Maîtrise des risques liés à la production des fluides de dialyse dans une unité de télédialyse

Objective

The “Centre Hospitalier Francois Dunan” is located on an isolated island and ensures patients care in hemodialysis thanks to telemedicine support. Many research studies have demonstrated the importance of hemodialysis fluids composition to reduce morbidity in patients on chronic hemodialysis. The aim of this study was to identify the risks inherent in the production of dialysis fluids in a particular context, in order to set up an improvement action plan to improve risk control on the production of dialysis fluids.

基于失效模式、影响及危害性分析的呼吸机部件失效危害度变化研究

目的研究呼吸机部件失效模式和影响,分析比较不同时间段呼吸机部件失效发生和危害的变化情况。方法统计陆军军医大学大坪医院2012年和2016年呼吸机机故障数据,选取其中部件原因故障失效数据2012年52台,2016年26台,采用失效模式、影响及危害性分析进行分析,参考刘延武文章方法分为13种模式,以风险优先数(RPN)值定量确定呼吸机部件失效危害度并比较。结果 2012年呼吸机部件故障的发生率为43.6%,2016年呼吸机部件故障的发生率为16.4%。2016年因呼吸机部件故障失效发生数量和发生概率较2012年大幅度下降,RPN值下降的部件有空氧混合器(空气)、空氧混合器(氧气)、呼气流量传感器、湿化器、呼吸回路、电源、面板,下降值分别为-108、-120、-40、-14、-192、-64、-50;RPN值增加的部件为吸(呼)压力传感器、支架、显示器,增加值分别为180、12、48;其他部件为RPN值不变,整体呼吸机部件失效危害度下降。结论通过失效模式、影响及危害性分析RPN值计算可以有效掌握呼吸机各部件可靠性与失效危害度变化,结合应用分析与实际需求及时改进呼吸机预防性维护、使用维护培训和维修管理措施,可以保障呼吸机使用过程中的可靠性,提高使用安全性。     

Analyse du risque infectieux autour du patient dans l’unité d’hémodialyse de l’hôpital Ibn Sina de Rabat par application de la méthode d’analyse des modes de défaillance,de leurs effets et de leur criticité

IntroductionHemodialysis is a technique of extra-renal purification associated with high level of risk. The objective is to assess infectious risk during a hemodialysis session on hygiene around the patient in hospital.MethodsAn a priori risk assessment by Failure Modes, Effects and Criticality Analysis method (FMECA) was carried out from May to August 2018, in order to overview infectious risk during the process of hemodialysis in the Ibn Sina Hospital (Rabat, Morocco).ResultsTwenty eight failure modes were identified during the hemodialysis process around the patient: fourteen criticality level 1, ten level 2, and four level 3. A prevention plan has been drafted. Three of the four level 3 failure modes were reduced to level 1 and one to level 2.DiscussionFMECA have enabled us to identify the potential risks, to reconsider certain procedures and to suggest measure matrix for the coverage of the most critical risks.ConclusionThis analysis makes it possible, through periodic evaluations, to enter a real quality approach, which reinforces the satisfaction of the patients as well as all the actors of the hemodialysis center.     

Cartilage Tissue Engineering by Extrusion Bioprinting: Process Analysis,Risk Evaluation,and Mitigation Strategies

Extrusion bioprinting is considered promising in cartilage tissue engineering since it allows the fabrication of complex, customized, and living constructs potentially suitable for clinical applications. However, clinical translation is often complicated by the variability and unknown/unsolved issues related to this technology. The aim of this study was to perform a risk analysis on a research process, consisting in the bioprinting of a stem cell-laden collagen bioink to fabricate constructs with cartilage-like properties. The method utilized was the Failure Mode and Effect Analysis/Failure Mode and Effect Criticality Analysis (FMEA/FMECA) which foresees a mapping of the process to proactively identify related risks and the mitigation actions. This proactive risk analysis allowed the identification of forty-seven possible failure modes, deriving from seventy-one potential causes. Twenty-four failure modes displayed a high-risk level according to the selected evaluation criteria and threshold (RPN > 100). The results highlighted that the main process risks are a relatively low fidelity of the fabricated structures, unsuitable parameters/material properties, the death of encapsulated cells due to the shear stress generated along the nozzle by mechanical extrusion, and possible biological contamination phenomena. The main mitigation actions involved personnel training and the implementation of dedicated procedures, system calibration, printing conditions check, and, most importantly, a thorough knowledge of selected biomaterial and cell properties that could be built either through the provided data/scientific literature or their preliminary assessment through dedicated experimental optimization phase. To conclude, highlighting issues in the early research phase and putting in place all the required actions to mitigate risks will make easier to develop a standardized process to be quickly translated to clinical use.     

Applying failure mode effects and criticality analysis in radiotherapy: Lessons learned and perspectives of enhancement

Introduction

The radiation oncology process along with its unique therapeutic properties is also potentially dangerous for the patient, and thus it should be delivered under a systematic risk control. To this aim incident reporting and analysis are not sufficient for assuring patient safety and proactive risk assessment should also be implemented. The paper accounts for some methodological solutions, lessons learned and opportunities for improvement, starting from the systematic application of the failure mode effects and criticality analysis (FMECA) technique to the radiotherapy process of an Italian hospital.

Materials and methods

The analysis, performed by a working group made of experts of the radiotherapy unit, was organised into the following steps: (1) complete and detailed analysis of the process (integration definition for function modelling); (2) identification of possible failure modes (FM) of the process, representing sources of adverse events for the patient; (3) qualitative risk assessment of FMs, aimed at identifying priorities of intervention; (4) identification and planning of corrective actions.

Results

Organisational and procedural corrective measures were implemented; a set of safety indexes for the process was integrated within the traditional quality assurance indicators measured by the unit. A strong commitment of all the professionals involved was observed and the study revealed to be a powerful “tool” for dissemination of patient safety culture.

Conclusion

The feasibility of FMECA in fostering radiotherapy safety was proven; nevertheless, some lessons learned as well as weaknesses of current practices in risk management open to future research for the integration of retrospective methods (e.g. incident reporting or root cause analysis) and risk assessment.     

药物Ⅰ期临床试验实施阶段质量风险管理研究

目的：建立药物Ⅰ期临床试验实施阶段质量风险管理的一般方法。方法：以质量风险管理理论为指导，运用失效模式、影响与危害性分析法（FMECA），结合文献研究和调查问卷法，对药物Ⅰ期临床试验实施阶段进行风险评估。结果与结论：药物Ⅰ期临床试验实施阶段共有"研究场地管理""SOP管理""受试者管理""试验用药物管理""生物样本管理""试验记录管理""安全性报告管理""质量保证" 8个环节下87个失效模式和274个失效原因会影响到研究质量。其中"SOP的制定不符合当时当地药品相关法律法规的要求""招募质量低"及"受试者用药剂量、时间、方式及饮水量错误"等14个失效模式属于高风险，应实施风险控制；从"受试者管理""SOP管理""试验数据记录管理""试验用药物管理"及"研究场地管理"五个方面提出了风险控制措施和建议。     

The AMÉLIE project: failure mode,effects and criticality analysis: a model to evaluate the nurse medication administration process on the floor

Objective The objective of this article was to critically evaluate the causes of adverse drug events during the nurse medication administration process in paediatric care units in order to identify and prioritize interventions that need to be implemented. Methodology This is a failure mode, effects and criticality analysis (FMECA) study. A multidisciplinary committee composed of nurses, pharmacists, physicians and risk managers evaluated through consensus the process of administering medications at the Centre hospitalier universitaire de Sainte‐Justine. By mapping the process, all the failure modes were identified and associated with at least one cause each. Using a summary grid, each failure mode was evaluated by rating frequency (from 1 to 9), likelihood of failure detection (from 0 to 100%) and severity (from 1 to 9) using adapted versions of already published scales. Results A 10‐member committee was set up, and it met eight times between January and April 2010. In the two specialized paediatric units selected (n = 38 beds), an average number of approximately 20 000 drug doses was administered monthly from about 400 non‐proprietary names. Through consensus, the committee identified 16 processes and 53 failure modes. While frequency and severity were based on perceptions that could be objectivized with local data and scientific documentation, the likelihood of detection was mainly based on individual perception. Conclusion FMECA is a useful approach to improve the medication process.