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Power of Parametric: Methods to Validate Ethylene Oxide Sterilization Parametric Release. 参数的力量:验证环氧乙烷灭菌参数发布的方法。
Q4 Medicine Pub Date : 2023-01-01 Epub Date: 2024-01-03 DOI: 10.2345/0899-8205-57.4.129
Elise Coakley, Liliana De Alba Nunez, Abigail Honetschlager, Daniel Howell, Scott Jelley, Nicole McLees, Rosa I Vale Mercado

When approaching an ethylene oxide (EO) sterilization validation, medical device manufacturers traditionally have two choices. They can use biological indicators (BIs) to monitor each production run or establish a parametric release process in which sterile release is based on the monitoring and control of physical process parameters that ensure process specifications are met. In ISO 11135:2014, parametric release was brought to the forefront as an acceptable release method; however, a perception exists that implementing parametric release is challenging and time consuming. This article will demonstrate that the opposite is true. It presents a streamlined approach in which parametric release is addressed through the various stages of validation: product definition, process definition, performance qualification, routine release, and process control. Considerations for establishing specifications directly from validation versus "run and record" and trending critical process parameters (e.g., relative humidity, temperature, EO concentration) are discussed. In addition, the benefits of parametric release (active monitoring) over BI release (passive monitoring), including improvements to turnaround time, process control, risk mitigation, reduction of resource investment, and elimination of microbiological release testing, are highlighted. With multiple benefits, parametric release should be the gold standard for EO sterilization processes. It is not novel and has been widely accepted by regulatory agencies globally and notified bodies. The article further describes how the data collection and process capability that is central to process control and parametric release is more powerful than the information provided by a BI, which is merely a catastrophic indicator when used in routine processing.

在进行环氧乙烷 (EO) 灭菌验证时,医疗器械制造商通常有两种选择。他们可以使用生物指标 (BI) 来监控每个生产流程,或者建立参数释放流程,其中无菌释放基于对物理流程参数的监控,以确保符合流程规范。在 ISO 11135:2014 中,参数放行作为一种可接受的放行方法被推到了前沿;然而,人们普遍认为实施参数放行具有挑战性且耗时。本文将证明事实恰恰相反。本文将介绍一种简化的方法,通过验证的各个阶段(产品定义、工艺定义、性能鉴定、常规放行和工艺控制)来解决参数放行问题。讨论了直接从验证中确定规格与 "运行和记录 "以及关键工艺参数(如相对湿度、温度、环氧乙烷浓度)趋势的考虑因素。此外,还强调了参数放行(主动监测)相对于 BI 放行(被动监测)的好处,包括缩短周转时间、改进工艺控制、降低风险、减少资源投入和取消微生物放行测试。参数释放法具有多种优点,应成为环氧乙烷灭菌工艺的黄金标准。它并不新颖,已被全球监管机构和申报机构广泛接受。文章进一步介绍了作为过程控制和参数释放核心的数据收集和过程能力如何比生物统计学指标提供的信息更强大,后者在常规处理过程中仅仅是一个灾难性指标。
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引用次数: 0
Pediatric Characteristics Associated With Higher Rates of Monitor Alarms. 与监护仪报警率较高有关的儿科特征。
Q4 Medicine Pub Date : 2023-01-01 Epub Date: 2024-01-03 DOI: 10.2345/0899-8205-57.4.171
Halley Ruppel, Spandana Makeneni, Irit R Rasooly, Daria F Ferro, Christopher P Bonafide

Background: Continuous physiologic monitoring commonly is used in pediatric medical-surgical (med-surg) units and is associated with high alarm burden for clinicians. Characteristics of pediatric patients generating high rates of alarms on med-surg units are not known. Objective: To describe the demographic and clinical characteristics of pediatric med-surg patients associated with high rates of clinical alarms. Methods: We conducted a cross-sectional, single-site, retrospective study using existing clinical and alarm data from a children's hospital. Continuously monitored patients from med-surg units who had available alarm data were included. Negative binomial regression models were used to test the association between patient characteristics and the rate of clinical alarms per continuously monitored hour. Results: Our final sample consisted of 1,569 patients with a total of 38,501 continuously monitored hours generating 265,432 clinical alarms. Peripheral oxygen saturation (SpO2) low alarms accounted for 57.5% of alarms. Patients with medical complexity averaged 11% fewer alarms per hour than those without medical complexity (P < 0.01). Patients older than 5 years had up to 30% fewer alarms per hour than those who were younger than 5 years (P < 0.01). Patients using supplemental oxygen averaged 39% more alarms per hour compared with patients who had no supplemental oxygen use (P < 0.01). Patients at high risk for deterioration averaged 19% more alarms per hour than patients who were not high risk (P = 0.01). Conclusion: SpO2 alarms were the most common type of alarm in this study. The results highlight patient populations in pediatric medical-surgical units that may be high yield for interventions to reduce alarms. Most physiologic monitor alarms in pediatric medical-surgical (med-surg) units are not informative and likely could be safely eliminated to reduce noise and alarm fatigue.1-3 However, identifying and sustaining successful alarm-reduction strategies is a challenge. Research shows that 25% of patients in pediatric med-surg units produce almost three-quarters of all alarms.4 These patients are a potential high-yield target for alarm-reduction strategies; however, we are not aware of studies describing characteristics of pediatric patients generating high rates of alarms. The patient populations seen on pediatric med-surg units are diverse. Children of all ages are cared for on these units, with diagnoses ranging from acute respiratory infections, to management of chronic conditions, and to psychiatric conditions. Not all patients on pediatric med-surg units have physiologic parameters continuously monitored,4 but among those who do, understanding patient characteristics associated with high rates of alarms may help clinicians, healthcare technology managemen

背景:连续生理监测通常用于儿科内外科(med-surg)病房,但对临床医生来说却带来了很高的警报负担。目前尚不清楚在内外科病房产生高报警率的儿科患者的特征。目的描述与高临床报警率相关的儿科内外科患者的人口统计学和临床特征。方法:我们利用一家儿童医院现有的临床和警报数据进行了一项横断面、单点、回顾性研究。研究对象包括有报警数据的持续接受监控的外科病人。我们使用负二项回归模型来检验患者特征与每连续监测小时临床警报率之间的关联。结果:我们的最终样本包括 1,569 名患者,共连续监测了 38,501 个小时,产生了 265,432 次临床警报。外周血氧饱和度(SpO2)低报警占报警总数的 57.5%。病情复杂的患者平均每小时比病情不复杂的患者少发出 11% 的警报(P < 0.01)。年龄大于 5 岁的患者每小时发出的警报比年龄小于 5 岁的患者少 30%(P < 0.01)。与不使用辅助供氧的患者相比,使用辅助供氧的患者平均每小时多发出 39% 的警报(P < 0.01)。病情恶化风险高的患者平均每小时比非高风险患者多发出 19% 的警报(P = 0.01)。结论:在这项研究中,SpO2 警报是最常见的警报类型。研究结果凸显了儿科内外科病房中可能需要采取干预措施以减少警报的高危患者群体。儿科内外科(med-surg)病房中的大多数生理监护仪警报信息量不大,可以安全消除,以减少噪音和警报疲劳。研究表明,儿科内外科病房中 25% 的患者发出的警报几乎占所有警报的四分之三。4 这些患者是减少警报策略的潜在高收益目标;但是,我们并不知道有哪些研究描述了发出高比率警报的儿科患者的特征。儿科内外科的病人群体多种多样。各年龄段的儿童都在这些科室接受治疗,其诊断包括急性呼吸道感染、慢性病管理和精神疾病。并非所有儿科手术室的患者都接受连续的生理参数监测4 ,但在接受监测的患者中,了解与高报警率相关的患者特征可能有助于临床医生、医疗保健技术管理(HTM)专业人员和其他从事报警管理策略研究的人员制定有针对性的干预措施。我们开展了一项探索性回顾研究,以描述与儿科内外科高报警率相关的患者特征。
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引用次数: 0
ISO 4135, Fourth Edition: Two Decades of Progress in ISO/TC 121. ISO 4135,第四版:ISO/TC 121的二十年进展。
Q4 Medicine Pub Date : 2022-01-01 DOI: 10.2345/1943-5967-56.1.29
Debra R Milamed

The publication of ISO 4135, Anaesthetic and respiratory equipment-Vocabulary, fourth edition, highlights expansion of the scope of the International Organization for Standardization (ISO) Technical Committee (TC) 121 and its Subcommittees and Working Groups during two decades of work. This document stands alongside ISO 19223:2019, Lung ventilators and related equipment-Vocabulary and semantics, to promote consistency and specificity of terminology across ISO/TC 121 standards.

ISO 4135《麻醉和呼吸设备-词汇》第四版的出版,突出了国际标准化组织(ISO)技术委员会(TC) 121及其小组委员会和工作组在二十年的工作中扩大了范围。本文件与ISO 19223:2019《肺呼吸机及相关设备-词汇和语义》保持一致,以促进ISO/TC 121标准中术语的一致性和特异性。
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引用次数: 0
Signaling Patient Oxygen Desaturation with Enhanced Pulse Oximetry Tones. 用增强型脉搏血氧计音调向患者发出血氧饱和度信号。
Q4 Medicine Pub Date : 2022-01-01 DOI: 10.2345/1943-5967-56.2.46
P. Sanderson, R. Loeb, H. Liley, David Liu, E. Paterson, Kelly Hinckfuss, J. Zestic
Manufacturers could improve the pulse tones emitted by pulse oximeters to support more accurate identification of a patient's peripheral oxygen saturation (SpO2) range. In this article, we outline the strengths and limitations of the variable-pitch tone that represents SpO2 of each detected pulse, and we argue that enhancements to the tone to demarcate clinically relevant ranges are feasible and desirable. The variable-pitch tone is an appreciated and trusted feature of the pulse oximeter's user interface. However, studies show that it supports relative judgments of SpO2 trends over time and is less effective at supporting absolute judgments about the SpO2 number or conveying when SpO2 moves into clinically important ranges. We outline recent studies that tested whether acoustic enhancements to the current tone could convey clinically important ranges more directly, without necessarily using auditory alarms. The studies cover the use of enhanced variable-pitch pulse oximeter tones for neonatal and adult use. Compared with current tones, the characteristics of the enhanced tones represent improvements that are both clinically relevant and statistically significant. We outline the benefits of enhanced tones, as well as discuss constraints of which developers of enhanced tones should be aware if enhancements are to be successful.
制造商可以改进脉搏血氧计发出的脉搏音,以支持更准确地识别患者的外周血氧饱和度(SpO2)范围。在这篇文章中,我们概述了代表每个检测到的脉冲的SpO2的可变音调的强度和局限性,我们认为增强音调以划分临床相关范围是可行和可取的。可变音调是脉搏血氧计用户界面的一个值得赞赏和信赖的特征。然而,研究表明,它支持对SpO2随时间变化趋势的相对判断,而在支持SpO2值的绝对判断或SpO2进入临床重要范围时的输送方面效果较差。我们概述了最近的研究,这些研究测试了当前音调的声学增强是否可以更直接地传达临床上重要的范围,而不必使用听觉警报。这些研究涵盖了增强型可变螺距脉搏血氧计音调在新生儿和成人中的使用。与当前音调相比,增强音调的特征表示具有临床相关性和统计学意义的改善。我们概述了增强音调的好处,并讨论了如果增强要成功,增强音调的开发人员应该意识到的限制。
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引用次数: 4
Detecting Unusual Intravenous Infusion Alerting Patterns with Machine Learning Algorithms. 用机器学习算法检测异常静脉输液警报模式。
Q4 Medicine Pub Date : 2022-01-01 DOI: 10.2345/1943-5967-56.2.58
Marian Obuseh, Denny Yu, P. DeLaurentis
OBJECTIVETo detect unusual infusion alerting patterns using machine learning (ML) algorithms as a first step to advance safer inpatient intravenous administration of high-alert medications.MATERIALS AND METHODSWe used one year of detailed propofol infusion data from a hospital. Interpretable and clinically relevant variables were feature engineered, and data points were aggregated per calendar day. A univariate (maximum times-limit) moving range (mr) control chart was used to simulate clinicians' common approach to identifying unusual infusion alerting patterns. Three different unsupervised multivariate ML-based anomaly detection algorithms (Local Outlier Factor, Isolation Forest, and k-Nearest Neighbors) were used for the same purpose. Results from the control chart and ML algorithms were compared.RESULTSThe propofol data had 3,300 infusion alerts, 92% of which were generated during the day shift and seven of which had a times-limit greater than 10. The mr-chart identified 15 alert pattern anomalies. Different thresholds were set to include the top 15 anomalies from each ML algorithm. A total of 31 unique ML anomalies were grouped and ranked by agreeability. All algorithms agreed on 10% of the anomalies, and at least two algorithms agreed on 36%. Each algorithm detected one specific anomaly that the mr-chart did not detect. The anomaly represented a day with 71 propofol alerts (half of which were overridden) generated at an average rate of 1.06 per infusion, whereas the moving alert rate for the week was 0.35 per infusion.DISCUSSIONThese findings show that ML-based algorithms are more robust than control charts in detecting unusual alerting patterns. However, we recommend using a combination of algorithms, as multiple algorithms serve a benchmarking function and allow researchers to focus on data points with the highest algorithm agreeability.CONCLUSIONUnsupervised ML algorithms can assist clinicians in identifying unusual alert patterns as a first step toward achieving safer infusion practices.
目的利用机器学习(ML)算法检测异常输液报警模式,以提高住院患者静脉给药的安全性。材料与方法我们使用了一家医院一年的异丙酚输注的详细数据。对可解释的和临床相关的变量进行特征设计,并按日历日汇总数据点。单变量(最大时限)移动范围(mr)控制图用于模拟临床医生识别异常输液报警模式的常用方法。三种不同的无监督多变量基于ml的异常检测算法(局部离群因子、隔离森林和k近邻)被用于相同的目的。比较了控制图和ML算法的结果。结果异丙酚数据有3300个输液报警,92%发生在白班,其中7个时限大于10。mr图确定了15个异常的警报模式。设置不同的阈值,以包括每个ML算法的前15个异常。共有31个独特的ML异常被分组并按亲和性排名。所有算法在10%的异常情况下达成一致,至少有两种算法在36%的异常情况下达成一致。每个算法都检测到一个特定的异常,而磁共振图没有检测到。异常代表一天71次异丙酚警报(其中一半被覆盖),平均每次输注1.06次,而一周的移动警报率为0.35次输注。这些发现表明,在检测异常报警模式方面,基于ml的算法比控制图更健壮。然而,我们建议使用算法的组合,因为多个算法服务于基准测试功能,并允许研究人员专注于具有最高算法一致性的数据点。结论:无监督ML算法可以帮助临床医生识别异常警报模式,作为实现更安全输液实践的第一步。
{"title":"Detecting Unusual Intravenous Infusion Alerting Patterns with Machine Learning Algorithms.","authors":"Marian Obuseh, Denny Yu, P. DeLaurentis","doi":"10.2345/1943-5967-56.2.58","DOIUrl":"https://doi.org/10.2345/1943-5967-56.2.58","url":null,"abstract":"OBJECTIVE\u0000To detect unusual infusion alerting patterns using machine learning (ML) algorithms as a first step to advance safer inpatient intravenous administration of high-alert medications.\u0000\u0000\u0000MATERIALS AND METHODS\u0000We used one year of detailed propofol infusion data from a hospital. Interpretable and clinically relevant variables were feature engineered, and data points were aggregated per calendar day. A univariate (maximum times-limit) moving range (mr) control chart was used to simulate clinicians' common approach to identifying unusual infusion alerting patterns. Three different unsupervised multivariate ML-based anomaly detection algorithms (Local Outlier Factor, Isolation Forest, and k-Nearest Neighbors) were used for the same purpose. Results from the control chart and ML algorithms were compared.\u0000\u0000\u0000RESULTS\u0000The propofol data had 3,300 infusion alerts, 92% of which were generated during the day shift and seven of which had a times-limit greater than 10. The mr-chart identified 15 alert pattern anomalies. Different thresholds were set to include the top 15 anomalies from each ML algorithm. A total of 31 unique ML anomalies were grouped and ranked by agreeability. All algorithms agreed on 10% of the anomalies, and at least two algorithms agreed on 36%. Each algorithm detected one specific anomaly that the mr-chart did not detect. The anomaly represented a day with 71 propofol alerts (half of which were overridden) generated at an average rate of 1.06 per infusion, whereas the moving alert rate for the week was 0.35 per infusion.\u0000\u0000\u0000DISCUSSION\u0000These findings show that ML-based algorithms are more robust than control charts in detecting unusual alerting patterns. However, we recommend using a combination of algorithms, as multiple algorithms serve a benchmarking function and allow researchers to focus on data points with the highest algorithm agreeability.\u0000\u0000\u0000CONCLUSION\u0000Unsupervised ML algorithms can assist clinicians in identifying unusual alert patterns as a first step toward achieving safer infusion practices.","PeriodicalId":35656,"journal":{"name":"Biomedical Instrumentation and Technology","volume":"56 2 1","pages":"58-70"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41341990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Assessing Detergent Residuals for Reusable Device Cleaning Validations. 评估可重复使用设备清洁验证的洗涤剂残留量。
Q4 Medicine Pub Date : 2021-11-01 DOI: 10.2345/0890-8205-55.4.165
T. Kremer, D. Olsen, Chad Summers, Alpa Patel, Julie Hoover, M. Cieślak, D. Znamensky, G. Mcdonnell
Cleaning chemistries are detergent-based formulations that are used during the processing of reusable medical devices. Manufacturers are responsible for demonstrating the safety of cleaning formulations when they are used during a device processing cycle, including the risk of device-associated cytotoxicity over the concentration ranges for recommended use and rinsing during cleaning. However, no regulation currently exists requiring manufacturers to demonstrate such safety. Although manufacturers' safety data sheets (SDSs) provide information on the safe use of chemicals for users, this information may not provide sufficient detail to determine the risks of residual chemicals on device surfaces. SDSs are not required to contain a comprehensive list of chemicals used, only those of risk to the user. They should be supplemented with information on the correct concentrations that should be used for cleaning, as well as instructions on the rinsing required to reduce the levels of chemicals to safe (nontoxic) levels prior to further processing. Supporting data, such as toxicity profiles or cytotoxicity data that support the instructions for use, would provide medical device manufacturers and healthcare personnel with the necessary information to make informed decisions about selection and correct use of detergents. In the current work, cytotoxicity profiles for eight commonly used cleaning formulations available internationally were studied. Although all of these products are indicated for use in the cleaning of reusable medical devices, results vary across the serial dilution curves and are not consistent among detergent types. The information presented here can be leveraged by both medical device manufacturers and processing department personnel to properly assess residual detergent risks during processing. This work also serves as a call to cleaning formulation manufacturers to provide this information for all chemistries.
清洁化学品是在可重复使用的医疗器械加工过程中使用的基于洗涤剂的配方。制造商有责任证明在器械加工周期中使用的清洁制剂的安全性,包括在推荐使用的浓度范围内以及在清洁过程中冲洗时与器械相关的细胞毒性的风险。然而,目前没有任何法规要求制造商证明此类安全性。尽管制造商的安全数据表(SDS)为用户提供了有关化学品安全使用的信息,但这些信息可能无法提供足够的细节来确定设备表面残留化学品的风险。SDS不需要包含所用化学品的全面清单,只需要包含对用户有风险的化学品。应补充有关清洁所用正确浓度的信息,以及在进一步处理前将化学品水平降至安全(无毒)水平所需的冲洗说明。支持数据,如支持使用说明的毒性特征或细胞毒性数据,将为医疗器械制造商和医护人员提供必要的信息,以便就洗涤剂的选择和正确使用做出明智的决定。在目前的工作中,研究了国际上常用的八种清洁配方的细胞毒性特征。尽管所有这些产品都被指示用于可重复使用的医疗器械的清洁,但在系列稀释曲线上的结果各不相同,并且在不同的洗涤剂类型之间并不一致。医疗器械制造商和加工部门人员都可以利用此处提供的信息来正确评估加工过程中残留洗涤剂的风险。这项工作也呼吁清洁配方制造商为所有化学品提供这些信息。
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引用次数: 3
Usability Engineering Recommendations for Next-Gen Integrated Interoperable Medical Devices. 下一代集成互操作医疗设备的可用性工程建议。
Q4 Medicine Pub Date : 2021-11-01 DOI: 10.2345/0890-8205-55.4.132
P. Masci, S. Weininger
This article reports on the development of usability engineering recommendations for next-generation integrated interoperable medical devices. A model-based hazard analysis method is used to reason about possible design anomalies in interoperability functions that could lead to use errors. Design recommendations are identified that can mitigate design problems. An example application of the method is presented based on an integrated medical system prototype for postoperative care. The AAMI/UL technical committee used the results of the described analysis to inform the creation of the Interoperability Usability Concepts, Annex J, which is included in the first edition of the new ANSI/AAMI/UL 2800-1:2019 standard on medical device interoperability. The presented work is valuable to experts developing future revisions of the interoperability standard, as it documents key aspects of the analysis method used to create part of the standard. The contribution is also valuable to manufacturers, as it demonstrates how to perform a model-based analysis of use-related aspects of a medical system at the early stages of development, when a concrete implementation of the system is not yet available.
本文报告了下一代集成互操作医疗设备的可用性工程建议的发展。采用基于模型的危害分析方法对互操作性功能中可能导致使用错误的设计异常进行推理。确定了可以减轻设计问题的设计建议。基于一个综合医疗系统的术后护理原型,给出了该方法的应用实例。AAMI/UL技术委员会使用所描述的分析结果为互操作性可用性概念(附录J)的创建提供了信息,该概念包含在新的医疗器械互操作性标准ANSI/AAMI/UL 2800-1:2019的第一版中。所介绍的工作对于开发互操作性标准未来修订版的专家很有价值,因为它记录了用于创建部分标准的分析方法的关键方面。该贡献对制造商也很有价值,因为它演示了如何在开发的早期阶段,当系统的具体实现尚未可用时,对医疗系统的使用相关方面进行基于模型的分析。
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引用次数: 0
Assessing Detergent Residuals for Reusable Device Cleaning Validations. 评估可重复使用设备清洁验证的洗涤剂残留量。
Q4 Medicine Pub Date : 2021-11-01 DOI: 10.2345/0899-8205-55.4.165
Terra A Kremer, Daniel Olsen, Chad Summers, Alpa Patel, Julie Hoover, Marcin Cieslak, Dmitry Znamensky, Gerald McDonnell

Cleaning chemistries are detergent-based formulations that are used during the processing of reusable medical devices. Manufacturers are responsible for demonstrating the safety of cleaning formulations when they are used during a device processing cycle, including the risk of device-associated cytotoxicity over the concentration ranges for recommended use and rinsing during cleaning. However, no regulation currently exists requiring manufacturers to demonstrate such safety. Although manufacturers' safety data sheets (SDSs) provide information on the safe use of chemicals for users, this information may not provide sufficient detail to determine the risks of residual chemicals on device surfaces. SDSs are not required to contain a comprehensive list of chemicals used, only those of risk to the user. They should be supplemented with information on the correct concentrations that should be used for cleaning, as well as instructions on the rinsing required to reduce the levels of chemicals to safe (nontoxic) levels prior to further processing. Supporting data, such as toxicity profiles or cytotoxicity data that support the instructions for use, would provide medical device manufacturers and healthcare personnel with the necessary information to make informed decisions about selection and correct use of detergents. In the current work, cytotoxicity profiles for eight commonly used cleaning formulations available internationally were studied. Although all of these products are indicated for use in the cleaning of reusable medical devices, results vary across the serial dilution curves and are not consistent among detergent types. The information presented here can be leveraged by both medical device manufacturers and processing department personnel to properly assess residual detergent risks during processing. This work also serves as a call to cleaning formulation manufacturers to provide this information for all chemistries.

清洁化学品是在可重复使用的医疗器械加工过程中使用的基于洗涤剂的配方。制造商有责任证明在器械加工周期中使用的清洁配方的安全性,包括在推荐使用的浓度范围内与器械相关的细胞毒性风险和清洗期间的冲洗。然而,目前没有任何法规要求制造商证明这种安全性。尽管制造商的安全数据表(sds)为用户提供了关于化学品安全使用的信息,但这些信息可能无法提供足够的细节来确定设备表面残留化学品的风险。sds不需要包含所使用化学品的全面清单,只需要包含对用户有风险的化学品。应补充说明用于清洁的正确浓度,以及在进一步处理之前将化学品水平降低到安全(无毒)水平所需的冲洗说明。支持性数据,如支持使用说明的毒性概况或细胞毒性数据,将为医疗设备制造商和保健人员提供必要的信息,以便在选择和正确使用洗涤剂方面做出明智的决定。在目前的工作中,研究了国际上常用的八种清洁配方的细胞毒性。虽然所有这些产品都指示用于可重复使用的医疗设备的清洁,但结果在系列稀释曲线上有所不同,并且在洗涤剂类型之间不一致。医疗设备制造商和加工部门人员都可以利用这里提供的信息来正确评估加工过程中残留洗涤剂的风险。这项工作也可以作为清洁配方制造商的呼吁,为所有化学品提供这些信息。
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引用次数: 0
Quality Fade in Medical Device Manufacturing: Thinness of Airway Breathing Circuit Plastic. 医疗器械制造中的质量衰退:气道呼吸回路塑料的厚度。
Q4 Medicine Pub Date : 2021-11-01 DOI: 10.2345/0890-8205-55.4.118
R. Naftalovich, Marko Oydanich, Tolga Berkman, Andrew Iskander
Mechanical respirators typically use a plastic circuit apparatus to pass gases from the ventilator to the patient. Structural integrity of these circuits is crucial for maintaining oxygenation. Anesthesiologists, respiratory therapists, and other critical care professionals rely on the circuit to be free of defects. The American Society for Testing and Materials maintains standards of medical devices and had a standard (titled Standard Specification for Anesthesia Breathing Tubes) that included circuits. This standard, which was last updated in 2008, has since been withdrawn. Lack of a defined standard can invite quality fade-the phenomenon whereby manufacturers deliberately but surreptitiously reduce material quality to widen profit margins. With plastics, this is often in the form of thinner material. A minimum thickness delineated in the breathing circuit standard would help ensure product quality, maintain tolerance to mechanical insults, and avert leaks. Our impression is that over the recent years, the plastic in many of the commercially available breathing circuits has gotten thinner. We experienced a circuit leak in the middle of a laminectomy due to compromised plastic tubing in a location that evaded the safety circuit leak check that is performed prior to surgery. This compromised ventilation and oxygenation in the middle of a surgery in which the patient is positioned prone and hence with a minimally accessible airway; it could have resulted in anoxic brain injury or death. The incident led us to reflect on the degree of thinness of the circuit's plastic.
机械呼吸器通常使用塑料电路装置将气体从呼吸机传递给患者。这些电路的结构完整性对于维持氧合至关重要。麻醉师,呼吸治疗师和其他重症监护专业人员依靠回路无缺陷。美国测试和材料协会维护医疗设备的标准,并有一个标准(题为麻醉呼吸管的标准规范),其中包括电路。该标准上次更新是在2008年,现已被撤销。缺乏明确的标准可能会导致质量下降——制造商故意但偷偷地降低材料质量以扩大利润空间的现象。对于塑料,这通常是以更薄的材料的形式出现的。在呼吸电路标准中描述的最小厚度将有助于确保产品质量,保持对机械损伤的容忍度,并避免泄漏。我们的印象是,近年来,许多商用呼吸回路中的塑料变得越来越薄。我们在椎板切除术中经历了一次回路泄漏,原因是手术前在一个位置的塑料管受损,逃避了安全回路泄漏检查。在手术中,患者俯卧,气道可达性最低,通气和氧合受损;这可能会导致缺氧脑损伤甚至死亡。这一事件引发了我们对电路塑料厚度的思考。
{"title":"Quality Fade in Medical Device Manufacturing: Thinness of Airway Breathing Circuit Plastic.","authors":"R. Naftalovich, Marko Oydanich, Tolga Berkman, Andrew Iskander","doi":"10.2345/0890-8205-55.4.118","DOIUrl":"https://doi.org/10.2345/0890-8205-55.4.118","url":null,"abstract":"Mechanical respirators typically use a plastic circuit apparatus to pass gases from the ventilator to the patient. Structural integrity of these circuits is crucial for maintaining oxygenation. Anesthesiologists, respiratory therapists, and other critical care professionals rely on the circuit to be free of defects. The American Society for Testing and Materials maintains standards of medical devices and had a standard (titled Standard Specification for Anesthesia Breathing Tubes) that included circuits. This standard, which was last updated in 2008, has since been withdrawn. Lack of a defined standard can invite quality fade-the phenomenon whereby manufacturers deliberately but surreptitiously reduce material quality to widen profit margins. With plastics, this is often in the form of thinner material. A minimum thickness delineated in the breathing circuit standard would help ensure product quality, maintain tolerance to mechanical insults, and avert leaks. Our impression is that over the recent years, the plastic in many of the commercially available breathing circuits has gotten thinner. We experienced a circuit leak in the middle of a laminectomy due to compromised plastic tubing in a location that evaded the safety circuit leak check that is performed prior to surgery. This compromised ventilation and oxygenation in the middle of a surgery in which the patient is positioned prone and hence with a minimally accessible airway; it could have resulted in anoxic brain injury or death. The incident led us to reflect on the degree of thinness of the circuit's plastic.","PeriodicalId":35656,"journal":{"name":"Biomedical Instrumentation and Technology","volume":"55 4 1","pages":"118-120"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48115768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Selecting a Passive Network Monitoring Solution for Medical Device Cybersecurity Management. 选择用于医疗设备网络安全管理的被动网络监控解决方案。
Q4 Medicine Pub Date : 2021-11-01 DOI: 10.2345/0890-8205-55.4.121
P. Upendra
The number of cyberattacks and information system breaches in healthcare have grown exponentially, as well as escalated from accidental incidents to targeted and malicious attacks. With medical devices representing a substantial repository of all the assets in a healthcare system, network security and monitoring are critical to ensuring cyber hygiene of these medical devices. Because of the unique challenges of connected medical devices, a passive network monitoring (PNM) solution is preferred for its overall cybersecurity management. This article is intended to provide guidance on selecting PNM solutions while reinforcing the importance of program assessment, project management, and use of leading practices that facilitate the selection and further implementation of PNM solutions for medical devices. The article provides a detailed introduction to connected medical devices and its role in effective care delivery, an overview of network security types and PNM, an overview of the National Institute of Standards and Technology Cybersecurity Framework and its application for program assessment, essentials of project management for PNM solution selection and implementation, key performance indicators for measuring a solution's ability to meet critical cybersecurity needs for medical devices, and lessons learned from the author's professional experience, selective literature review, and leading practices. Rather than describing a complete list of guidelines for selecting PNM solutions, the current work is intended to provide guidance based on the author's experience and leading practices compiled from successful medical device cybersecurity programs.
医疗保健领域的网络攻击和信息系统漏洞数量呈指数级增长,并从意外事件升级为有针对性的恶意攻击。医疗设备是医疗系统中所有资产的重要存储库,网络安全和监控对于确保这些医疗设备的网络卫生至关重要。由于联网医疗设备的独特挑战,被动网络监控(PNM)解决方案是其整体网络安全管理的首选方案。本文旨在为选择PNM解决方案提供指导,同时强调项目评估、项目管理和使用领先实践的重要性,以促进医疗器械PNM解决方法的选择和进一步实施。文章详细介绍了联网医疗设备及其在有效护理中的作用,概述了网络安全类型和PNM,概述了国家标准与技术研究所网络安全框架及其在项目评估中的应用,PNM解决方案选择和实施的项目管理要点,衡量解决方案满足医疗设备关键网络安全需求的能力的关键性能指标,以及从作者的专业经验、选择性文献综述和领先实践中吸取的经验教训。目前的工作不是描述选择PNM解决方案的完整指南列表,而是根据作者的经验和从成功的医疗设备网络安全计划中汇编的领先实践提供指导。
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引用次数: 1
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Biomedical Instrumentation and Technology
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