Core Viewpoint - The article emphasizes the importance of data quality management in healthcare institutions, highlighting how improper data handling can lead to significant regulatory issues and inefficiencies in the healthcare system [3][15]. Group 1: Case Studies of Data Issues - A doctor was found to have prescribed niacinamide at a total amount over 200 times the national average, leading to an investigation that revealed data quality issues due to the use of "unknown" in place of actual doctor names [5][6]. - An elderly patient was mistakenly recorded as undergoing "painless ovum retrieval" instead of the intended "painless gastrointestinal endoscopy" due to incorrect data entry, prompting the need for improved data validation mechanisms [8][9]. - A doctor was found to have issued multiple prescriptions for semaglutide in a very short time frame, indicating potential fraudulent activity, which led to further investigation and corrective actions against the involved medical personnel [10][11]. Group 2: Data Quality Management Recommendations - The article stresses that healthcare institutions must take responsibility for data quality management, ensuring strict audits and timely corrections to prevent regulatory alerts and unnecessary inspections [15]. - It calls for the establishment of a closed-loop management system for problem detection, alerts, and resolution, leveraging technology for better monitoring and cross-verification of data [15]. - Collaboration between healthcare institutions and regulatory bodies is essential to safeguard public funds and ensure accurate data reporting [15].
有医院为73岁老人开展“无痛取卵”,为86岁老人开展“试管内受精”?国家医保局披露→
第一财经·2025-09-29 08:42