Development and Evaluation of a Data Validation System for Healthcare Quality Indicators within China's Tiered Hospital Accreditation Framework
Year: 2025
Type: preprint
Abstract: 【Abstract】Background: Data validation is essential for ensuring the authenticity and reliability of healthcare quality monitoring indicators. China’s 2022 Tertiary Hospital Accreditation Standards require internal validation of quality monitoring data. However, hospitals often face challenges such as ambiguous definitions, fragmented data collection, and insufficient IT support, which hinder effective validation. Methods: This study designed and implemented a comprehensive data validation system in a tertiary hospital. The framework included: (1) an organizational structure centered on the Quality Control Office; (2) a dynamic trigger mechanism based on six scenarios; (3) a standardized five-step validation process (data collection, consistency comparison, root cause analysis, corrective action, re-validation) using stratified sampling; and (4) an information platform for automated sampling, comparison, and root cause tracking. Results: A case study on the Admission Rate of Patients with APACHE II Score ≥15 within 24 hours of ICU admission demonstrated system effectiveness. Initial consistency was 69.26%. Root cause analysis and corrective actions (including role clarification, EHR integration, and training) led to 100% consistency upon re-validation, and the indicator improved from 61.19% to 85.94%. Hospital-wide, data consistency increased from 65% to 89%, external reporting pass rates reached 100%, validation efficiency improved by 40%, and manual effort decreased by 30%. Conclusion: The data validation system significantly enhances data reliability, supports accreditation compliance, and facilitates continuous quality improvement. Success depends on integrating institutional protocols, technology, and staff engagement. Future work should focus on adapting to evolving standards, incorporating AI and big data, and strengthening data quality culture.
Authors: Pang Wenwen, Qin Rong, Luo Ling, Zhang Xue, Gan Ming, Wang Jinian
Institution: Anhui Medical University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Funder: Anhui Medical University
OpenAlex ID: W4414414155
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