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Biobanks are valuable service units that ensure the usage of high-quality biological samples. They contribute to translational research, and their support may improve future therapeutic approaches. They store biological samples that can be used to examine circulation biomarkers, immune cells, and immunohistochemistry aspects of illnesses and further in-depth examinations using NGS techniques. The IRCCS Synlab SDN Biobank has about 70,000 well-preserved cryopreserved human samples from various diseases, primarily oncological but also neurological and cardiovascular. These biospecimens were taken from 25,000 participants underwent imaging with a contrast agent. The goal is to propose quality control assays that meet the requirements of the international standard ISO 9001:2015 and ISO 20387:2020 accreditation. PBMCs viability was determined, and immune subset cells were analyzed by flow cytometry. Furthermore, the expression of ubiquitous miRNAs was used to assess plasma sample integrity. The quality controls demonstrated that the biological samples were correctly cryopreserved; the preservation of human biological samples did not affect the quality of the biological samples tested. Indeed, the cryopreserved PBMCs had a vitality of more than 80%, and the lymphocyte subsets could be selected for future immune cell investigations. Furthermore, miRNA expression was highest in thawed plasma samples compared to the positive and negative controls. We evaluated the quality of our randomly selected biobank-thawed human samples. Both PBMCs and plasma samples fulfill the high-quality standards needed for biomedical research, assuring their long-term preservation. However, further research is needed in the biobanking field to establish globally accepted procedures to confirm the quality of biological samples.

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As the reliance on clinical epidemiological information from human specimens grows, so does the need for effective clinical information management systems, particularly for biobanks. Our study focuses on enhancing the Korea Biobank Network's (KBN) system with data quality verification features. By comparing the quality of data collected before and after these enhancements, we observed a notable improvement in data accuracy, with the error rate decreasing from 0.1198% to 0.0492%. This advancement underscores the importance of robust data quality management in supporting high-quality clinical research and sets a precedent for the development of clinical information management systems.

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Cloud products from geostationary satellites are the main alternative to surface synoptic cloud observations (SYNOP), and have become the baseline products for the development and construction of the Quality Management System (QMS) of integrated meteorological observation in China. This study addresses the needs of the China Meteorological Administration (CMA) for such an operational reform, and it is carried out using real-time observations obtained from the Fengyun-2E (FY-2E) geostationary satellite in 2012 to derive cloud total amount and classification using two different methods. Compared to surface SYNOP observations, the cloud total amount estimated by FY-2E is generally significantly lower (about 30% lower on average). The cloud classification resulting from the two methods used in this study is also significantly different from the classification obtained from surface observations (difference between 22 and 32%). The difference is smaller for the classification method, which uses additional auxiliary temperature profiles.

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A quality management system for clinical and public health research operations is indispensable because it ensures the integrity and reliability of research outcomes. By implementing a robust quality management practice in research implementation and operation, research teams can uphold the highest standard of research conduct, thereby enhancing the credibility and trustworthiness of research findings. This paper elucidates the significance and role of a quality management system in clinical and public health research operations and its efficacy in minimising and eliminating protocol deviations and highlights the key steps in setting up a quality management system for research operations.

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Introduction: laboratory errors mostly emerge from the pre-analytical phase, mainly those related to collection, handling, transportation, and storage of diagnostic specimens. Specimen rejection due to improper sample collection, may lead to poor patient outcomes, such as incorrect diagnosis, inappropriate treatment, and death. This study aimed to assess the specimen rejection rate and associated factors among referred specimens at Debre Markos Referral Hospital. Methods: a prospective cross-sectional study design was applied from January 2020 to April 2020 to investigate specimen rejection rate and associated factors among referred specimens. The study population was all laboratory specimens referred for viral load, CD4 count, gene expert, and early infant diagnosis to the Debre Markos Referral Hospital laboratory. The statistical analysis was done with Statistical Package for Social Sciences version 20.0 software. Results: of the total of 2750 specimens submitted to the laboratory from January 2020 to April 2020, 37 (1.34%) specimens were rejected due to different reasons like insufficient volume, hemolysis, and an inappropriate specimen container. Specimen collector training status and experience had a significant association with the specimen rejection rate. Conclusion: the results of our study show that the specimen rejection rate among referred specimens was high, indicating that more interventions are required to decrease the specimen rejection rate.

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Critical issues in forensic science quality management have emerged in recent decades. The debate on accrediting quality management systems of forensic laboratories is relevant to the African context. Neuteboom, Ross, Bugeja, Willis, Roux, and Lothridge (2022) have conducted a comprehensive survey exploring critical issues in their article "Quality Management in Forensic Science: A Closer Inspection." Their work is a crucial foundation for our discussion, urging the African forensic community to engage in more in-depth conversations. This letter briefly describes the survey, discussing embracing the Sydney Declaration (SD) for Forensic Sciences and issues of quality management systems comprising standards, accreditation, and potential regulation, and highlights the issue of cognitive competency from an African perspective. This underscores the urgent need for critical dialogue, emphasizing that the time for action is now, and urges practitioners, particularly in Africa, to enhance quality management systems to deliver superior forensic products.

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The quality management system of occupational diseases diagnosis is belonged to one part of the hospital quality management system. It must be adhered to the quality management concept of comprehensive, full staff and whole process. To establish and improve the quality management system should be included: (1) Formulated a quality management manual for occupational disease diagnosis, including organization construction, rules and regulations, responsibilities, work flow, operating procedures and clinical pathways, standard instrument, etc. (2) Managed the document of occupational diseases diagnosis. (3) The continuous improvement of quality management. The quality management of occupational diseases diagnosis focuses on the mastery and implementation of the manual by employees, which is reflected in the continuous improvement of daily work, internal assessment and external assessment.

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Assisted human reproduction has undergone rapid advances since its inception 45 years ago. To keep pace with these advances, assisted reproduction laboratories should adhere to a quality management system that addresses staffing and training, physical space and air quality, equipment maintenance and other operational matters, and ensures gamete and embryo handling in accordance with the latest quality and safety standards. Accordingly, this review aims to provide a reference document that highlights the critical aspects to consider when establishing and operating an ART laboratory. The review collates and expands upon published national and international guidelines and consensus documents, providing easier access to this large body of important information.

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Six Sigma Foundations is a statistical standard that indicates an exceptionally high level of quality, along with a customer satisfaction management approach that intends to lower error rates and boost process efficiency. The Define, Measure, Analyse, Improve, and Control (DMAIC) approach is a fundamental component of Six Sigma and provides an organised framework for process improvement. In contrast to conventional techniques that are more manual-based, Six Sigma emphasises and focuses on making decisions based on facts and evidence. The key to the success of Six Sigma is its reliance on statistical methods. Advanced tools like Pareto charts, histograms, regression analysis, and fishbone diagrams are used ardently for the benefit of customers and to reduce the overall error rate. To support clinical decision-making, a clinical laboratory's primary responsibility is to generate test results that are accurate, repeatable, fast, and appropriately interpreted. Ensuring desired clinical outcomes must be the ultimate objective. To accomplish this goal, laboratories must prioritise cost-effectiveness while establishing and maintaining quality in all laboratory procedures. The concept of the Lean Six Sigma (LSS) methodology, which mainly centres on efficiency by discerning and eradicating actions or operations that do not provide any benefit to the organisation, is combined with the proposition of Six Sigma, which emphasises data-driven analyses and optimization. The integration of these powerful concepts aids in the overall improvement of the organisations adopting these techniques. This review provides a brief overview of the benefits of the LSS methodology and its implementation in the oral pathology laboratory.

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Through the effective application of Essential Principles of Safety and Performance of Medical Devices and IVD Medical Devices (EP), to continuously improve the corresponding management tools to ensure the safety and effectiveness of medical device in the quality management system, risk management system, evaluation of safety and effectiveness for the supervision departments and manufacturers. The current status of the application of EP and the application issues are analyzed in the study. Take artificial joint products for example, the idea of using EP in quality management system, risk management system and evaluation of safety and effectiveness is investigated, and several thoughts are proposed. Supervision departments should strengthen the unified understanding of EP, develop requirements according to the classification of medical device，and refine specific execution requirements.

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The main objectives of multidisciplinary clinical investigation center (CIC-P) are to facilitate the availability of new drugs for patients, to enhance the visibility and attractiveness of French clinical research, to improve the quality of early phase trials, and to enhance the value of academic research by evaluating molecules in rare diseases. Since 2017, the CIC-P has been committed to a quality approach process, launching in 2018 its first satisfaction survey on patient care and clinical trial management of all its employees. A second satisfaction survey targeted by profession type was to be launched in 2020, in view of the requirements of the ISO 9001:2015 standard, but the process was interrupted following the coronavirus diseases 2019 (COVID-19) pandemic. The successful reorganization of the CIC-P activity during the first containment of the COVID-19 pandemic was driven by the implementation of a quality management system that promotes continuous improvement through the organization and involvement of all the staff. This voluntary and participative approach motivated the CIC-P to apply for the organizational sesame. The ISO 9001:2015 certification of CIC-P aims at increasing its performance, to satisfying its customers and to fully integrate its activities in a continuous improvement process, according to the requirements of this international standard, through the deployment of quality tools such as The Deming wheel (PDCA), an indispensable tool for transformation and reorganization; the analysis of the environment by the strengths, weakness, opportunities, threats (SWOT) analysis tool; the analysis and management of risks by the FMEA method, and all with performance indicators (SMART) and precise objectives at each stage of a project/process. The implementation of satisfaction questionnaires remains the essential tool for evaluating the expectations and needs of interested parties, but also for improving the quality of CIC-P activities and services. All these tools put in place have allowed us to continuously improve the means of production and to constantly improve our organization.

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The amount of research on the gathering and handling of healthcare data keeps growing. To support multi-center research, numerous institutions have sought to create a common data model (CDM). However, data quality issues continue to be a major obstacle in the development of CDM. To address these limitations, a data quality assessment system was created based on the representative data model OMOP CDM v5.3.1. Additionally, 2,433 advanced evaluation rules were created and incorporated into the system by mapping the rules of existing OMOP CDM quality assessment systems. The data quality of six hospitals was verified using the developed system and an overall error rate of 0.197% was confirmed. Finally, we proposed a plan for high-quality data generation and the evaluation of multi-center CDM quality.

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The study compares an artificial intelligence technology with traditional manual search of literature databases to assess the accuracy and efficiency of retrieving relevant articles for post-market surveillance of in vitro diagnostic and medical devices under the Medical Device Regulation and In Vitro Diagnostic Medical Device Regulation. Over a 3-year period, literature searches and technical assessment searches were performed manually or using the Huma.AI platform to retrieve relevant articles related to the safety and performance of selected in vitro diagnostic and medical devices. The manual search involved refined keyword searches, screening of titles/abstracts / full text, and extraction of relevant information. The Huma.AI search utilized advanced caching techniques and a natural language processing system to identify relevant reports. Searches were conducted on PubMed and PubMed Central. The number of identified relevant reports, precision rates, and time requirements for each approach were analyzed. The Huma.AI system outperformed the manual search in terms of the number of identified relevant articles in almost all cases. The average precision rates per year were significantly higher and more consistent with the Huma.AI search compared with the manual search. The Huma.AI system also took significantly less time to perform the searches and analyze the outputs than the manual search. The study demonstrated that the Huma.AI platform was more effective and efficient in identifying relevant articles compared with the manual approach.

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OBJECTIVE: To analyze and summarize data on formation and implementation in practice of standard operational procedures for developing algorithm to improve the quality management system of bureau of forensic medical expertise. MATERIAL AND METHODS: Normative legal documents regulating principles of standardization in healthcare were studied. Literature was analyzed in PubMed, Google Scholar, eLIBRARY search engines in English and Russian languages on the issues of development and implementation of standard operational procedures in practice. RESULTS: Data on using standard operational procedures as a standardization element in medical practice have been analyzed and generalized. Specific proposals for developing system of standard operational procedures, based on general principles for the creation of such documents, in forensic medical expert institutions have been proposed. CONCLUSION: Suggested recommendations can be used in practice to develop new common standard operational procedures.

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BACKGROUND: Strengthening external quality assessment (EQA) services across the One Health sector supports implementation of effective antimicrobial resistance (AMR) control strategies. Here we describe and compare 2 different approaches for conducting virtual laboratory follow-up assessments within an EQA program to evaluate quality management system (QMS) and procedures for pathogen identification and antimicrobial susceptibility testing (AST). METHODS: During the coronavirus disease 2019 (COVID-19) pandemic in 2021 and 2022, 2 laboratory assessment approaches were introduced: virtual-based and survey-based methodologies. The evaluation of 2 underperforming Animal Health laboratories through a virtual-based approach occurred between May and August 2021. This evaluation encompassed the utilization of 3 online meetings and document reviews, performed subsequent to the execution of EQA procedures. Within a distinct group of laboratories, the survey-based assessment was implemented from December 2021 to February 2022, also following EQA procedures. This phase encompassed the dissemination of an online survey to 31 participating laboratories, alongside a sole online consultation meeting involving 4 specific underperforming laboratories. RESULTS: The virtual-based assessment post-EQA aimed to identify gaps and areas for improvement in the laboratory's practices for pathogen identification and AST. This approach was, however, time-intensive, and, hence, only 2 laboratories were assessed. In addition, limited interactions in virtual platforms compromised the assessment quality. The survey-based post-EQA assessment enabled evaluation of 31 laboratories. Despite limitations for in-depth analysis of each procedure, gaps in QMS across multiple laboratories were identified and tailored laboratory-specific recommendations were provided. CONCLUSIONS: Reliable internet and plans for efficient time management, post-EQA virtual laboratory follow-up assessments are an effective alternative when conducting onsite evaluation is infeasible as observed during the COVID-19 pandemic, although the successful implementation of remediation plans will likely require in person assessments. We advocate application of hybrid approaches (both onsite and virtual) for targeted capacity building of AMR procedures with the ability to implement and oversee the process.

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El establecimiento de un sistema de gestión de la calidad es obligatorio para algunas instituciones de salud, entre las que se encuentra el Laboratorio de Biología Molecular, esto queda explícito en la Regulación D 03-21, que plantea la obligatoriedad de su cumplimiento para los laboratorios clínicos que se basan en técnicas de biología molecular. El objetivo del presente texto es exponer los presupuestos teóricos que sustentan un estudio sobre la gestión de la calidad en el mencionado laboratorio. Se realiza una revisión documental a partir de artículos publicados en el período comprendido de 2012-2022. Del total de las fuentes consultadas en las plataformas de acceso a bases de datos de la red de información de la salud cubana Infomed: PubMed, Scopus, SciELo, Redalyc, y Dialnet, se seleccionaron 33 para la revisión al considerar que abordaban el tema con mayor profundidad. La adopción de un sistema de gestión de la calidad garantiza y gestiona el alto nivel de los servicios, aumenta la satisfacción del cliente y el prestigio de la organización.

The establishment of a quality management system is mandatory for some health institutions, among which is the Molecular Biology Laboratory. This is explicit in Regulation D 03-21, which makes compliance mandatory for laboratories. clinical trials that are based on molecular biology techniques. The objective of this text is to present the theoretical assumptions that support a study on quality management in the aforementioned laboratory. A documentary review is carried out based on articles published in the period from 2012-2022. Of the total sources consulted on the database access platforms of the cuban health information network Infomed: PubMed, Scopus, SciELo, Redalyc, and Dialnet, 33 were selected for the review considering that they addressed the topic with greater depth. The adoption of a quality management system guarantees and manages the high level of services, increases customer satisfaction and the prestige of the organization.

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Trichinellosis is a parasitic foodborne zoonotic disease transmitted by ingestion of raw or undercooked meat containing the first larval stage (L1) of the nematode. To ensure the quality and safety of food intended for human consumption, meat inspection for detection of Trichinella spp. larvae is a mandatory procedure according to EU regulations. The implementation of quality assurance practices in laboratories that are responsible for Trichinella spp. detection is essential given that the detection of this parasite is still a pivotal threat to public health, and it is included in list A of Annex I, Directive 2003/99/EC, which determines the agents to be monitored on a mandatory basis. A Quality Management System (QMS) was applied to slaughterhouses and game handling establishments conducting Trichinella spp. testing without official accreditation but under the supervision of the relevant authority. This study aims to retrospectively analyze the outcomes of implementing the QMS in slaughterhouses and game handling establishments involved in Trichinella testing in southern Spain. Canonical discriminant analyses (CDAs) were performed to design a tool enabling the classification of SLs while determining whether linear combinations of measures of quality-assurance-related traits describe within- and between-SL clustering patterns. The participation of two or more auditors improves the homogeneity of the results deriving from audits. However, when training expertise ensures that such levels of inter-/intralaboratory homogeneity are reached, auditors can perform single audits and act as potential trainers for other auditors. Additionally, technical procedure issues were the primary risk factors identified during audits, which suggests that they should be considered a critical control point within the QMS.

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Sarcomas, rare and with lower survival rates than common tumors, offer insights into healthcare efficiency via the analysis of the total interval of the diagnostic pathway, combining the patient interval (time between the first symptom and visit with a physician) and diagnostic interval (time between first physician visit and histological diagnosis). Switzerland's healthcare system, Europe's costliest, lacks research on treating rare conditions, like mesenchymal tumors. This study examines the total interval of the diagnostic pathway for optimization strategies. Analyzing a dataset of 1028 patients presented from 2018 to 2021 to the Swiss Sarcoma Board (MDT/SB-SSN), this retrospective analysis delves into bone sarcoma (BS), soft-tissue sarcoma (STS), and their benign counterparts. Demographic and treatment data were extracted from medical records. The patient interval accounted for the largest proportion of the total interval and secondary care interval for the largest proportion of the diagnostic interval. Age, grade, and localization could be elicited as influencing factors of the length of different components of the total interval. An increasing age and tumor size, as well as the axial localization, could be elicited as factors increasing the probability of sarcoma. The patient and secondary care interval (SCI) offer the greatest potential for optimization, with SCI being the bottleneck of the diagnostic interval. New organizational structures for care work-ups are needed, such as integrated practice units (IPU) as integral part of value-based healthcare (VBHC).

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Standardized routine operation management (SROM) has been widely accepted and applied by kinds of enterprises and played a key supporting role. With full use of the emerging knowledge-based smart management technology, SROM will further increase comprehensive efficiency and save human resources greatly at the same time, especially for small and medium enterprises (SMEs). Hence, we propose a systematic knowledge-based smart management method to transfer SROM activities from human operations to automatic response by means of knowledge explicitation, organization, sharing and reusing, which can be further achieved by employing knowledge graph. We took a typical SROM instance, ISO 9000 implementation management, as an example to validate the transformation from human activities to knowledge graph-based automatic operation. We firstly analyzed characteristics of domain knowledge and constructed an ontology model according to the knowledge stability. Secondly, a hybrid knowledge graph construction and dynamic updating framework together with related algorithms were designed by deliberately integrating semantic similarity calculation and natural language processing. Thirdly, we developed a question-answering mechanism and reasoning system based on the ISO 9000 implementation knowledge graph to support automatic decision and feedback for ISO 9000 routine operation management including knowledge learning and processes auditing. Finally, the practicability and effectiveness of SROM knowledge graph has been validated in a SME in China, realizing the application of question-answering, job responsibility recommendation, conflict detection, semantic detection, multidimensional statistical analysis. The proposed method can also be generalized to support auxiliary optimization decision, vertical risk control, operation mode analysis, optimization model improvement experience and so on.

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OBJECTIVES: In the medical field, we face many challenges, including the high cost of data collection and processing, difficult standards issues, and complex preprocessing techniques. It is necessary to establish an objective and systematic data quality management system that ensures data reliability, mitigates risks caused by incorrect data, reduces data management costs, and increases data utilization. We introduce the concept of SMART data in a data quality management system and conducted a case study using real-world data on colorectal cancer. METHODS: We defined the data quality management system from three aspects (Construction - Operation - Utilization) based on the life cycle of medical data. Based on this, we proposed the "SMART DATA" concept and tested it on colorectal cancer data, which is actual real-world data. RESULTS: We define "SMART DATA" as systematized, high-quality data collected based on the life cycle of data construction, operation, and utilization through quality control activities for medical data. In this study, we selected a scenario using data on colorectal cancer patients from a single medical institution provided by the Clinical Oncology Network (CONNECT). As SMART DATA, we curated 1,724 learning data and 27 Clinically Critical Set (CCS) data for colorectal cancer prediction. These datasets contributed to the development and fine-tuning of the colorectal cancer prediction model, and it was determined that CCS cases had unique characteristics and patterns that warranted additional clinical review and consideration in the context of colorectal cancer prediction. CONCLUSIONS: In this study, we conducted primary research to develop a medical data quality management system. This will standardize medical data extraction and quality control methods and increase the utilization of medical data. Ultimately, we aim to provide an opportunity to develop a medical data quality management methodology and contribute to the establishment of a medical data quality management system.

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