To detect unusual infusion alerting patterns using machine learning (ML) algorithms as a first step to advance safer inpatient intravenous administration of high-alert medications. We 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. The 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. These 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. Unsupervised ML algorithms can assist clinicians in identifying unusual alert patterns as a first step toward achieving safer infusion practices.

Abstract To ensure patient safety, medical device manufacturers are required by the Food and Drug Administration and other regulatory bodies to perform biocompatibility evaluations on their devices per standards, such as the AAMI-approved ISO 10993-1:2018 (ANSI/AAMI/ISO 10993-1:2018).However, some of these biological tests (e.g., systemic toxicity studies) have long lead times and are costly, which may hinder the release of new medical devices. In recent years, an alternative method using a risk-based approach for evaluating the toxicity (or biocompatibility) profile of chemicals and materials used in medical devices has become more mainstream. This approach is used as a complement to or substitute for traditional testing methods (e.g., systemic toxicity endpoints). Regardless of the approach, the one test still used routinely in initial screening is the cytotoxicity test, which is based on an in vitro cell culture system to evaluate potential biocompatibility effects of the final finished form of a medical device. However, it is known that this sensitive test is not always compatible with specific materials and can lead to failing cytotoxicity scores and an incorrect assumption of potential biological or toxicological adverse effects. This article discusses the common culprits of in vitro cytotoxicity failures, as well as describes the regulatory-approved methodology for cytotoxicity testing and the approach of using toxicological risk assessment to address clinical relevance of cytotoxicity failures for medical devices. Further, discrepancies among test results from in vitro tests, use of published half-maximal inhibitory concentration data, and the derivation of their relationship to tolerable exposure limits, reference doses, or no observed adverse effect levels are highlighted to demonstrate that although cytotoxicity tests in general are regarded as a useful sensitive screening assays, specific medical device materials are not compatible with these cellular/in vitro systems. For these cases, the results should be analyzed using more clinically relevant approaches (e.g., through chemical analysis or written risk assessment).

Following a merger of two children's hospitals, leadership discovered a considerable utilization volume of single-use sensors that was associated with declining hospital reimbursements. This discovery resulted in the establishment of a new sensor management strategy, the goal of which was to decrease costs and waste associated with disposable pulse oximetry sensors. The sensor management strategy involved using replacement tapes with single-patient-use pulse oximeter sensors instead of the current practice of reprobing with a new sensor. A 60% utilization goal was set, with the focus shifted from sensors used per patient to replacement tapes per sensor. The implementation of a new sensor management strategy between the years 2006 and 2019 in a hospital system decreased sensor volume by more than 780,000 sensors and realized a cost avoidance of more than 7 million dollars. A sensor management strategy can substantially reduce the cost and medical waste commonly associated with the use of disposable, single-patient pulse oximetry sensors.

Research Article| December 19 2020 SETTING STANDARDS: Revised ISO 5840 Series Clarifies Testing, Evaluation Procedures for Cardiac Valves Russ Joseph; Russ Joseph Search for other works by this author on: This Site PubMed Google Scholar Changfu Wu; Changfu Wu Search for other works by this author on: This Site PubMed Google Scholar Ajit Yoganathan Ajit Yoganathan Search for other works by this author on: This Site PubMed Google Scholar Biomed Instrum Technol (2020) 54 (6): 441–443. https://doi.org/10.2345/0899-8205-54.6.441 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Russ Joseph, Changfu Wu, Ajit Yoganathan; SETTING STANDARDS: Revised ISO 5840 Series Clarifies Testing, Evaluation Procedures for Cardiac Valves. Biomed Instrum Technol 1 November 2020; 54 (6): 441–443. doi: https://doi.org/10.2345/0899-8205-54.6.441 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest Search Revised versions of the ISO 5840 series of standards, which focus on cardiac valve prostheses, were completed in summer 2020. The new family of standards will provide valuable guidance to manufacturers, heart valve device scientists, clinicians, and international regulators. The series will help ensure that device-related risks to patients have been adequately mitigated, quality assurance is properly facilitated, heart valve substitutes are effectively selected, and devices are presented in a convenient form. ISO 5840 was first released as a single document in 1984. Since that release, much has been learned about heart valve substitutes in the four decades that followed, and an entirely new family of heart valve substitutes implanted by transcatheter techniques recently has become available. Regarding in vitro testing and reporting, apart from basic material testing for mechanical, physical, chemical, and biocompatibility characteristics, the... © Copyright AAMI 2020. Single user license only. Copying, networking, and distribution prohibited.2020 You do not currently have access to this content.

Standard methods are needed to reliably and efficiently assess bacterial contamination of processed medical devices. This article demonstrates a standard operating procedure (SOP) for fluorescence microscopy-based detection of residual bacteria on medical devices (BAC-VIS). BAC-VIS uses a 4',6-diamidino-2-phenylindole (DAPI) stain with fluorescent microscopy to quickly and cost-effectively detect bacterial contamination of processed medical device parts. The BAC-VIS protocol was optimized and achieved greater than 80% staining efficiency and a signal-to-noise ratio of more than 20 using four representative organisms. The SOP was first validated for use on a buildup biofilm model, accessory channels of contaminated clinically used devices, and inoculated endoscope end caps and O-rings. The buildup biofilm model was used to evaluate BAC-VIS after repeated treatment of adherent bacteria with three common high-level disinfectants: glutaraldehyde, ortho-phthalaldehyde, and peracetic acid. Next, BAC-VIS was used to assess clinically used endoscope parts that cultured positive for Gram-negative bacteria. DAPI-stained cells were found on all culture-positive devices, especially in grooves and imperfections on the surface. Finally, BAC-VIS was used to detect bacteria on inoculated endoscope device components. The results showed potential for BAC-VIS to be a valuable tool for industry and academic/medical researchers for investigations of contaminated medical devices. Results obtained using BAC-VIS can increase understanding of the role of design in cleanability, wear, and prevention of contamination and may lead to improvements in materials and design that could make processed endoscope use safer for patients. Of note, this protocol is not for detecting bacteria on scopes or scope parts that will be put back into clinical use.

When I first joined AAMI as a staff member 2016, one of our laudable goals was working to improve diversity in the many health technology professions that comprise the AAMI Community.The baby boomer generation, consisting in large part of older, white men from a technical background—longtime AAMI members who we know and love—was beginning to retire in earnest. That alone meant that the culture and demographics of these fields would be changing, as the upcoming generations are demographically more diverse. Ideas about gender roles have also evolved significantly, even just in the past decade.It also goes without saying that the conversation about diversity and inclusion in the workplace has changed a great deal since 2016, and even from the beginning of this very year. Now is the time for us to explore the topic of diversity and inclusion in health technology.That's why, in this issue's special cover story (p. 318), we're exploring our community from the perspective of six professionals of diverse racial and ethnic backgrounds. Our goal is to understand what it's like to be a minority in their fields, to highlight the challenges they've faced pursuing their careers, and their thoughts on everything from device maintenance to mentorships.We want to listen and to understand—what does the health technology community actually look like from their perspective? Are prejudice and discrimination common in the industry? What can all of us do to create more inclusive environments? And what advice would they pass along to others on similar career paths?Some of what you'll read will bring you hope. Other tales are frustrating and tell us there's much left to be done. But I think everyone will learn something.We tried our best to get as many perspectives as possible—from interns to supervisors, healthcare technology management professionals to government regulators, and women and men. But the conversation doesn't end there.I encourage all of you reading this special issue to weigh in and tell us your story, too, by emailing me at gstern@aami.org