trial management and evaluation models. Section 3 describes the methodology, including the indicator system and AHP-based weighting. Section 4 presents the results of model validation. Section 5 discusses the implications and limitations. Finally, Section 6 concludes with recommendations for practice and future research.
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Zhang Wei, Li Na, Wang Fang, Chen Jie (2026). Quantitative Management Level Evaluation Model for Clinical Trials: A Multi-Indicator Approach. Chinese Journal of New Drugs. https://doi.org/10.1007/s11205-025-03456-7
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Frequently Asked Questions
What is the purpose of the quantitative evaluation model for clinical trial management?
The model aims to provide an objective, systematic framework to assess the management level of clinical trials, helping stakeholders identify strengths and areas for improvement.
How are the weights of indicators determined in the model?
Weights are determined using the analytic hierarchy process (AHP), which relies on expert judgments to establish the relative importance of each indicator.
What are the key indicators used in the evaluation model?
The model includes first-level indicators such as risk monitoring, quality management, and management effectiveness, each with specific second-level indicators like risk identification and quality assurance.
How was the model validated?
The model was validated using data from multiple clinical trial centers, demonstrating its ability to differentiate between high and low management performance.
What are the practical implications of this model?
The model provides a practical tool for continuous improvement in clinical trial operations, enhancing patient safety, data integrity, and regulatory compliance.
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