PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Systems engineering"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Systems+engineering%22&sort=Date,+newest+firstAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-29T05:39:33ZA new automatic sugarcane seed cutting machine based on internet of things technology and RGB color sensorLiu YangLoai S. NasratMohamed E. BadawyDaniel Eutyche Mbadjoun WapetManar A. OurapiTamer M. El-MesseryIrina AleksandrovaMohamed Metwally MahmoudMahmoud M. HusseinAbdallah E. Elwakeel10.1371/journal.pone.03012942024-03-28T14:00:00Z2024-03-28T14:00:00Z<p>by Liu Yang, Loai S. Nasrat, Mohamed E. Badawy, Daniel Eutyche Mbadjoun Wapet, Manar A. Ourapi, Tamer M. El-Messery, Irina Aleksandrova, Mohamed Metwally Mahmoud, Mahmoud M. Hussein, Abdallah E. Elwakeel</p>
Egypt is among the world’s largest producers of sugarcane. This crop is of great economic importance in the country, as it serves as a primary source of sugar, a vital strategic material. The pre-cutting planting mode is the most used technique for cultivating sugarcane in Egypt. However, this method is plagued by several issues that adversely affect the quality of the crop. A proposed solution to these problems is the implementation of a sugarcane-seed-cutting device, which incorporates automatic identification technology for optimal efficiency. The aim is to enhance the cutting quality and efficiency of the pre-cutting planting mode of sugarcane. The developed machine consists of a feeding system, a node scanning and detection system, a node cutting system, a sugarcane seed counting and monitoring system, and a control system. The current research aims to study the pulse widths (PW) of three-color channels (R, G, and B) of the RGB color sensors under laboratory conditions. The output PW of red, green, and blue channel values were recorded at three color types for hand-colored nodes [black, red, and blue], three speeds of the feeding system [7.5 m/min, 5 m/min, and 4.3 m/min], three installing heights of the RGB color sensors [2.0 cm, 3.0 cm, and 4.0 cm], and three widths of the colored line [10.0 mm, 7.0 mm, and 3.0 mm]. The laboratory test results s to identify hand-colored sugarcane nodes showed that the recognition rate ranged from 95% to 100% and the average scanning time ranged from 1.0 s to 1.75 s. The capacity of the developed machine ranged up to 1200 seeds per hour. The highest performance of the developed machine was 100% when using hand-colored sugarcane stalks with a 10 mm blue color line and installing the RGB color sensor at 2.0 cm in height, as well as increasing the speed of the feeding system to 7.5 m/min. The use of IoT and RGB color sensors has made it possible to get analytical indicators like those achieved with other automatic systems for cutting sugar cane seeds without requiring the use of computers or expensive, fast industrial cameras for image processing.Predicting Successful Weaning from Mechanical Ventilation by Reduction in Positive End-expiratory Pressure Level Using Machine LearningSeyedmostafa SheikhalishahiMathias KasparSarra ZaghdoudiJulia SanderPhilipp SimonBenjamin P. GeislerDorothea LangeLudwig Christian Hinske10.1371/journal.pdig.00004782024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Seyedmostafa Sheikhalishahi, Mathias Kaspar, Sarra Zaghdoudi, Julia Sander, Philipp Simon, Benjamin P. Geisler, Dorothea Lange, Ludwig Christian Hinske</p>
Weaning patients from mechanical ventilation (MV) is a critical and resource intensive process in the Intensive Care Unit (ICU) that impacts patient outcomes and healthcare expenses. Weaning methods vary widely among providers. Prolonged MV is associated with adverse events and higher healthcare expenses. Predicting weaning readiness is a non-trivial process in which the positive end-expiratory pressure (PEEP), a crucial component of MV, has potential to be indicative but has not yet been used as the target. We aimed to predict successful weaning from mechanical ventilation by targeting changes in the PEEP-level using a supervised machine learning model. This retrospective study included 12,153 mechanically ventilated patients from Medical Information Mart for Intensive Care (MIMIC-IV) and eICU collaborative research database (eICU-CRD). Two machine learning models (Extreme Gradient Boosting and Logistic Regression) were developed using a continuous PEEP reduction as target. The data is splitted into 80% as training set and 20% as test set. The model’s predictive performance was reported using 95% confidence interval (CI), based on evaluation metrics such as area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), F1-Score, Recall, positive predictive value (PPV), and negative predictive value (NPV). The model’s descriptive performance was reported as the variable ranking using SHAP (SHapley Additive exPlanations) algorithm. The best model achieved an AUROC of 0.84 (95% CI 0.83–0.85) and an AUPRC of 0.69 (95% CI 0.67–0.70) in predicting successful weaning based on the PEEP reduction. The model demonstrated a Recall of 0.85 (95% CI 0.84–0.86), F1-score of 0.86 (95% CI 0.85–0.87), PPV of 0.87 (95% CI 0.86–0.88), and NPV of 0.64 (95% CI 0.63–0.66). Most of the variables that SHAP algorithm ranked to be important correspond with clinical intuition, such as duration of MV, oxygen saturation (SaO<sub>2</sub>), PEEP, and Glasgow Coma Score (GCS) components. This study demonstrates the potential application of machine learning in predicting successful weaning from MV based on continuous PEEP reduction. The model’s high PPV and moderate NPV suggest that it could be a useful tool to assist clinicians in making decisions regarding ventilator management.Don’t judge a book or health app by its cover: User ratings and downloads are not linked to qualityMaciej HyzyRaymond BondMaurice MulvennaLu BaiAnna-Lena FreyJorge Martinez CarracedoRobert DalySimon Leigh10.1371/journal.pone.02989772024-03-04T14:00:00Z2024-03-04T14:00:00Z<p>by Maciej Hyzy, Raymond Bond, Maurice Mulvenna, Lu Bai, Anna-Lena Frey, Jorge Martinez Carracedo, Robert Daly, Simon Leigh</p>
Objective <p>To analyse the relationship between health app quality with user ratings and the number of downloads of corresponding health apps.</p> Materials and methods <p>Utilising a dataset of 881 Android-based health apps, assessed via the 300-point objective Organisation for the Review of Care and Health Applications (ORCHA) assessment tool, we explored whether subjective user-level indicators of quality (user ratings and downloads) correlate with objective quality scores in the domains of user experience, data privacy and professional/clinical assurance. For this purpose, we applied spearman correlation and multiple linear regression models.</p> Results <p>For user experience, professional/clinical assurance and data privacy scores, all models had very low adjusted R squared values (< .02). Suggesting that there is no meaningful link between subjective user ratings or the number of health app downloads and objective quality measures. Spearman correlations suggested that prior downloads only had a very weak positive correlation with user experience scores (Spearman = .084, p = .012) and data privacy scores (Spearman = .088, p = .009). There was a very weak negative correlation between downloads and professional/clinical assurance score (Spearman = -.081, p = .016). Additionally, user ratings demonstrated a very weak correlation with no statistically significant correlations observed between user ratings and the scores (all p > 0.05). For ORCHA scores multiple linear regression had adjusted R-squared = -.002.</p> Conclusion <p>This study highlights that widely available proxies which users may perceive to signify the quality of health apps, namely user ratings and downloads, are inaccurate predictors for estimating quality. This indicates the need for wider use of quality assurance methodologies which can accurately determine the quality, safety, and compliance of health apps. Findings suggest more should be done to enable users to recognise high-quality health apps, including digital health literacy training and the provision of nationally endorsed “libraries”.</p>The study on surface morphology and decorative properties of Magnesium-glass-board (MGB)Chaojun SongJinxin WangZhanwen WuFeng ZhangZhaolong ZhuXiaolei GuoPingxiang Cao10.1371/journal.pone.02962882024-01-29T14:00:00Z2024-01-29T14:00:00Z<p>by Chaojun Song, Jinxin Wang, Zhanwen Wu, Feng Zhang, Zhaolong Zhu, Xiaolei Guo, Pingxiang Cao</p>
In order to improve the decorative properties of Magnesium-Glass-Board (MGB), the surface morphology and decoration performance of MGB, are studied in detail by using profilometer, microscope and SEM, and the influence of its characterization, such as surface roughness, surface porosity and wettability, on decorative properties of MGB is analyzed by comparing with medium density fiberboard (MDF) and medium density particleboard (MDP). The results first showed that the surface of MGB has a porous structure, but MDF and MDP are not, resulting in a poor decorative performance of MGB. Second, it is found that the surface wettability of MGB is better than others. Third, the hot-pressing parameters including pressure, temperature and time have different influence on decorative performance of MGB during hot-pressing experiment. Finally, the surface bonding strength is positively correlated with pressure, but not with temperature and time. In general, a higher surface bonding strength led to a better decorative performance of MGB. The furthermore research can concentrate on the modification method of the MGB’s surface according to this paper’s conclusion to improve the lamination performance of melamine paper.PO-YOLOv5: A defect detection model for solenoid connector based on YOLOv5Ming ChenYuqing LiuXing WeiZichen ZhangOleg GaidaiHengshou SuiBin Li10.1371/journal.pone.02970592024-01-26T14:00:00Z2024-01-26T14:00:00Z<p>by Ming Chen, Yuqing Liu, Xing Wei, Zichen Zhang, Oleg Gaidai, Hengshou Sui, Bin Li</p>
Solenoid connectors play important role in electronic stability system design, with the features of small size, low cost, fast response time and high reliability. The main production process challenge for solenoid connectors is the accurate detection of defects, which is closely related to safe driving. Both faultless and defective products have similar color and shape at the defect location, making proper inspection challenging. To address these issues, we proposed a defect detection model called PO-YOLOv5 to achieve accurate defect detection for solenoid connectors. First, an additional prediction head was added to enable the model to acquire more semantic information to detect larger-scale defective features. Second, we introduced dynamic convolution to learn complementary connections between the four dimensions of the convolution kernel by utilizing its multidimensional attention mechanism. Replacing conventional convolution with dynamic convolution enhances the detection accuracy of the model and reduces the inference time. Finally, we validated PO-YOLOv5 versus the state-of-the-art object detection methods on the same solenoid connectors dataset. Experiments revealed that our proposed approach exhibited higher accuracy. The mAP (mean Average Precision) result of PO-YOLOv5 was found to be about 90.1%. Compared with the original YOLOv5, PO-YOLOv5 exhibited improved precision by about 3%.Re-testing as a method of implementing external quality assessment program for COVID-19 real time PCR testing in UgandaErick Jacob OkekFredrick Joshua MasembeJocelyn KiconcoJohn KayiwaEsther AmwineDaniel OboteStephen AleleCharles NahabweJackson WereBernard BagayaStephen BalinandiJulius LutwamaPontiano Kaleebu10.1371/journal.pone.02872722024-01-24T14:00:00Z2024-01-24T14:00:00Z<p>by Erick Jacob Okek, Fredrick Joshua Masembe, Jocelyn Kiconco, John Kayiwa, Esther Amwine, Daniel Obote, Stephen Alele, Charles Nahabwe, Jackson Were, Bernard Bagaya, Stephen Balinandi, Julius Lutwama, Pontiano Kaleebu</p>
Background <p>Significant milestones have been made in the development of COVID19 diagnostics Technologies. Government of the republic of Uganda and the line Ministry of Health mandated Uganda Virus Research Institute to ensure quality of COVID19 diagnostics. Re-testing was one of the methods initiated by the UVRI to implement External Quality assessment of COVID19 molecular diagnostics.</p> Method <p>participating laboratories were required by UVRI to submit their already tested and archived nasopharyngeal samples and corresponding meta data. These were then re-tested at UVRI using the WHO Berlin protocol, the UVRI results were compared to those of the primary testing laboratories in order to ascertain performance agreement for the qualitative & quantitative results obtained. Ms Excel window 12 and GraphPad prism ver 15 was used in the analysis. Bar graphs, pie charts and line graphs were used to compare performance agreement between the reference Laboratory and primary testing Laboratories.</p> Results <p>Eleven (11) Ministry of Health/Uganda Virus Research Institute COVID19 accredited laboratories participated in the re-testing of quality control samples. 5/11 (45%) of the primary testing laboratories had 100% performance agreement with that of the National Reference Laboratory for the final test result. Even where there was concordance in the final test outcome (negative or positive) between UVRI and primary testing laboratories, there were still differences in CT values. The differences in the Cycle Threshold (CT) values were insignificant except for Tenna & Pharma Laboratory and the UVRI(p = 0.0296). The difference in the CT values were not skewed to either the National reference Laboratory(UVRI) or the primary testing laboratory but varied from one laboratory to another. In the remaining 6/11 (55%) laboratories where there were discrepancies in the aggregate test results, only samples initially tested and reported as positive by the primary laboratories were tested and found to be false positives by the UVRI COVID19 National Reference Laboratory.</p> Conclusion <p>False positives were detected from public, private not for profit and private testing laboratories in almost equal proportion. There is need for standardization of molecular testing platforms in Uganda. There is also urgent need to improve on the Laboratory quality management systems of the molecular testing laboratories in order to minimize such discrepancies.</p>Rapid dataset generation methods for stacked construction solid waste based on machine vision and deep learningTianchen JiJiantao LiHuaiying FangRenCheng ZhangJianhong YangLulu Fan10.1371/journal.pone.02966662024-01-16T14:00:00Z2024-01-16T14:00:00Z<p>by Tianchen Ji, Jiantao Li, Huaiying Fang, RenCheng Zhang, Jianhong Yang, Lulu Fan</p>
The development of urbanization has brought convenience to people, but it has also brought a lot of harmful construction solid waste. The machine vision detection algorithm is the crucial technology for finely sorting solid waste, which is faster and more stable than traditional methods. However, accurate identification relies on large datasets, while the datasets from the field working conditions are scarce, and the manual annotation cost of datasets is high. To rapidly and automatically generate datasets for stacked construction waste, an acquisition and detection platform was built to automatically collect different groups of RGB-D images for instances labeling. Then, based on the distribution points generation theory and data augmentation algorithm, a rapid-generation method for synthetic construction solid waste datasets was proposed. Additionally, two automatic annotation methods for real stacked construction solid waste datasets based on semi-supervised self-training and RGB-D fusion edge detection were proposed, and datasets under real-world conditions yield better models training results. Finally, two different working conditions were designed to validate these methods. Under the simple working condition, the generated dataset achieved an F1-score of 95.98, higher than 94.81 for the manually labeled dataset. In the complicated working condition, the F1-score obtained by the rapid generation method reached 97.74. In contrast, the F1-score of the dataset obtained manually labeled was only 85.97, which demonstrates the effectiveness of proposed approaches.Radiographers’ perceptions on the quality of managing general radiographic paediatric examinations through the use of a reflective toolKate CaruanaChris HayreChandra Makanjee10.1371/journal.pone.02956032023-12-07T14:00:00Z2023-12-07T14:00:00Z<p>by Kate Caruana, Chris Hayre, Chandra Makanjee</p>
Introduction <p>Paediatric patients are a vulnerable population that require additional care by healthcare professionals. Quality managing these examinations ensures that effective and quality care is provided to individual patients, whilst encouraging consistency within the medical imaging department. This study explored radiographers’ perspectives on quality management strategies of general radiographic paediatric examinations using a paediatric imaging reflective checklist.</p> Methods <p>A quantitative descriptive research design with qualitative questions was used through a purposive sampling method from both public and private Australian diagnostic imaging qualified radiographers who had experience in paediatric imaging examinations. The paediatric imaging service reflective tool consisted of 65 items in total. Data analysis entailed Microsoft Excel version 16.16.6 and Jamovi version 2.3.21 for the closed-ended questions and for the open-ended responses a thematic analysis.</p> Results <p>The participation rate was 13.2% and the most significant findings were: lead shielding was still being used at their organisation, despite recent recommendations to suspend its use; access to paediatric patient related information resources is limited; there was no involvement of families and communities regarding policy development or quality improvement measures as advocated in literature; and there was a need for enhanced specialised paediatric education, training and protocols.</p> Conclusion <p>Using the paediatric patient-centred imaging reflective checklist, radiographers had an opportunity to identify quality improvement indicators as well as issues that could further enhance best practice principles. Further studies could inform on the validity of this reflective tool.</p>An open-source system for efficient clinical trial support: The COMET study experienceJonathan CluttonRobert Neal MontgomeryDinesh Pal MudaranthakamErin M. BlockerAshley R. ShawAmanda N. Szabo ReedEric D. Vidoni10.1371/journal.pone.02938742023-11-27T14:00:00Z2023-11-27T14:00:00Z<p>by Jonathan Clutton, Robert Neal Montgomery, Dinesh Pal Mudaranthakam, Erin M. Blocker, Ashley R. Shaw, Amanda N. Szabo Reed, Eric D. Vidoni</p>
Exercise clinical trials are complex, logistically burdensome, and require a well-coordinated multi-disciplinary approach. Challenges include managing, curating, and reporting on many disparate information sources, while remaining responsive to a variety of stakeholders. The Combined Exercise Trial (COMET, NCT04848038) is a one-year comparison of three exercise modalities delivered in the community. Target enrollment is 280 individuals over 4 years. To support rigorous execution of COMET, the study team has developed a suite of scripts and dashboards to assist study stakeholders in each of their various functions. The result is a highly automated study system that preserves rigor, increases communication, and reduces staff burden. This manuscript describes system considerations and the COMET approach to data management and use, with a goal of encouraging further development and adaptation by other study teams in various fields.Assessing the readiness of health facilities to provide family planning services in low-resource settings: Insights from nationally representative service provision assessment surveys in 10 CountriesMosiur RahmanMd. Jahirul IslamIzzeldin Fadl AdamNguyen Huu Chau DucProsannajid SarkarMd. Nuruzzaman HaqueMd. Golam Mostofa10.1371/journal.pone.02900942023-11-16T14:00:00Z2023-11-16T14:00:00Z<p>by Mosiur Rahman, Md. Jahirul Islam, Izzeldin Fadl Adam, Nguyen Huu Chau Duc, Prosannajid Sarkar, Md. Nuruzzaman Haque, Md. Golam Mostofa</p>
Background <p>Many low-income countries continue to have high fertility levels and unmet need for family planning (FP) despite progress in increasing access to modern contraceptive methods and in reducing the total fertility rate (TFR). Health facilities in sub-Saharan Africa (SSA) and South Asia (SA) are thought to be unable to adequately deal with the burden of high unmet FP demands due to their weaker health systems. As a result, determining the readiness of health facilities that offer FP services is critical for identifying weaknesses and opportunities for continued development of FP health systems in those regions. Service Provision Assessment (SPA) tools—which break down health systems into measurable, trackable components—are one useful way to assess service readiness and the ability of health institutions to deliver FP services.</p> Methods <p>Using data from nationally representative SPA surveys, we conducted a study that aimed to: (1) evaluate healthcare facilities’ readiness to provide FP services; and (2) identify the factors that affect FP service readiness. Using a cross-sectional survey design, we used data from SPA surveys conducted in 10 low-resource SA and SSA countries: Afghanistan, Bangladesh, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Tanzania, and the Democratic Republic of the Congo (DRC). We analyzed data from public and private health facilities in Afghanistan (84), Bangladesh (1,303), Kenya (567), Malawi (810), Namibia (357), Nepal (899), Rwanda (382), Senegal (334), Tanzania (933), and the DRC (1,061) for a total of 6,730 facilities. We used 17 items/indicators recommended by the Service Availability and Readiness Assessment to measure a health facility’s readiness to provide FP services across four domains.</p> Results <p>Only 3.6% to 34.1% of the health facilities were reporting at least 75% (12–13 of 17) of the relevant items for FP service provision. Most of the health facilities in the countries under investigation suffered from lack of readiness, meaning that they did not fulfill at least 75% of the standards (12–13 items of 17 items on the availability of trained staff and guidelines, equipment, and commodities components). The factors associated with higher readiness scores varied among the 10 countries analyzed. Regression models showed that increases in the number of FP healthcare providers available at a health facility and infection control measures for FP exams were factors linked to increased readiness scores in all 10 countries. The low readiness of health facilities to provide FP services in the countries studied showed that the health systems in these low-resource settings faced significant problems with providing FP services. Differences in country-specific variability in the characteristics linked with better preparedness ratings could be attributed to data collected across different years in different nations or to country-specific healthcare financing policies.</p> Conclusions <p>To increase a health facility’s readiness to offer FP services, country-specific factors must be addressed, in addition to common factors found in all 10 countries. Further research is required to determine the causes of country-level differences in FP tracer item availability to develop targeted and effective country-specific strategies to improve the quality of FP services in the SA and SSA regions and address unmet need for FP.</p>Implementing circularity measurements in industry 4.0-based manufacturing metrology using MQTT protocol and Open CV: A case studyYazid SaifYusri YusofAnika Zafiah M. RusAtef M. GhalebSobhi MejjaouliSami Al-AlimiDjamal Hissein DidaneKamran LatifAini Zuhra Abdul KadirHamood AlshalabiSafwan Sadeq10.1371/journal.pone.02928142023-10-13T14:00:00Z2023-10-13T14:00:00Z<p>by Yazid Saif, Yusri Yusof, Anika Zafiah M. Rus, Atef M. Ghaleb, Sobhi Mejjaouli, Sami Al-Alimi, Djamal Hissein Didane, Kamran Latif, Aini Zuhra Abdul Kadir, Hamood Alshalabi, Safwan Sadeq</p>
In the context of Industry 4.0, manufacturing metrology is crucial for inspecting and measuring machines. The Internet of Things (IoT) technology enables seamless communication between advanced industrial devices through local and cloud computing servers. This study investigates the use of the MQTT protocol to enhance the performance of circularity measurement data transmission between cloud servers and round-hole data sources through Open CV. Accurate inspection of circular characteristics, particularly roundness errors, is vital for lubricant distribution, assemblies, and rotational force innovation. Circularity measurement techniques employ algorithms like the minimal zone circle tolerance algorithm. Vision inspection systems, utilizing image processing techniques, can promptly and accurately detect quality concerns by analyzing the model’s surface through circular dimension analysis. This involves sending the model’s image to a computer, which employs techniques such as Hough Transform, Edge Detection, and Contour Analysis to identify circular features and extract relevant parameters. This method is utilized in the camera industry and component assembly. To assess the performance, a comparative experiment was conducted between the non-contact-based 3SMVI system and the contact-based CMM system widely used in various industries for roundness evaluation. The CMM technique is known for its high precision but is time-consuming. Experimental results indicated a variation of 5 to 9.6 micrometers between the two methods. It is suggested that using a high-resolution camera and appropriate lighting conditions can further enhance result precision.How do US corporations communicate interculturally with their Chinese stakeholders: Analysis of GM Company’s social media posts from the cultural value perspectiveJin XuRuijun Duan10.1371/journal.pone.02925522023-10-05T14:00:00Z2023-10-05T14:00:00Z<p>by Jin Xu, Ruijun Duan</p>
Social Media is an important means of communication with audiences around the world. The purpose of this study was to explore whether GM—a famous US auto company adapts its US Cultural values to suit the prevalent cultural values of its Chinese stakeholders on Chinese social media. Content analysis was used to evaluate the cultural content of GM Company’s posts on Weibo and Twitter. Although influenced by the special features of the car industry, there is still enough evidence that the communication style of the US auto Company makes cultural adaption on Chinese social media, reflecting more Chinese prevalent cultural values.Adenosine triphosphate (ATP) sampling algorithm for monitoring the cleanliness of surgical instrumentsDaniela Oliveira PontesDayane de Melo CostaPriscilla Perez da Silva PereiraGreg S. WhiteleyTrevor GlasbeyAnaclara Ferreira Veiga Tipple10.1371/journal.pone.02849672023-08-15T14:00:00Z2023-08-15T14:00:00Z<p>by Daniela Oliveira Pontes, Dayane de Melo Costa, Priscilla Perez da Silva Pereira, Greg S. Whiteley, Trevor Glasbey, Anaclara Ferreira Veiga Tipple</p>
Background <p>Timely detection of cleaning failure is critical for quality assurance within Sterilising Service Units (SSUs). Rapid Adenosine Triphosphate (ATP) testing provides a real time and quantitative indication of cellular contaminants, when used to measure surface or device cleanliness. The aim of this study was to investigate the use of an ATP algorithm and to whether it could be used as a routine quality assurance step, to monitor surgical instruments cleanliness in SSUs prior to sterilisation.</p> Methods <p>Cleanliness monitoring using rapid ATP testing was undertaken in the SSUs of four hospitals located in the western (Amazonia) region of Brazil. ATP testing was conducted (Clean Trace, 3M) on 163 surgical instruments, following manual cleaning. A sampling algorithm using a duplicate swab approach was applied to indicate surgical instruments as (i) very clean, (ii) clean, (iii) equivocal or (iv) fail, based around a ‘clean’ cut-off of 250 Relative Light Units (RLU) and a ‘very clean’ <100 RLU.</p> Results <p>The four cleanliness categories were significantly differentiated (P≤0.001). The worst performing locations (hospitals A & C) had failure rates of 39.2% and 32.4%, respectively, and were distinctly different from hospitals B & D (P≤0.001). The best performing hospitals (B & D) had failure rates of 7.7% and 2.8%, respectively.</p> Conclusion <p>The ATP testing algorithm provides a simple to use method within SSUs. The measurements are in real time, quantitative and useful for risk-based quality assurance monitoring, and the tool can be used for staff training. The four-tiered approach to the grading of surgical instrument cleanliness provides a nuanced approach for continuous quality improvement within SSU than does a simple pass/fail methodology.</p>An absence of evidence breeds contempt: A qualitative study of health system stakeholder perceptions of the quality of medicines available in SenegalMirza LalaniScott Kaba MatafwaliAminata Dior NdiayeJayne WebsterSian E. ClarkeHarparkash Kaur10.1371/journal.pgph.00020042023-07-12T14:00:00Z2023-07-12T14:00:00Z<p>by Mirza Lalani, Scott Kaba Matafwali, Aminata Dior Ndiaye, Jayne Webster, Sian E. Clarke, Harparkash Kaur</p>
Poor-quality medicines pose a significant challenge for health systems in low- to middle-income countries (LMICs),with recent deaths in multiple countries following ingestion of substandard cough syrups emphasising the need for quality-assurance of medicines in our increasingly interconnected global markets. Research also suggests that the source (country of manufacture) and type of medicine (generic/brand) are perceived to be associated with medicine quality. This study explores perceptions of medicines quality among national stakeholders of a medicines quality assurance system (MQAS) in sub-Saharan Africa. Through semi-structured interviews (n = 29) with managers from organisations responsible for the MQAS, public-sector doctors and nurses, and regulated private-sector pharmacists in three urban centres in Senegal in 2013. A thematic approach to analysis was undertaken with themes organised under three main categories, the source of drugs, the type of medicine, and medicines storage. A key emerging theme was the perception of the inferior quality of generic medicines, especially those produced in Asia and Africa, as they were lower in cost and thus believed to be less effective in alleviating symptoms than their brand versions. Medicines in Senegal’s less regulated (informal) street markets were also thought to be of poor-quality as they were not subjected to national regulatory processes or stored appropriately, resulting in exposure to direct sunlight and high temperatures. In contrast, the interviewees expressed confidence in medicines quality within the regulated sectors (public and private retail pharmacies) attributed to stringent national medicines regulation, secure medicines supply chains and adequate technical capacity to survey and analyse for medicines quality. Also, the views expressed typically described a medicine’s quality in terms of its effectiveness in alleviating the symptoms of ill health (efficacy of a medicine).These perceptions may have implications for developing national medicines policy, the procurement and supply of affordable medicines and consumers’ decision-making when purchasing medicines. Indeed, a proclivity for supplying and purchasing more expensive brand medicines may act as a barrier to accessing essential medicines.Increasing SARS-CoV-2 testing capacity through specimen pooling: An acute care center experienceAna CabreraFatimah Al MutawahMike KadourShannon SchofieldBeverley ConkeyJeffrey FullerMichael PayneSameer ElsayedJohan Delport10.1371/journal.pone.02671372023-06-28T14:00:00Z2023-06-28T14:00:00Z<p>by Ana Cabrera, Fatimah Al Mutawah, Mike Kadour, Shannon Schofield, Beverley Conkey, Jeffrey Fuller, Michael Payne, Sameer Elsayed, Johan Delport</p>
Innovation in laboratory testing algorithms to address seemingly uncontrollable global supply chain shortages in plastics and other consumables during emergencies such as the current COVID-19 pandemic have been urgently needed. We report our experience with specimen pooling on SARS-CoV-2 testing in an acute care hospital microbiology laboratory during a high testing demand period that exceeded available processing capacity. A fully automated four-in-one pooling algorithm was designed and validated. Correlation and agreement were calculated. A custom Microsoft Excel tool was designed for use by the technologists to aid interpretation, verification and result entry. Cost-per-test impact for pooling was measured in reference to the consumable cost and was denoted as the percentage reduction of cost versus the baseline cost-per-test of testing specimens individually. Validation showed a strong correlation between the signals observed when testing specimens individually versus those that were pooled. Average crossing point difference was 1.352 cycles (95% confidence interval of -0.235 and 2.940). Overall agreement observed between individually and pooled tested specimens was 96.8%. Stratified agreement showed an expected decreased performance of pooling for weakly positive specimens dropping below 60% after a crossing point of 35. Post-implementation data showed the consumable cost-savings achieved through this algorithm was 85.5% after 8 months, creating both testing and resource capacity. Pooling is an effective method to be used for SARS-CoV-2 testing during the current pandemic to address resource shortages and provide quick turnaround times for high test volumes without compromising performance.