筑牢医保数据质量防线

Core Viewpoint - The recent cases of abnormal data in the healthcare system highlight the critical importance of data quality in ensuring the effective operation of medical insurance funds, which are essential for public health [1][5]. Group 1: Data Quality Issues - Numerous bizarre medical practices, such as a 73-year-old woman undergoing "painless egg retrieval" and male patients having hysteroscopy billing records, were identified as results of poor data quality management [1][5]. - The National Healthcare Security Administration (NHSA) has utilized a unified medical insurance information platform to identify and address these abnormal data cases, showcasing the empowering role of data in regulatory oversight [1][5]. Group 2: Implications of Data Errors - Errors in medical insurance data can trigger regulatory alarms and lead to on-site inspections, resulting in increased management costs for both regulatory bodies and medical institutions [5][7]. - The integrity of medical insurance funds, which are considered "lifesaving money" for the public, relies heavily on the quality of data management by designated medical institutions [5][7]. Group 3: Responsibilities and Recommendations - Designated medical institutions are urged to take primary responsibility for data quality, ensuring accurate reporting and ongoing verification to eliminate data risks at the source [7]. - Healthcare departments are encouraged to enhance their technical capabilities, implement intelligent monitoring and cross-verification mechanisms, and increase penalties for violations to ensure the proper functioning of medical insurance funds [7].