Biomedical Instrumentation and Technology最新文献

Parametric release, which relies on use of process data for product release, provides many benefits. However, adoption by the sterilization industry has been slow, with release typically involving biological indicator (BI) growth responses/ dosimetry readings. The current article highlights how the data provided by the process (described through examples for ethylene oxide [EO], vaporized hydrogen peroxide [VHP], and radiation) may be better used to inform parametric release implementation. The examples involving EO and VHP demonstrated the ability of the sterilization equipment to deliver validated parameters repeatedly after the load presented was validated. For instances in which load variability has not been addressed in performance qualification, BI testing or even measurement of EO concentration cannot reliably or fully inform the impact of such variance on the validated process. "Direct" monitoring of EO concentration is a current requirement in ISO 11135:2014. Nonetheless, the findings presented here show that EO and VHP concentrations can be determined by the calculated method, rendering the use of a concentration measurement probe somewhat superfluous. In alignment with European Union good manufacturing practice Annex 17, a key requirement of parametric release is to have sufficient data to demonstrate the repeatability of the validated process. Similar to gas technologies, radiation processing strives to implement parametric release but is limited by the currently available means of measuring all critical parameters, such as photon delivery.

While selecting the test variables for a cleaning validation for reusable medical devices, the manufacturer must provide a simulative and clinically representative challenge for the device. An appropriate challenge must be identified with care so as not to overchallenge the cleaning process by selecting the worst case for every variable, thus leading to an impossible validation or unrealistic processing requirements. To appropriately select the testing variables, an understanding of the challenge to the cleaning process is important. The relationship among device material, test soil, and application method was investigated by testing 140 variable combinations, including seven materials (stainless steel, polyoxymethylene, polyether ether ketone, nitinol, aluminum, titanium, and silicone), four test soils (defibrinated blood soil, coagulated blood, modified coagulated blood, and Miles soil), and five soil application methods (pipetting neat, pipetting spreader, painting, handling with soiled gloves, and immersion). Stainless steel was the only material that showed consistent soil application in a thickness (at ~6 μL/cm²) that fully covered the test surface without some element of pooling, cracking, flaking, or soil migration with all test soils and application methods. The data collected using solubility testing indicated that a complex relationship for material adherence may exist between device materials and test soil. Stainless steel was the most challenging material tested.

The identification of worst-case device (or device set) features has been a well-established validation approach in many areas (e.g., terminal sterilization) for determining process effectiveness and requirements, including for reusable medical devices. A device feature approach for cleaning validations has many advantages, representing a more conservative approach compared with the alternative compendial method of testing the entirety of the device. By focusing on the device feature(s), the most challenging validation variables can be isolated to and studied at the most difficult-to-clean feature(s). The device feature approach can be used to develop a design feature database that can be used to design and validate device cleanliness. It can also be used to commensurately develop a quantitative cleaning classification system that will augment and innovate the effectiveness of the Spaulding classification for microbial risk reduction. The current study investigated this validation approach to verify the efficacy of device cleaning procedures and mitigate patient risk. This feature categorization approach will help to close the existing patient safety gap at the important interface between device manufacturers and healthcare facilities for the effective and reliable processing of reusable medical devices. A total of 56,000 flushes of the device features were conducted, highlighting the rigor associated with the validation. Generating information from design features as a critical control point for cleaning and microbiological quality will inform future digital transformation of the medical device industry and healthcare delivery, including automation.

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.

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

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.