Objective:To study the feasibility of control charts in the quality management of hospital statistical data as a reference for improving such management.Methods:Main business indicators of the main campus and some business indicators of the affiliated campus of a tertiary general hospital from January to May 2022 were selected. K-S test and chi-square goodness of fit test were used to test data in its statistical daily report, analyzing whether the data conform to the specific distributions. Then appropriat control chart were used according to the data type and distribution type. Minitab 21.1 software was used to draw the hospital data quality control chart, and data quality was monitored by analyzing the distribution of data points in the control chart.Results:The test found that the number of admissions, ultrasound examinations and emergency department visits in the main campus, and CT examinations in the affiliated campus, conformed to normal distribution, and single value control charts were applied. The number of ambulance trips in the main campus and the affiliated campus conform to Poisson distribution, and the defect number control chart was applied. The number of inpatient deaths in the main campus conform to a geometric distribution, and a rare event control chart was applied. The volume of admissions and ultrasound examinations in the main campus were mostly influenced by other factors, and the single-value selective control chart was used to further determine the cause of abnormal data distribution. The results of the control chart analysis showed that, there were no abnormal points in the data distribution of admissions, color ultrasound volume and in-hospital deaths in the main campus, two abnormal points in the CT examination volume in the affiliated campus. The control charts for the number of emergency department visits in the main campus and the number of ambulance trips in the main and affiliated campuses each had one outlier. It was verified that one anomaly in the volume of CT examinations in the affiliated campus and one anomaly in the number of ambulance trips in the affiliated campus were caused by data errors, while the other data were correct.Conclusions:It is feasible to use control charts to monitor the quality of hospital data, which can be used as a quality management tool to assist the quality management of hospital data.

【Objective】 To analyze a case of hyperhemolytic syndrome(HHS) and explore the laboratory diagnostic method and clinical treatment strategy. 【Methods】 Serological tests such as blood typing, direct antiglobulin test(DAT), anti-screening and antibody identification were performed, The complete blood count(CBC), as well as hemolysis indicators such as lactate dehydrogenase(LDH) and bilirubin were tested, and the changes and progression of hemolysis were monitored.By using genotyping methods to test 32 common rare blood type antigens in clinical practice, the accuracy of antibody identification results was supported. 【Results】 The patient had anti-E antibodies and autoantibodies in her serum. After blood transfusion, LDH and bilirubin increased significantly, but hemoglobin dropped sharply, far lower than before transfusion, presenting with unique manifestations such as hemoglobinuria.The patient made a full recovery after treatment with high-dose intravenous immunoglobulin and corticosteroids. 【Conclusion】 HHS is a rare and potentially fatal diseases, which is mainly manifested by hemolysis and severe anemia, and the hemoglobin level after blood transfusion is often lower than that before blood transfusion. This patient had typical clinical manifestations of post-transfusion hyperhemolytic reaction. After timely and correct treatment, the patient recovered completely and was discharged, accumulating valuable clinical experience for the diagnosis and treatment of such disease.