 Subjects -> ELECTRONICS (Total: 207 journals)
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- Cleanability of Metal Surface Finishes Found in Medical Devices and the
Environment of Care-
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Authors: Tandy J; Hanhquynh Le K, Michael Deane G, et al.
Pages: 29 - 36
Abstract: AbstractThe surface finish of reusable medical devices often is a consideration during design, with attention paid to utility, aesthetics, and cost. To study the cleanability of metal surfaces of varying roughness and finish, soil made of bovine blood and egg yolk was placed on nickel alloy surface of varying average roughness (Ra) values (nominal values of 2–500 μin) and finishes (lapped, ground, milled, profiled, and shape turned). A commercially available wipe consisting of quaternary ammonium compound and less than 20% alcohol was applied for a total of eight wipe cycles to remove the soil. The wipe was applied in both horizontal and vertical directions. Evaluation methods for cleanliness include visual inspection and adenosine triphosphate (ATP) measurement. Rougher surfaces above nominal Ra of 250 were found to have higher ATP readings when wiped in both horizontal and vertical directions. In addition, different surface finishes have different cleanabilities despite similar nominal Ra. To ensure optimal cleaning, surfaces should be cleaned in multiple directions. In the future, similar studies will be coupled with efficacy studies and surfaces made with other materials will be investigated.
PubDate: Fri, 01 Apr 2022 00:00:00 GMT
DOI: 10.2345/1943-5967-56.2.29
Issue No: Vol. 56, No. 2 (2022)
- Aluminum Leaching from Fluid Warmers: Regulatory Deferral to Clinicians'
Decision-
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Authors: Oydanich M; Naftalovich R, Discepola PJ, et al.
Pages: 37 - 40
Abstract: AbstractFluid-warming systems are crucial in surgical and trauma settings because of their key role in preventing or treating hypothermia and enabling proper resuscitation of blood products that are stored cold. Recently, several manufacturers have issued warnings of the possibility of aluminum leaching from their fluid warmers and cautioned about the potential for aluminum toxicity in patients who underwent fluid resuscitation with these devices. Studies suggest that one of the main factors affecting aluminum leaching in this setting is the coating of the aluminum plate itself. Coating, often with a biocompatible material, appears to reduce aluminum leaching by 100- to 200-fold compared with an uncoated plate. Nonetheless, leaching with the coating is still at a level exceeding U.S. regulations. A few aluminum-free warming systems are available on the market, but these are not carried by all providers and some clinicians may be less familiar with their use. Medical device manufacturers will likely design future warming systems with less potential for aluminum blood contact. In the meantime, the risk of inadequate resuscitation, consequent to the proper fluid warmer no longer being available, is contrasted with the risk of potential toxicity. In the situation described here, the regulators deferred the ultimate decision of which fluid warmer to use in a given situation to the risk-benefit decision of the clinician.
PubDate: Fri, 06 May 2022 00:00:00 GMT
DOI: 10.2345/1943-5967-56.2.37
Issue No: Vol. 56, No. 2 (2022)
- CMMS Database Migration in Clinical Engineering: Penn Medicine's
Experience-
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Authors: Panichelli R; Jr..
Pages: 41 - 45
Abstract: AbstractDatabase migration involves the transferring of data from one system to another system and typically is associated with information systems, database administration, relational databases, analytics, and business intelligence. Database migration requires careful planning and poses many challenges related to data assessment and cleansing, migration, testing, and managing risks throughout the project. This article describes the database migration activities associated with Penn Medicine's initiative to insource the clinical engineering department at Princeton Health into the health system's corporate information services department. Achieving established milestones throughout the project was pivotal to its successful execution. Defining key goals and making business decisions that would positively affect and support the migration also was imperative. Moreover, the experience described here highlights multiple stages of a computerized maintenance management system (CMMS) database migration project, conveys the importance of building internal and external relationships, and addresses additional ways to improve on future migration projects.
PubDate: Fri, 06 May 2022 00:00:00 GMT
DOI: 10.2345/1943-5967-56.2.41
Issue No: Vol. 56, No. 2 (2022)
- Signaling Patient Oxygen Desaturation with Enhanced Pulse Oximetry Tones
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Authors: Sanderson PM; Loeb RG, Liley H, et al.
Pages: 46 - 57
Abstract: AbstractManufacturers 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.
PubDate: Tue, 07 Jun 2022 00:00:00 GMT
DOI: 10.2345/1943-5967-56.2.46
Issue No: Vol. 56, No. 2 (2022)
- Detecting Unusual Intravenous Infusion Alerting Patterns with Machine
Learning Algorithms-
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Authors: Obuseh M; Yu D, DeLaurentis P.
Pages: 58 - 70
Abstract: AbstractObjectiveTo 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.
PubDate: Fri, 24 Jun 2022 00:00:00 GMT
DOI: 10.2345/1943-5967-56.2.58
Issue No: Vol. 56, No. 2 (2022)
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