The PACIFIC ontology for heterogeneous data management in cardiology.

With the emergence of health data warehouses and major initiatives to collect and analyze multi-modal and multisource data, data organization becomes central. In the PACIFIC-PRESERVED (PhenomApping, ClassIFication, and Innovation for Cardiac Dysfunction - Heart Failure with PRESERVED LVEF Study, NCT04189029) study, a data driven research project aiming at redefining and profiling the Heart Failure with preserved Ejection Fraction (HFpEF), an ontology was developed by different data experts in cardiology to enable better data management in a complex study context (multisource, multiformat, multimodality, multipartners). The PACIFIC ontology provides a cardiac data management framework for the phenomapping of patients. It was built upon the BMS-LM (Biomedical Study -Lifecycle Management) core ontology and framework, proposed in a previous work to ensure data organization and provenance throughout the study lifecycle (specification, acquisition, analysis, publication). The BMS-LM design pattern was applied to the PACIFIC multisource variables. In addition, data was structured using a subset of MeSH headings for diseases, technical procedures, or biological processes, and using the Uberon ontology anatomical entities. A total of 1372 variables were organized and enriched with annotations and description from existing ontologies and taxonomies such as LOINC to enable later semantic interoperability. Both, data structuring using the BMS-LM framework, and its mapping with published standards, foster interoperability of multimodal cardiac phenomapping datasets.

Iranian experts' perspectives on facilitators and barriers influencing the infectious disease knowledge network: A qualitative study.

BACKGROUND: Knowledge networks, such as Communities of Practice (CoP), are essential elements of knowledge management. They play a crucial role in assimilating various knowledge domains and converting individual knowledge into collective knowledge. This study aimed to assess the concept of knowledge networks and identify facilitators and barriers influencing knowledge sharing in infectious diseases, according to Iranian experts. METHODS: This qualitative study employed content analysis and used purposive and snowball sampling. The data were collected via online or face-to-face interviews with 25 participants with diverse expertise in infectious diseases (both clinical and non-clinical), epidemiology, knowledge management, and knowledge-based business management in Iran. The thematic analysis technique was used to code the interviews, and the collected data were analyzed using MAXQDA 20 software. RESULTS: Thematic analysis of the interviews led to 437 codes. These codes were categorized into two groups: facilitators and barriers. The facilitators shaping the knowledge network for infectious diseases were classified into three main categories: individual factors, organizational factors, and communication mechanisms. Individual factors involved two themes: strengthening knowledge exchange between experts in infectious diseases and personal characteristics such as the criteria for network membership. Organizational factors comprised three themes: organizational and trans-organizational factors, management strategies, and interactions with non-governmental sectors. Communication mechanisms included two themes: the use of information technology and knowledge brokers. In addition, three important challenges were identified as barriers influencing the knowledge network: administration and policy-making, organizational and trans-organizational, and personal challenges. CONCLUSIONS: Several facilitators and barriers influence the formation of an infectious disease knowledge network, which must be addressed to ensure its effectiveness, development, and long-term sustainability. Addressing these factors will enable the network to effectively integrate diverse knowledge and contribute to advancing infectious disease management.

COVID-19 Pandemic: From Population Need to Professional Nursing Competence.

Nursing has proven to be an essential healthcare profession, especially in the face of the COVID-19 pandemic crisis. In this chapter, it shows the essential aspects of the discipline of care and its application in the face of the pandemic from an Informatics Nursing approach. The conceptual bases include the conception of care and its historical evolution. Thus, the Personal Care Knowledge Model, the clinical care sequence and its standardized languages allow Taxonomic Triangulation to be developed. Taxonomic Triangulation is a technique created by nurses that allows managing information and that served to extract knowledge from documents and clinical experiences. The application of this vision of care and its knowledge management models have been tested in different situations: from the identification of care diagnoses in a World Health Organization clinical guide to the design of a care plan manual in a hospital. On the other hand, a secondary result is the resilience shown by the nurses. A resilience based on theoretical models centered on the person and on a language that can represent life from care. In addition, nursing includes a comprehensive perspective that addresses the emotional and spiritual area. In conclusion, nurses and their specialization with skills in knowledge management allow giving visibility to care. A professional care whose purpose is to improve health systems through solutions based on care so that people can achieve their best health situation.

Sustainability risk management: Exploring the role of artificial intelligence capabilities through an information-processing lens.

The global sustainability movement is reshaping the operational requirements and managerial approaches of maritime firms, resulting in the emergence of unprecedented and complex risks in the sector. This has driven maritime firms to leverage digital tools, such as artificial intelligence (AI) capabilities, to enhance their sustainability risk management (SRM) endeavors. Drawing on the organizational information-processing theory (OIPT), this study proposes four AI capabilities: customer value proposition, key process optimization, key resource optimization, and societal good. It examines their influence on sustainability-related knowledge management capabilities (SKMC), stakeholder engagement, and SRM. A survey questionnaire was used to gather responses from 157 maritime professionals across various sectors of the industry, providing empirical data for analysis. Employing structural equation modeling, the findings reveal that AI capabilities can improve SKMC. These findings enhance existing literature by using OIPT concepts to investigate the interplay among the constructs that lead to better SRM in maritime firms. Furthermore, the study offers managerial guidance by providing insights into AI capabilities that maritime firms should incorporate into their operations, fostering best practices to effectively manage sustainability risks and ensure the firm's long-term survival.

Health and social care managers' self-assessed competence in knowledge management: A descriptive cross-sectional study.

AIM: To describe health and social care managers' self-assessed competence in knowledge management and the factors associated with management competence. BACKGROUND: It has been shown that the performance of an organization is as good as the competence of its managers, so health and social care managers' competence in knowledge management should be assessed to improve organizational performance. DESGIN: A descriptive cross-sectional design. METHODS: A total of 116 managers participated from six Finnish public health and social care organizations. The data were collected in February and August 2022 using the managers' competence in knowledge management (MCKM) instrument and analysed using descriptive statistical methods. RESULTS: Health and social care managers rated their self-reported total competence in knowledge management as good. Among the dimensions of knowledge management competence, managing a culture of competence received the highest rating, while planning competence development and cooperation was perceived as the weakest dimension. The results indicate that background factors such as the healthcare setting, the number of units managed and the number of direct staff had a statistically significant association with the health and social care managers' self-assessed competence in planning competence development and cooperation. CONCLUSION: Even though the health and social care managers' total self-assessed competence level in knowledge management was rated as good, the results underscore the significance of continuous competence development among these managers in all dimensions of knowledge management. IMPACT: By enhancing and clarifying managers' tasks and competence in knowledge management, managers can increase staff retention, attractiveness and work well-being. IMPLICATIONS: The results can be utilized to identify managers' strengths and weaknesses in knowledge management and, thus, effectively target their limited competence development resources. REPORTING METHOD: The STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) checklist. PATIENT OR PUBLIC CONTRIBUTION: There is no patient or public contribution.

An innovative referral system: Bridging healthcare providers and community supports for pregnant and parenting people.

The connection between community healthcare providers and available community-based programs is often weak. For community members to be connected with services, a strong referral link between providers and programs is paramount. The Referral Express and Central Hub (REACH) project was born out of this need for Nurse-Family Partnership (NFP) program sites in the Denver Metro area of Colorado to be better connected and coordinated with local referral sources. The objective of the REACH pilot was to create a centralized referral system and determine its feasibility in practice. After a 12-month pilot, this innovative referral system supported the increase in a number of referral partners to Denver Metro area sites, an increase in clients served across the Denver Metro area, as well as an increase in the "refer to enroll" rate which increased by 37%. The success of the pilot of REACH led the developers to test the process on a second program, Child First, which was also successful. REACH has proved to be sustainable and continues to operate for both programs. Additionally, REACH acts as a consultant to NFP sites outside the Denver Metro area, in the state of Colorado, as each site works to increase its relationships with referral partners.

Developing an online knowledge sharing platform and community of practice for health professionals: Experiences from C-WorKS developed in North East England and Yorkshire during COVID-19.

BACKGROUND: Although knowledge sharing online has been recognised as an important strategy for health professionals to apply research findings to their practice, limited research exists on how to develop and implement these platforms to help facilitate collaboration and knowledge sharing. OBJECTIVES: This study evaluated an online knowledge sharing platform and community of practice developed in the North East of England and Yorkshire during COVID-19 to support UK health and care professionals to reduce the impact of the wider consequences of COVID-19. METHODS: Semi-structured interviews with stakeholders (n = 8) and users of C-WorKS (n = 13), followed by an online survey (n = 19) among a wider group of users to analyse knowledge use. RESULTS: Interview and survey findings highlighted several strengths, weaknesses, opportunities and threats to support future development of online knowledge sharing platforms. DISCUSSION: Online knowledge sharing supports six 'pillars' of successful research and innovation partnerships. This requires distributed forms of leadership and linking of different knowledge sharing strategies, and careful combination of platforms with communities of practice. CONCLUSION: Online knowledge sharing provides pragmatic and timely strategies for health professionals in the UK to apply research evidence to their practice. Our study provides generalisable, practical insights in how to develop and implement a knowledge sharing platform.

A theory based study on diabetes self-management in older Chinese adults.

Approximately 1 in 3 (or 80 million) Chinese age 60 years or older are living with type 2 diabetes in China. New perspectives are needed to understand the intricate phenomenon of diabetes self-management (DSM) in older Chinese adults. Guided by the expanded Tripartite Model of Self-Management, this study aimed to identify the inter-relationships between the tripartite components simultaneously and their influencing factors. This cross-sectional study included a stratified random sample of 98 community-dwelling adults age 60 or older with type 2 diabetes. Findings revealed distinct predictors for knowledge about DSM, DSM behaviors and coping. There were significant inter-relationships among the tripartite components. The theoretical model was a good fit for the data. This study provides valuable insights into the complex relationships between knowledge about DSM, DSM behaviors, and coping strategies, offering direct implications for improving the health outcomes of older adults with diabetes.

The Procedures for Documenting Organizational Knowledge and Experiences: A Scoping Review.

Background: The present study was motivated by issues with earlier studies on documenting knowledge and experiences. This scoping review investigates and maps the procedures for documenting organizational knowledge and experiences. Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for Scoping Reviews (PRISMA-ScR) guidelines, a scoping review was conducted. Data were obtained by searching PubMed, Web of Science, Scopus, ProQuest, Embase, and Emerald Insight databases and Persian databases, such as Magiran, Noormags, and Ensani. The selected terms were searched using the Boolean AND/OR operators, phrases, parentheses, and truncations in the title, abstract, keywords, and text word fields. The inclusion criteria were resources relevant to the research question, studies in English and Persian, original research articles, and resources published between 2011 and 2022. Finally, 8 related papers were selected as the research population after screening records. Results: The review of the selected studies indicates that there have been different steps for documenting knowledge and experiences according to the subject's scope and the goals of the studies. The included articles revealed numerous steps for documentation-including planning, acquisition, registration, evaluation, submission, maintenance, publication, application, payment, and compensation. Conclusion: Although a systematic mechanism for documenting knowledge and experience is essential, many processes and phases are offered for documentation. Therefore, a complete review that synthesizes and integrates past study findings must still be included. Several shortcomings in past research on documenting knowledge and expertise prompted the present study. The results of the present study can be of great use to managers and employees of various organizations in topics such as the creation of standards for documenting knowledge and experiences, organizational-structural planning in this field, and training on different documentation methods.

Learning from public health practice: the development of a library of community-centered practice examples.

BACKGROUND: Valuable learning derived from public health practice can be captured through practice-based case studies, also known as practice examples. Practice examples of participatory interventions supplement the evidence base by providing information on the complexities of implementation in communities. This paper reports on a Public Health England project to build a bank of community-centered practice examples based on robust processes of collection and curation. METHODS: The multidisciplinary project had three phases: (i) development and piloting a process to collect practice examples, (ii) refining review processes and gathering further examples via national and regional teams (iii) maintenance of an accessible collection on the library platform. RESULTS: The project resulted in a searchable collection of 55 practice examples illustrating participatory approaches in public health practice. The collection shows diversity in terms of settings, population, focus and type of approach used to work with communities. A secondary outcome was the development of generic guidance and templates for further collections on public health topics. CONCLUSIONS: This project illustrates how information on the implementation of community-centered approaches in real-life contexts can be gathered and disseminated through a transferable process. Having collections of practice examples supports knowledge exchange in public health as learning is shared.

Functional Requirements for Medical Data Integration into Knowledge Management Environments: Requirements Elicitation Approach Based on Systematic Literature Analysis.

BACKGROUND: In patient care, data are historically generated and stored in heterogeneous databases that are domain specific and often noninteroperable or isolated. As the amount of health data increases, the number of isolated data silos is also expected to grow, limiting the accessibility of the collected data. Medical informatics is developing ways to move from siloed data to a more harmonized arrangement in information architectures. This paradigm shift will allow future research to integrate medical data at various levels and from various sources. Currently, comprehensive requirements engineering is working on data integration projects in both patient care- and research-oriented contexts, and it is significantly contributing to the success of such projects. In addition to various stakeholder-based methods, document-based requirement elicitation is a valid method for improving the scope and quality of requirements. OBJECTIVE: Our main objective was to provide a general catalog of functional requirements for integrating medical data into knowledge management environments. We aimed to identify where integration projects intersect to derive consistent and representative functional requirements from the literature. On the basis of these findings, we identified which functional requirements for data integration exist in the literature and thus provide a general catalog of requirements. METHODS: This work began by conducting a literature-based requirement elicitation based on a broad requirement engineering approach. Thus, in the first step, we performed a web-based systematic literature review to identify published articles that dealt with the requirements for medical data integration. We identified and analyzed the available literature by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. In the second step, we screened the results for functional requirements using the requirements engineering method of document analysis and derived the requirements into a uniform requirement syntax. Finally, we classified the elicited requirements into a category scheme that represents the data life cycle. RESULTS: Our 2-step requirements elicitation approach yielded 821 articles, of which 61 (7.4%) were included in the requirement elicitation process. There, we identified 220 requirements, which were covered by 314 references. We assigned the requirements to different data life cycle categories as follows: 25% (55/220) to data acquisition, 35.9% (79/220) to data processing, 12.7% (28/220) to data storage, 9.1% (20/220) to data analysis, 6.4% (14/220) to metadata management, 2.3% (5/220) to data lineage, 3.2% (7/220) to data traceability, and 5.5% (12/220) to data security. CONCLUSIONS: The aim of this study was to present a cross-section of functional data integration-related requirements defined in the literature by other researchers. The aim was achieved with 220 distinct requirements from 61 publications. We concluded that scientific publications are, in principle, a reliable source of information for functional requirements with respect to medical data integration. Finally, we provide a broad catalog to support other scientists in the requirement elicitation phase.

iCHECK-DH: Guidelines and Checklist for the Reporting on Digital Health Implementations.

BACKGROUND: Implementation of digital health technologies has grown rapidly, but many remain limited to pilot studies due to challenges, such as a lack of evidence or barriers to implementation. Overcoming these challenges requires learning from previous implementations and systematically documenting implementation processes to better understand the real-world impact of a technology and identify effective strategies for future implementation. OBJECTIVE: A group of global experts, facilitated by the Geneva Digital Health Hub, developed the Guidelines and Checklist for the Reporting on Digital Health Implementations (iCHECK-DH, pronounced "I checked") to improve the completeness of reporting on digital health implementations. METHODS: A guideline development group was convened to define key considerations and criteria for reporting on digital health implementations. To ensure the practicality and effectiveness of the checklist, it was pilot-tested by applying it to several real-world digital health implementations, and adjustments were made based on the feedback received. The guiding principle for the development of iCHECK-DH was to identify the minimum set of information needed to comprehensively define a digital health implementation, to support the identification of key factors for success and failure, and to enable others to replicate it in different settings. RESULTS: The result was a 20-item checklist with detailed explanations and examples in this paper. The authors anticipate that widespread adoption will standardize the quality of reporting and, indirectly, improve implementation standards and best practices. CONCLUSIONS: Guidelines for reporting on digital health implementations are important to ensure the accuracy, completeness, and consistency of reported information. This allows for meaningful comparison and evaluation of results, transparency, and accountability and informs stakeholder decision-making. i-CHECK-DH facilitates standardization of the way information is collected and reported, improving systematic documentation and knowledge transfer that can lead to the development of more effective digital health interventions and better health outcomes.

Knowledge management tools and mechanisms for evidence-informed decision-making in the WHO European Region: a scoping review.

BACKGROUND: Knowledge management (KM) emerged as a strategy to promote evidence-informed decision-making. This scoping review aims to map existing KM tools and mechanisms used to promote evidence-informed health decision-making in the WHO European Region and identify knowledge gaps. METHODS: Following the Joanna Briggs Institute (JBI) guidance for conducting scoping reviews, we searched Medline, PubMed, EMBASE, the Cochrane library, and Open Grey. We conducted a descriptive analysis of the general characteristics of the included papers and conducted narrative analysis of the included studies and categorized studies according to KM type and phase. RESULTS: Out of 9541 citations identified, we included 141 studies. The KM tools mostly assessed are evidence networks, surveillance tools, observatories, data platforms and registries, with most examining KM tools in high-income countries of the WHO European region. Findings suggest that KM tools can identify health problems, inform health planning and resource allocation, increase the use of evidence by policymakers and stimulate policy discussion. CONCLUSION: Policymakers and funding agencies are called to support capacity-building activities, and future studies to strengthen KM in the WHO European region particularly in Eastern Europe and Central Asia. An updated over-arching strategy to coordinate KM activities in the WHO European region will be useful in these efforts.

Health and social care managers' perceptions of factors affecting the competence of managers in knowledge management: A qualitative study.

AIM: To describe health and social care managers' perceptions of the factors affecting the competence of managers in knowledge management. DESIGN: A qualitative descriptive study. METHODS: A semi-structured interview was conducted with 15 managers from three public health and social care organizations in Finland. Data were collected in the spring of 2022 and analysed using inductive content analysis. RESULTS: Health and social care managers perceived that the competence of managers working in knowledge management is affected by managers' behavioural and attitudinal characteristics, their interactive network competence in knowledge management, the dimensions of their competence in knowledge management, the knowledge management infrastructure with which they work and the organizational learning culture within which they work. CONCLUSIONS: The competence of health and social managers in knowledge management is influenced by various factors, including their personal characteristics, management competence and the infrastructure and culture of the organization for which they work. However, their competence is constrained by an absence of clear processes, structures and resources in knowledge management as well as a lack of systematic support and training for managers working in knowledge management. IMPACT: The study provides valuable information for improving the competence of managers working in knowledge management in health and social care organizations. The competence of managers working in knowledge management is instrumental for successful implementation and sustaining of knowledge management practices and thus, such competence has a positive impact on the overall performance of an organization. IMPLICATIONS: Clarifying the roles and responsibilities of health and social care managers, as well as establishing organizational structures, is essential for effective knowledge management in organizations. REPORTING METHOD: Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist has been used in the reporting. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Development of a Knowledge Graph for Automatic Job Hazard Analysis: The Schema.

In the current practice, an essential element of safety management systems, Job Hazard Analysis (JHA), is performed manually, relying on the safety personnel's experiential knowledge and observations. This research was conducted to create a new ontology that comprehensively represents the JHA knowledge domain, including the implicit knowledge. Specifically, 115 actual JHA documents and interviews with 18 JHA domain experts were analyzed and used as the source of knowledge for creating a new JHA knowledge base, namely the Job Hazard Analysis Knowledge Graph (JHAKG). To ensure the quality of the developed ontology, a systematic approach to ontology development called METHONTOLOGY was used in this process. The case study performed for validation purposes demonstrates that a JHAKG can operate as a knowledge base that answers queries regarding hazards, external factors, level of risks, and appropriate control measures to mitigate risks. As the JHAKG is a database of knowledge representing a large number of actual JHA cases previously developed and also implicit knowledge that has not been formalized in any explicit forms yet, the quality of JHA documents produced from queries to the database is expectedly higher than the ones produced by an individual safety manager in terms of completeness and comprehensiveness.

Bridging the educational gap in terms of digital competences between healthcare institutions' demands and professionals' needs.

BACKGROUND: Healthcare professionals with insufficient digital competence can be detrimental to patient safety and increase the incidence of errors. In order to guarantee proper care, healthcare organizations should provide opportunities to learn how to use technology, especially for those professionals who have not received training about this topic during their undergraduate studies. OBJECTIVE: This exploratory study aimed to conduct surveys among Spanish healthcare professionals to determine whether their organisations had trained them in the use of healthcare technology and the areas where most emphasis was placed. METHODS: 1624 Spanish healthcare professionals responded to an ad hoc online survey 7 questions related to the digital skill training offered by the healthcare organisations they work for. RESULTS: Nurses were the most widely represented group, making up 58.29% of the total, followed by physicians namely 26.49%. Only 20% of the nurses surveyed had received some training from their institution related to healthcare technology. According to the participants' responses, physicians received significantly more training in this area than nurses. Training related to database searching for research purposes or computer management followed the same trend. Nurses also received less training than physicians in this area. 32% of physicians and nurses paid for their own training if they did not receive any training from institutions. CONCLUSIONS: Nurses receive less training, on topics such as database searching or management, from the healthcare centres and hospitals where they work. Moreover, they also have fewer research and digital skills. Both of these factors may lead to deficits in their care activities, and have adverse effects on patients. Not to mention fewer opportunities for professional progress.

Organizational unlearning: A risky food safety strategy?

Strategically unlearning specific knowledge, behaviors, and practices facilitates product and process innovation, business model evolution, and new market opportunities and is essential to meet emergent supply chain and customer requirements. Indeed, addressing societal concerns such as climate change and net zero means elements of contemporary practice in food supply chains need to be unlearned to ensure new practices are adopted. However, unlearning is a risky process if crucial knowledge is lost, for example, if knowledge is situated in the supply base not the organization itself, or there is insufficient organizational food safety knowledge generation, curation, and management when new practices/processes are designed and implemented. An exploratory, critical review of management and food safety academic and gray literature is undertaken that aims to consider the cycle of unlearning, learning, and relearning in food organizations and supply chains with particular emphasis on organizational innovation, inertia, and the impact on food safety management systems and food safety performance. Findings demonstrate it is critical with food safety practices, such as duration date coding or refrigeration practices, that organizations "unlearn" in a way that does not increase organizational, food safety, or public health risk. This paper contributes to extant literature by highlighting the organizational vulnerabilities that can arise when strategically unlearning to promote sustainability in a food supply context. Mitigating such organizational, food safety, and public health risk means organizations must simultaneously drive unlearning, learning, and relearning as a dynamic integrated knowledge acquisition and management approach. The research implications are of value to academics, business managers, and wider industry.

Quick links: Apprenticeship project.

This project was designed to support people to find information, resources, and evidence independently within Health Education England (now NHS England Workforce Training and Education) and allow the Knowledge Management team more time to focus on other services offered. This project aimed to pull together a number of resources in to one simple 'Quick links' page, with relevant information, resources and further training, providing people with opportunities to build on their own knowledge and skills.

Effective medical center finding during COVID-19 pandemic using a spatial DSS centered on ontology engineering.

The global spread of the coronavirus has generated one of the most critical circumstances forcing healthcare systems to deal with it everywhere in the world. The complexity of crisis management, particularly in Iran, the unfamiliarity of the disease, and a lack of expertise, provided the foundation for researchers and implementers to propose innovative solutions. One of the most important obstacles in COVID-19 crisis management is the lack of information and the need for immediate and real-time data on the situation and appropriate solutions. Such complex problems fall into the category of semi-structured problems. In this respect, decision support systems use people's mental resources with computer capabilities to improve the quality of decisions. In synergetic situations, for instance, healthcare domains cooperating with spatial solutions, coming to a decision needs logical reasoning and high-level analysis. Therefore, it is necessary to add rich semantics to different classes of involved data, find their relationships, and conceptualize the knowledge domain. For the COVID-19 case in this study, ontologies allow for querying over such established relationships to find related medical solutions based on description logic. Bringing such capabilities to a spatial decision support system (SDSS) can help with better control of the COVID-19 pandemic. Ontology-based SDSS solution has been developed in this study due to the complexity of information related to coronavirus and its geospatial aspect in the city of Tehran. According to the results, ontology can rationalize different classes and properties about the user's clinical information, various medical centers, and users' priority. Then, based on the user's requests in a web-based SDSS, the system focuses on the inference made, advises the users on choosing the most related medical center, and navigates the user on a map. The ontology's capacity for reasoning, overcoming knowledge gaps, and combining geographic and descriptive criteria to choose a medical center all contributed to promising outcomes and the satisfaction of the sample community of evaluators.

Toxic effects of nanomaterials for health applications: How automation can support a systematic review of the literature?

Systematic reviews of the scientific literature can be an important source of information supporting the daily work of the regulators in their decision making, particularly in areas of innovative technologies where the regulatory experience is still limited. Significant research activities in the field of nanotechnology resulted in a huge number of publications in the last decades. However, even if the published data can provide relevant information, scientific articles are often of diverse quality, and it is nearly impossible to manually process and evaluate such amount of data in a systematic manner. In this feasibility study, we investigated to what extent open-access automation tools can support a systematic review of toxic effects of nanomaterials for health applications reported in the scientific literature. In this study, we used a battery of available tools to perform the initial steps of a systematic review such as targeted searches, data curation and abstract screening. This work was complemented with an in-house developed tool that allowed us to extract specific sections of the articles such as the materials and methods part or the results section where we could perform subsequent text analysis. We ranked the articles according to quality criteria based on the reported nanomaterial characterisation and extracted most frequently described toxic effects induced by different types of nanomaterials. Even if further demonstration of the reliability and applicability of automation tools is necessary, this study demonstrated the potential to leverage information from the scientific literature by using automation systems in a tiered strategy.