OBJECTIVE: Providing a risk assessment method for the implementation of radiotherapy to identify possible risks in the implementation of the treatment process, and proposing measures to reduce or prevent these risks. METHODS: A multidisciplinary expert evaluation team was developed and the radiotherapy treatment process flow was drawn. Through the expert team, the failure mode analysis is carried out in each step of the flow chart. The results were summarized and the (risk priority ordinal) score was obtained, and the quantitative evaluation results of the whole process risk were obtained. RESULTS: One hundred and six failure modes were obtained, risk assessment of (20%) high risk failure model are 22 and severity (≥ 8) high risk failure model are 27. The reasons for the failures were man-made errors or hardware and software failures. CONCLUSIONS Failure mode and effect analysis can be used to evaluate the risk assessment of radiotherapy, and it provides a new solution for risk control in radiotherapy field.
Healthcare Failure Mode and Effect Analysis ; Risk Assessment

PURPOSE: The purpose of this research was to provide patients with safe preoperative preparatory procedures by removing any risk factors from the preparatory procedures by using failure mode and effects analysis, which is a prospective risk-managing tool. METHODS: This was a research design in which before and after conditions of a single group were studied, Failure mode and effects analysis were applied for the preparatory procedures done before operations. RESULTS: The preparation omission rate before the operation decreased from 2.70% to 0.04%, and operation cancellation rate decreased from 0.48% to 0.08%. CONCLUSION: Failure mode and effects analysis which remove any risk factors for patients in advance of the operation is effective in preventing any negligent accidents.
Healthcare Failure Mode and Effect Analysis* ; Humans ; Patient Safety ; Prospective Studies ; Research Design ; Risk Factors

BACKGROUND: Blood transfusions are complicated procedures, and are highly sensitive to mistakes that could seriously endanger the life of patients. The failure mode and effect analysis (FMEA) can be used to inspect and improve high risk processes. Here, we aimed to identify the risk factors of a blood transfusion process and to improve its safety by optimizing the process. METHODS: We conducted a weekly meeting from March to April 2014. We investigated the frequency of events for 2013 (before FMEA) and 2015 (after FMEA). The FMEA process was performed in eight steps and the improvement priorities were determined in accordance with the magnitude of calculated fatalities (multiplied by severity, occurrence, and detection scores). RESULTS: The whole process of blood transfusion was analyzed by detailed steps: Decision of blood transfusion, blood transfusion request, pre-transfusion test, blood product discharge, delivery, and administration process. Then, we identified the types of failures and likelihood of occurrence, discovery, and severity. Based on the calculated risk priority number, strategies to improve the highest failure modes were developed. Eleven transfusion-related events occurred before FMEA, and three events occurred after FMEA. CONCLUSION: In this study, we analyzed the failure modes that may occur during a transfusion procedure. The FMEA was a useful tool for analyzing and reducing the risks associated with a blood transfusion procedure. Continuous efforts to improve the failure modes would be helpful to further improve the safety of patients undergoing blood transfusion.
Blood Transfusion ; Healthcare Failure Mode and Effect Analysis* ; Hematologic Tests ; Humans ; Patient Safety ; Risk Factors ; Transfusion Medicine*

OBJECTIVE: To investigate the clinical application and effect evaluation of failure mode and effect analysis (FMEA) in the optimization of vascular recanalization in patients with ST-segment elevation myocardial infarction (STEMI). METHODS: A total of 389 STEMI patients admitted to the emergency department of the Fifth Central Hospital in Tianjin from January 2014 to January 2015 were served as the control group, and 398 STEMI patients admitted to the chest pain center of the Fifth Central Hospital in Tianjin from January 2016 to October 2017 were served as the experimental group. In the control group, routine emergency treatment was used. At the same time, the intervention room was 24-hour prepared for emergency vascular recanalization. The experimental group used FMEA. Through the usage of FMEA, the main factors those caused the delay in revascularization treatment were determined, and the revascularization process was optimized for these influencing factors, thereby shortening the "criminal" blood vessel opening time of patients. The door-to-balloon dilatation time (D-to-B time), troponin testing time, placement time of the catheterization room, initiation of the catheterization room to balloon dilatation time, and preoperative and 1 week postoperative N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, heart function parameters [left ventricular ejection fraction (LVEF), left ventricular short axis shortening rate (FS), left ventricular end-systolic diameter (LVESD), and left ventricular end-diastolic diameter (LVEDD)] within 1 week, 3 months and 6 months after intervention, and the incidence of main cardiovascular adverse events within 1 month after intervention, hospital mortality, the length of hospital stay, and readmission within 1 year in the patients of two groups were recorded. RESULTS: D-to-B time (minutes: 70.6±3.6 vs. 79.4±8.7), troponin testing time (minutes: 17.1±2.3 vs. 65.2±6.5), placement time of the catheterization room (minutes: 28.9±9.8 vs. 52.3±12.2) and activation of the catheterization room to balloon expansion time (minutes: 47.3±9.3 vs. 65.1±7.2) in the experimental group were significantly shorter than those in the control group (all P < 0.01). The NT-proBNP levels at 1 week after intervention in the two groups were lower than the preoperative levels, slightly lower in the experimental group, but the difference was not statistically significant. There was no significant difference in cardiac function at 1 week and 3 months after intervention between the two groups. The LVEF and FS at 6 months after intervention in the experimental group were significantly higher than those in the control group [LVEF: 0.622±0.054 vs. 0.584±0.076, FS: (38.1±4.3)% vs. (35.4±6.2)%, both P < 0.01], and LVESD and LVEDD were decreased significantly [LVESD (mm): 31.2±3.8 vs. 34.7±4.2, LVEDD (mm): 49.2±5.3 vs. 52.4±5.6, all P < 0.01]. The length of hospital stay in the experimental group was significantly shorter than that in the control group (days: 8.3±3.2 vs. 13.2±6.8, P < 0.01), the incidence of major cardiovascular adverse events within 1 month after intervention [13.6% (54/398) vs. 19.8% (77/389)], hospital mortality [1.8% (7/398) vs. 4.9% (19/389)], and readmission rate within 1 year [9.5% (38/398) vs. 14.5% (56/389)] in the experimental group were significantly lower than those in the control group (all P < 0.05). CONCLUSIONS The usage of FMEA to optimize the vascular recanalization procedure can shorten the emergency treatment time of STEMI patients, reduce the occurrence of adverse events, and improve the prognosis.
Chest Pain ; Emergency Service, Hospital ; Healthcare Failure Mode and Effect Analysis ; Humans ; Myocardial Infarction ; Prognosis