Information sharing across institutions: Practices and barriers during public health emergencies in Ethiopia.

BACKGROUND: Rapid, integrated information exchange between stakeholders is critical for effective emergency preparedness and response. However, many low- and middle-income countries face barriers to seamless data sharing. While information accessibility is recognized as important for evidence-based decision-making and resource allocation in Ethiopia, factors influencing current health information sharing practices among stakeholders involved in public health emergency management programs are unclear. This study aims to examine multi-sectoral stakeholders' perspectives and experiences with health data sharing during emergencies in Ethiopia, to identify opportunities and challenges influencing practices to strengthen the national public health emergency response system. METHODS: A mixed-methods study was conducted between June and August 2023, involving a survey of 169 stakeholders actively involved in PHEM programs in Ethiopia as well as 23 in-depth interviews with key informants in senior leadership or advisory roles. The data was analyzed using descriptive statistics in SPSS and thematic analysis of qualitative transcripts. RESULTS: During emergencies, it was observed that data sharing between different entities occurred. Quantitative findings showed the predominant types of health data shared between stakeholders during emergencies included hospital data (109, 64.5 %), clinical case information, and laboratory results. Challenges limiting effective coordination included issues like limited functionality of digital health systems (75, 44 %), incompatible data formats (13, 34 %), and financial constraints (83, 49 %) and and socio-cultural barriers constrain current practices in Ethiopia. Qualitative interviews identified five themes around risk communication and inclusive alert systems. Experts emphasized tailored, multichannel outreach but noted infrastructure gaps and digital divides currently limit poorer communities' engagement. CONCLUSION: While collaborative health information exchange during emergencies is recognized as important, systemic, financial, and socio-cultural barriers constrain current practices in Ethiopia. Targeted strategies including capacity building, investment in integrated data infrastructure, economic optimization through innovative financing models, trust-based relationship development, and locally relevant communication channels informed by stakeholder perspectives can optimize information accessibility, coordination, quality, and equity of healthcare services during public health emergencies.

Assessment of transparency indicators in space medicine.

Space medicine is a vital discipline with often time-intensive and costly projects and constrained opportunities for studying various elements such as space missions, astronauts, and simulated environments. Moreover, private interests gain increasing influence in this discipline. In scientific disciplines with these features, transparent and rigorous methods are essential. Here, we undertook an evaluation of transparency indicators in publications within the field of space medicine. A meta-epidemiological assessment of PubMed Central Open Access (PMC OA) eligible articles within the field of space medicine was performed for prevalence of code sharing, data sharing, pre-registration, conflicts of interest, and funding. Text mining was performed with the rtransparent text mining algorithms with manual validation of 200 random articles to obtain corrected estimates. Across 1215 included articles, 39 (3%) shared code, 258 (21%) shared data, 10 (1%) were registered, 110 (90%) contained a conflict-of-interest statement, and 1141 (93%) included a funding statement. After manual validation, the corrected estimates for code sharing, data sharing, and registration were 5%, 27%, and 1%, respectively. Data sharing was 32% when limited to original articles and highest in space/parabolic flights (46%). Overall, across space medicine we observed modest rates of data sharing, rare sharing of code and almost non-existent protocol registration. Enhancing transparency in space medicine research is imperative for safeguarding its scientific rigor and reproducibility.

Rifts over equity imperil WHO's pandemic treaty.

As deadline nears, negotiations continue over sharing pathogen sequences and vaccine doses.

An assessment of the informative value of data sharing statements in clinical trial registries.

BACKGROUND: The provision of data sharing statements (DSS) for clinical trials has been made mandatory by different stakeholders. DSS are a device to clarify whether there is intention to share individual participant data (IPD). What is missing is a detailed assessment of whether DSS are providing clear and understandable information about the conditions for data sharing of IPD for secondary use. METHODS: A random sample of 200 COVID-19 clinical trials with explicit DSS was drawn from the ECRIN clinical research metadata repository. The DSS were assessed and classified, by two experienced experts and one assessor with less experience in data sharing (DS), into different categories (unclear, no sharing, no plans, yes but vague, yes on request, yes with specified storage location, yes but with complex conditions). RESULTS: Between the two experts the agreement was moderate to substantial (kappa=0.62, 95% CI [0.55, 0.70]). Agreement considerably decreased when these experts were compared with a third person who was less experienced and trained in data sharing ("assessor") (kappa=0.33, 95% CI [0.25, 0.41]; 0.35, 95% CI [0.27, 0.43]). Between the two experts and under supervision of an independent moderator, a consensus was achieved for those cases, where both experts had disagreed, and the result was used as "gold standard" for further analysis. At least some degree of willingness of DS (data sharing) was expressed in 63.5% (127/200) cases. Of these cases, around one quarter (31/127) were vague statements of support for data sharing but without useful detail. In around half of the cases (60/127) it was stated that IPD could be obtained by request. Only in in slightly more than 10% of the cases (15/127) it was stated that the IPD would be transferred to a specific data repository. In the remaining cases (21/127), a more complex regime was described or referenced, which could not be allocated to one of the three previous groups. As a result of the consensus meetings, the classification system was updated. CONCLUSION: The study showed that the current DSS that imply possible data sharing are often not easy to interpret, even by relatively experienced staff. Machine based interpretation, which would be necessary for any practical application, is currently not possible. Machine learning and / or natural language processing techniques might improve machine actionability, but would represent a very substantial investment of research effort. The cheaper and easier option would be for data providers, data requestors, funders and platforms to adopt a clearer, more structured and more standardised approach to specifying, providing and collecting DSS. TRIAL REGISTRATION: The protocol for the study was pre-registered on ZENODO ( https://zenodo.org/record/7064624#.Y4DIAHbMJD8 ).

The use of blockchain technology in enterprise financial accounting information sharing.

This work intends to comprehensively analyze the application of blockchain technology in enterprise financial accounting information sharing and address prevalent issues such as information opacity, data tampering, and data security in the current practices. Therefore, it writes smart contracts based on the Ethereum platform to achieve the secure sharing of financial accounting information between enterprises. This work employs a randomized experimental design approach, using a computer-generated random number program to divide 100 enterprises into experimental and control groups, each comprising 50 enterprises. Enterprises in the experimental group share financial accounting information using smart contracts on the Ethereum platform during the experiment. The financial personnel of these enterprises upload reconciled data to the corresponding smart contracts using the enterprise's digital signatures after each month's accounting process. Enterprises in the control group continue to use traditional methods of financial accounting information sharing (such as email and web platforms) to share financial data files directly. Quantitative analysis is performed to compare the data between the experimental and control groups. Empirical results reveal a notable enhancement in information-sharing efficiency by 25.7%, a 19.8% improvement in data accuracy, and a 13.6% reduction in financial information-sharing costs within the experimental group compared to the control group. This work provides compelling evidence that adopting blockchain-based information-sharing methods can effectively elevate data trustworthiness and security. Supported by systematic empirical findings, this work validates the significant potential of blockchain technology in the realm of enterprise financial accounting information sharing.

Bilibili, TikTok, and YouTube as sources of information on gastric cancer: assessment and analysis of the content and quality.

BACKGROUND: Gastric cancer has attracted widespread attention on social media due to its high incidence and severity. The Bilibili, TikTok, and YouTube video-sharing platforms have received considerable interest among general health consumers. Nevertheless, it remains unclear whether the information in videos on these platforms is of satisfactory content and quality. METHODS: A total of 300 eligible videos related to gastric cancer were screened from three video-sharing platforms, Bilibili, TikTok, and YouTube, for assessment and analysis. First, the basic information presented in the videos was recorded. Next, we identified the source and content type of each video. Then, the Global Quality Scale (GQS), Journal of the American Medical Association (JAMA), and Modified DISCERN were used to assess the educational content and quality of each video. A comparative analysis was undertaken of the videos procured from these three sources. RESULTS: We identified six categories of uploaders of the 300 videos: 159 videos (53%) were uploaded by health professionals, 21 videos (7%) by users in science communications, 29 videos (9.67%) by general users, 27 videos (9%) from news agencies, 63 videos (12%) by nonprofit organizations, and one video (0.33%) by a for-profit organization. In terms of the content types of the 300 videos, we identified five distinct categories. There were 48 videos (16%) on early signals, 12 videos (4%) on late symptoms, 40 videos (13.33%) on etiologies and causations, 160 videos (53.33%) on scientific introductions, and 40 videos (13.33%) on treatment methods. The overall quality of the videos was evaluated by the GQS, JAMA, and Modified DISCERN and was found to be medium, with scores of 2.6/5, 2.41/4, and 2.71/5 points, respectively. CONCLUSIONS: This innovative study demonstrates that videos on social media platforms can help the public learn about early signals, late symptoms, treatment methods, etiologies and causations, and scientific introductions of gastric cancer. However, both the content and quality of uploaded recordings are inadequate currently. More efforts should be made to enhance the content and quality of videos on gastric cancer and to increase public awareness.

Bayesian random-effects meta-analysis with empirical heterogeneity priors for application in health technology assessment with very few studies.

In Bayesian random-effects meta-analysis, the use of weakly informative prior distributions is of particular benefit in cases where only a few studies are included, a situation often encountered in health technology assessment (HTA). Suggestions for empirical prior distributions are available in the literature but it is unknown whether these are adequate in the context of HTA. Therefore, a database of all relevant meta-analyses conducted by the Institute for Quality and Efficiency in Health Care (IQWiG, Germany) was constructed to derive empirical prior distributions for the heterogeneity parameter suitable for HTA. Previously, an extension to the normal-normal hierarchical model had been suggested for this purpose. For different effect measures, this extended model was applied on the database to conservatively derive a prior distribution for the heterogeneity parameter. Comparison of a Bayesian approach using the derived priors with IQWiG's current standard approach for evidence synthesis shows favorable properties. Therefore, these prior distributions are recommended for future meta-analyses in HTA settings and could be embedded into the IQWiG evidence synthesis approach in the case of very few studies.

Ethical implications of AI and robotics in healthcare: A review.

Integrating Artificial Intelligence (AI) and robotics in healthcare heralds a new era of medical innovation, promising enhanced diagnostics, streamlined processes, and improved patient care. However, this technological revolution is accompanied by intricate ethical implications that demand meticulous consideration. This article navigates the complex ethical terrain surrounding AI and robotics in healthcare, delving into specific dimensions and providing strategies and best practices for ethical navigation. Privacy and data security are paramount concerns, necessitating robust encryption and anonymization techniques to safeguard patient data. Responsible data handling practices, including decentralized data sharing, are critical to preserve patient privacy. Algorithmic bias poses a significant challenge, demanding diverse datasets and ongoing monitoring to ensure fairness. Transparency and explainability in AI decision-making processes enhance trust and accountability. Clear responsibility frameworks are essential to address the accountability of manufacturers, healthcare institutions, and professionals. Ethical guidelines, regularly updated and accessible to all stakeholders, guide decision-making in this dynamic landscape. Moreover, the societal implications of AI and robotics extend to accessibility, equity, and societal trust. Strategies to bridge the digital divide and ensure equitable access must be prioritized. Global collaboration is pivotal in developing adaptable regulations and addressing legal challenges like liability and intellectual property. Ethics must remain at the forefront in the ever-evolving realm of healthcare technology. By embracing these strategies and best practices, healthcare systems and professionals can harness the potential of AI and robotics, ensuring responsible and ethical integration that benefits patients while upholding the highest ethical standards.

Public preference on sharing health data to inform research, health policy and clinical practice in Australia: A stated preference experiment.

OBJECTIVE: To investigate public willingness to share sensitive health information for research, health policy and clinical practice. METHODS: A total of 1,003 Australian respondents answered an online, attribute-driven, survey in which participants were asked to accept or reject hypothetical choice sets based on a willingness to share their health data for research and frontline-medical support as part of an integrated health system. The survey consisted of 5 attributes: Stakeholder access for analysis (Analysing group); Type of information collected; Purpose of data collection; Information governance; and Anticipated benefit; the results of which were analysed using logistic regression. RESULTS: When asked about their preference for sharing their health data, respondents had no preference between data collection for the purposes of clinical practice, health policy or research, with a slight preference for having government organisations manage, govern and curate the integrated datasets from which the analysis was being conducted. The least preferred option was for personal health records to be integrated with insurance records or for their data collected by privately owned corporate organisations. Individuals preferred their data to be analysed by a public healthcare provider or government staff and expressed a dislike for any private company involvement. CONCLUSIONS: The findings from this study suggest that Australian consumers prefer to share their health data when there is government oversight, and have concerns about sharing their anonymised health data for clinical practice, health policy or research purposes unless clarity is provided pertaining to its intended purpose, limitations of use and restrictions to access. Similar findings have been observed in the limited set of existing international studies utilising a stated preference approach. Evident from this study, and supported by national and international research, is that the establishment and preservation of a social license for data linkage in health research will require routine public engagement as a result of continuously evolving technological advancements and fluctuating risk tolerance. Without more work to understand and address stakeholder concerns, consumers risk being reluctant to participate in data-sharing and linkage programmes.

Does Legislation Impede Data Sharing in Australia Across Institutions and Jurisdictions? A Scoping Review.

In Australia, regulations governing data, including formal legislation and policies promulgated by private and public agencies, are often seen as a barrier to data sharing. This sharing can include between institutions, as well as across jurisdictional borders in a federated jurisdiction such as Australia. In some cases, these regulations place a barrier to sharing data across borders or between institutions without a prerequisite requirement. In other cases, these regulations may be perceived as a justification not to share data. The objective of this review was to analyse published literature from Australia to see what regulations were used to justify not sharing data, along with any other factors that might discourage data sharing. We searched PubMed, Scopus and Web of Science for empirical and policy articles discussing data sharing in Australia. We then filtered these results via abstract and conducted a full text assessment to include 33 articles for analysis. Although there are a few areas of notable regulatory divergence with respect to legislation governing health data, most regulations in Australia are relatively consistent. Further, the absence of uniform ethics approval between sites in different states was frequently cited as a barrier to data sharing.

Connect: Cultivating Academic-Community Partnerships to Address Our Communities' Complex Needs During Public Health Crises.

BACKGROUND: Black and Latino communities have been disproportionately impacted by coronavirus disease 2019 and we sought to understand perceptions and attitudes in four heavily impacted New Jersey counties to develop and evaluate engagement strategies to enhance access to testing. OBJECTIVE: To establish a successful academic/community partnership team during a public health emergency by building upon longstanding relationships and using principles from community engaged research. METHODS: We present a case study illustrating multiple levels of engagement, showing how we successfully aligned expectations, developed a commitment of cooperation, and implemented a research study, with community-based and health care organizations at the center of community engagement and recruitment. LESSONS LEARNED: This paper describes successful approaches to relationship building including information sharing and feedback to foster reciprocity, diverse dissemination strategies to enhance engagement, and intergenerational interaction to ensure sustainability. CONCLUSIONS: This model demonstrates how academic/community partnerships can work together during public health emergencies to develop sustainable relationships.

Achieving resilience through knowledge management practices and risk management culture in agri-food supply chains.

The problems with the current food distribution system are laid forth in this study. Getting high-quality agricultural and food products to consumers is the goal of what is known as the "agri-food supply chain." Agri-food supply chain knowledge exchange and risk management culture are being studied, as is the effect of supply chain management methods on business success. We are seeing an increase in the regularity of supply chain interruptions. The recent supply chain interruptions and their associated consequences highlight the necessity for robust supply systems. The primary goal of this research is to examine the interplay between critical antecedents of the agri-food supply chain; supply chain resilience (including risk management culture); supply chain connectivity, visibility, collaboration, and agility; and the effect these factors have on supply chain resilience and, ultimately, firm performance. With the same foundational elements and backing from the literature, an empirical model has been suggested. From September 2020 to June 2021, 245 random samples were collected throughout Indonesia for this investigation. The suggested model and the interdependencies among the crucial antecedents have been verified using partial least squares-structural equation modeling (PLS-SEM). Findings from this study support the notion that agri-food supply chains benefit from increased emphasis on traceability, transparency, information sharing, and a culture of risk management. One major takeaway from this study is that by adopting the suggested methodology, businesses may build and strengthen their supply chain resilience capabilities by institutionalizing a risk management culture, raising employee risk awareness, and holding regular risk assessment drills. The study also suggests that businesses that want to strengthen their supply chains can do so by adopting information and communications technologies and visibility tools to improve their supply chain connectivity and visibility, allowing them to respond to and recover from disruptions in the supply chain more quickly. The model is validated using data from Indonesia's industrial sector. In order to establish supply chain resilience, the suggested model provides a comprehensive perspective that defines the interconnections between key antecedents. We conclude with some thoughts and suggestions for further study.

Data sharing practices in collaborative human genomic research in low- and middle-income countries: A systematic review protocol.

INTRODUCTION: The practice of creating large databases has become increasingly common by combining research participants' data into larger repositories. Funders now require that data sharing be considered in newly funded research project, unless there are justifiable reasons not to do so. Access to genomic data brings along a host of ethical concerns as well as fairness and equity in the conduct of collaborative research between researchers from high- income and low-and middle-income countries. MATERIALS AND METHODS: This systematic review protocol will be developed in line with PRISMA -guidelines which refers to Open Science Framework, registered in PROSPERO (https://www.crd.york.ac.uk/prospero/) record CRD42022297984 and published in a peer reviewed journal. Data sources will include PubMed, google scholar, EMBASE, Web of science and MEDLINE. Both published and grey literature will be searched. Subject matter experts including bioethicists, principal investigators of genomic research projects and research administrators will be contacted. After de-duplication, titles and abstracts will be screened for eligibility. Data extraction will be undertaken using a piloted form designed in EPPI-Reviewer software before conducting risk of bias assessments by a pair of reviewers, acting independently. Any discrepancies will be resolved by consensus. Analysis will be done using a structured narrative synthesis and where feasible metanalysis. This review will attempt to highlight the context of data sharing practices in the global North-South and South-South collaborative human genomic research in low- and middle-income countries. This review will enhance the body of evidence on ethical, legal and social implications of data sharing in international collaborative genomic research setting criteria for data sharing. The full report will be shared with relevant stakeholders including universities, civil society, funders, and departments of genomic research to ensure an adequate reach in low-and middle-income countries (LMICs).

A 10-year update to the principles for clinical trial data sharing by pharmaceutical companies: perspectives based on a decade of literature and policies.

Data sharing is essential for promoting scientific discoveries and informed decision-making in clinical practice. In 2013, PhRMA/EFPIA recognised the importance of data sharing and supported initiatives to enhance clinical trial data transparency and promote scientific advancements. However, despite these commitments, recent investigations indicate significant scope for improvements in data sharing by the pharmaceutical industry. Drawing on a decade of literature and policy developments, this article presents perspectives from a multidisciplinary team of researchers, clinicians, and consumers. The focus is on policy and process updates to the PhRMA/EFPIA 2013 data sharing commitments, aiming to enhance the sharing and accessibility of participant-level data, clinical study reports, protocols, statistical analysis plans, lay summaries, and result publications from pharmaceutical industry-sponsored trials. The proposed updates provide clear recommendations regarding which data should be shared, when it should be shared, and under what conditions. The suggested improvements aim to develop a data sharing ecosystem that supports science and patient-centred care. Good data sharing principles require resources, time, and commitment. Notwithstanding these challenges, enhancing data sharing is necessary for efficient resource utilization, increased scientific collaboration, and better decision-making for patients and healthcare professionals.

Quality Assessment of YouTube Videos as an Information Source for Bowel Management in Children.

PURPOSE: This study aims to evaluate the quality and reliability of YouTube videos about bowel management in children. METHODS: On April 6th, 2023, the search results for "bowel management in children" on YouTube were rated independently by two authors. JAMA Benchmark Criteria (score 0-4) and a modified DISCERN tool (score 16-80) used for quality and reliability assessment. Data was analyzed by Chi-square test and one-way analysis of variance (ANOVA). RESULTS: Out of 48 videos included, 15 (31.2%) videos were intended for professionals and 33 (68.8%) for the public. The mean number of views was 144.806 and duration was 22 ± 28.4 min. The respective mean duration of videos for professionals 57.7 ± 21.4 min and median number of views was 404.5 (17-8.840) and those for public was 5.7 ± 10.7 min and 8400 (8-5.175.975) (both, p < 0.005). The respective mean DISCERN and JAMA scores of the videos for the public was 45.30 ± 13.18 and 2.93 ± 1.07, and for professionals 75.73 ± 6.52 and 3.8 ± 1.06 (both, p < 0.05). CONCLUSION: Although the reliability of the videos uploaded for the professionals about pediatric bowel management was higher than for public, duration of the videos was longer and the viewing rates were lower. Shorter but comprehensive and easy-to-understand guidance videos for the public may be of help. TYPE OF STUDY: Descriptive study. LEVEL OF EVIDENCE: IV.

Genomic Data as a National Strategic Resource: Implications for the Genomic Commons and International Data Sharing for Biomedical Research and Innovation.

This article provides a critical review of new policies in China, the United States, and the European Union that characterize genomic data as a national strategic resource. Specifically, we review policies that regulate human genomic data for economic, national security, or other strategic purposes rather than ethical or individual rights purposes.

Global mental health and its social determinants: How should we intervene?

This paper makes the case for expanding the field of global mental health to give more attention to the social determinants of mental health. It does so by describing challenges and opportunities for intervening to address these social determinants, and by presenting some potential approaches to the choice, design and evaluation of such interventions, especially in low and middle-income countries. Challenges include distal interventions, limits to the modifiability of some social and economic determinants, poorly understood mechanisms, difficulty defining the boundaries of such interventions, the need for inter-disciplinary and inter-sectoral collaboration, limited datasets in LMIC, sample size challenges for prevention interventions, ethical issues and siloed research funding. Potential approaches include the development of more robust causal models, trial designs that allow for analysis of mechanisms and the pooling of data across diverse settings to explore the role of contextual variables. Several criteria can inform the selection of interventions that target social determinants and these include the need for plausible mechanisms, feasibility, acceptability, cultural validity of moderator, mediator and outcome variables, generalizability and sustainability. These approaches require a high level of inter-sectoral and inter-disciplinary cooperation and data sharing across sites internationally. Examples are provided from ongoing research in LMIC.