The U.S. Department of Veterans Affairs (VA) is undergoing an enterprise-wide transition from a homegrown electronic health record (EHR) system to a commercial off-the-shelf product. Because of the far-reaching effects of the EHR transformation through all aspects of the healthcare system, VA Health Services Research and Development identified a need to develop a research agenda that aligned with health system priorities so that work may inform evidence-based improvements in implementation processes and outcomes.The purpose of this paper is to report on the development of a research agenda designed to optimize the EHR transition processes and implementation outcomes in a large, national integrated delivery system.We used a sequential mixed-methods approach  combined with multi-level stakeholder engagement approach that included research, informatics, and healthcare operations experts in EHR transitions in and outside the VA. Data from each stage were integrated iteratively to identify and prioritize key research areas within and across all stakeholder groups.VA informatics researchers, regional VA health system leaders, national VA program office leaders, and external informatics experts with EHR transition experience.Through three rounds of stakeholder engagement, priority research topics were identified that focused on operations, user experience, patient safety, clinical outcomes, value realization, and informatics innovations.The resulting EHR-focused research agenda was designed to guide development and conduct of rigorous research evidence aimed at providing actionable results to address the needs of operations partners, clinicians, clinical staff, patients, and other stakeholders. Continued investment in research and evaluation from both research and operations divisions of VA will be critical to executing the research agenda, ensuring its salience and value to the health system and its end users, and ultimately realizing the promise of this EHR transition. The U.S. Department of Veterans Affairs (VA) is undergoing an enterprise-wide transition from a homegrown electronic health record (EHR) system to a commercial off-the-shelf product. The stated goals of this transition are to improve VA providers’ ability to deliver high-quality health care for Veterans, and to promote interoperability with the U.S. Department of Defense (DoD) and community care providers, especially as VA increasingly pays for community-based non-VA care.–4 Developed by VA medical informaticists and clinicians, VistA/CPRS has long been recognized as being user-friendly for clinicians. Data generated in VistA/CPRS were used to create the VA Corporate Data Warehouse, which serves as a rich resource not only for computerized clinical decision support and management, but also for research and evaluation.The VA was among the earliest adopters of EHRs, with research and development of an EHR beginning in the 1970s, and nationwide implementation of the then ground-breaking Veterans Health Information Systems and Technology Architecture (VistA) and Computerized Patient Record System (CPRS) in the early 1990s. In 2017, VA decided to transition to a commercial off-the-shelf EHR product, and subsequently contracted with Cerner Corporation (now Oracle Cerner), enabling DoD interoperability given their transition to the same commercially-developed EHR. VA developed a 10-year phased implementation plan for a VA-adapted instance of Oracle Cerner’s Millennium EHR that began in October 2020, overseen by the VA Office of EHR Modernization . The lifetime costs for the entire transition are estimated at over $50 billion and will affect virtually every facet of VA health care delivery, with implications for clinical care, quality, safety, research, education, and more.Over the succeeding decades, efforts to upgrade and expand VistA to accommodate the needs of clinicians, researchers, and Veterans across the healthcare system have resulted in a complex system that is challenging to maintain.,10 Because of the far-reaching effects of the EHR transformation—affecting every clinical workflow for every clinical team member in over 1200 sites of care—research must be aligned with health system priorities enabling evidence-based improvements in implementation and implementation outcomes. Research must also be well coordinated to minimize burden on end-users; studying implementation requires collecting data from the same people who are learning the new EHR, all while continuing to deliver high-quality care for Veterans. The 10-year phased implementation plan for the new EHR also allows for research and evaluation findings from earlier deployment sites to systematically inform enhanced implementation strategies and outcomes for future deployments.VA has a robust intramural research mission and commitment to quality improvement. A particular strength is VA’s model of embedded research, in which health service researchers are integrated across the healthcare system and partner with operations and clinical leaders to address real-world needs.,12 The need to accelerate EHR research to improve the process and outcomes of such transitions is critical, as is the science underlying their implementation. Although a national health information technology research agenda exists, it is necessarily broad to address many aspects of technology; developing a research agenda focused on EHR transitions could provide valuable guidance for investigators in this space. VA Health Services Research and Development (HSR&D) Service funded the Coordinating Hub to Promote Research Optimizing Veteran-centric EHR Networks (PROVEN) to provide a single point of contact for the VA research community to design, conduct, and disseminate cutting-edge, operationally prioritized research and evaluation to support safe and efficient implementation of the new EHR. One of the first challenges for PROVEN was the systematic development of a comprehensive research agenda. The purpose of this paper is to report on the process of developing the research agenda and its results.Despite the costs associated with EHR transitions and their implications for healthcare delivery, remarkably little is known about EHR transitions, their impacts, or outcomes. Published literature is scant and of variable quality, limiting our ability to apply rigorous evidence to future efforts.,14–17 we (1) assessed the funded VA EHR-related research portfolio, (2) reviewed the published EHR transitions literature, and (3) convened stakeholder meetings with three key groups: VA researchers, VA operational partners, and external (non-VA) experts. These steps enabled us to reach consensus on a comprehensive EHR research agenda linked to researcher interests and capabilities linked to health system priorities and needs, anchored in nationally recognized EHR expertise to maximize rigor .We collaborated with the VA Evidence Synthesis Program in the design and conduct of a rapid systematic review of published research or evaluation of EHR transitions in or outside the VA. Results demonstrated a dearth of VA-generated EHR-related published research and a modest literature outside the VA.As implications of a new EHR for the research enterprise became clear, the VA HSR&D Service collaborated with field-based researchers (organized by EMY) to design and convene a day-long EHRM Implementation Evaluation and Research Meeting in Washington DC (June 2019). Approximately 25 participants attended including experts from the VA Office of Research and Development (which oversees HSR&D Service), representatives from OEHRM, and senior VA healthcare system leaders. Meeting objectives were to (1) identify areas where new research could provide the most value in improving implementation of the new EHR; (2) identify the most important outcomes to be assessed by research; (3) identify available data sources and possible study designs; and (4) discuss a timeline for soliciting and funding new research. The VA HSR&D Service Director, the VA HSR&D Scientific Program Manager for the informatics portfolio, and a VA HSR&D Center of Innovation Director (EMY) identified and invited VA researchers who had funding to conduct EHR-related research and/or were recognized as leaders in the field and with an eye to diverse geographic representation.The meeting began with a welcome and brief opening remarks from senior VA research leaders . An OEHRM leader in change management [Dr. Robin Graff-Reed] provided an overview of OEHRM areas of concern and plans for change management to frame operations needs. Next, four presentations by VA research experts were delivered on frameworks for studying EHR implementation and transition ; research approaches from an informatics perspective ; how implementation science can be helpful through the EHR transition ; and an overview of ongoing primary care projects related to the anticipated EHR transition in the VA Puget Sound Healthcare System (WA) . These research presentations were followed by a discussion about issues of concern with the planned EHR, existing research on EHR implementation and design inside and outside the VA, and decisions that could benefit from VA research expertise, evidence, and contextual knowledge about VA healthcare delivery. Attendees then broke out into three concurrent discussion groups: (1) implementation, change management, and organizational structures; (2) patient and provider experience; and (3) impact on quality, safety, and other performance measures. Following the breakout sessions, the full group reconvened to debrief, summarize discussions, synthesis research topics, and identify next steps. Products that resulted from this meeting include the meeting agenda, list of attendees, presentations, and meeting minutes; these products were used as inputs to the design of the Partnership Forum in Stage 2.In parallel, we (STR) actively engaged OEHRM and VA program office leaders  in the design of an evaluation of the initial “go live” sites in anticipation of launching a VA Quality Enhancement Research Initiative (QUERI) Partnered Evaluation Initiative. Through these efforts, several key operational partners for EHR-related research were identified, , and invited to participate in a panel discussion at the national VA HSR&D/QUERI research conference (October 2019), a full year before the first site would launch the new EHR.We (STR) organized a 3-h long partnership forum entitled, “Developing a Research Agenda for Cerner Implementation.” The forum’s primary objective was to collaboratively discuss EHRM research priorities, opportunities, and challenges with leaders from OEHRM, the VA Information Resource Center, and the Office of Nursing Services. The forum was open to all conference attendees; approximately 50 people participated. The session began with an overview of current EHRM research and partner perspectives on high-priority research areas. Panelists discussed cross-cutting themes for EHRM research including system implementation, system features to enhance quality and safety, increasing successful user adoption, provider behavior and well-being, and data collection and comparability for research and operations. Attendees broke out into four discussion groups, each tasked with identifying key research questions and prioritizing them according to partner goals and anticipated impact. All groups reconvened to summarize their recommendations and respond to questions. The forum concluded with reflections from VA operational partners and planning next steps, followed by post-forum development of a white paper summarizing discussion results . We used outputs of Stages 2 and 3 to develop a draft research agenda.One meeting outcome was recognition that to accelerate EHRM research effectively to keep pace with EHR deployment plans, a research coordinating hub would be needed. Within 6 months (April 2020), VA HSR&D had developed, fielded, and competed a Request for Applications to fund the PROVEN Hub. They represented over 10 diverse large healthcare systems and academic medical centers outside VA from current and past employment  and served in a variety of senior leadership roles. Areas of expertise included health information technology leadership, EHR design and implementation, clinical informatics, EHRs and patient safety, EHRs and interoperability, and human–computer interface.After drafting the research agenda, we then sought input on the draft from 12 external informatics experts as stakeholders, including 10 from outside VA. An additional two outside experts were invited but unable to participate. Experts were identified based on publications on EHR transitions, recognition in the field, and through snowball sampling.We convened external stakeholder panel meetings of these 12 experts in January and August 2021 via videoconference. Each meeting lasted 2 h and included PROVEN Hub leaders and project staff. Representatives from VA HSR&D and OEHRM attended as observers. In advance of each meeting, panelists were provided the draft research agenda and specific questions on which feedback was requested. A leading informaticist nationally recognized in and outside the VA  served as panel chair and discussion moderator. Prior to each meeting, he asked each attendee to be prepared to initiate discussion on one of the questions. After initial responses, conversation was open to input from all panelists. Participants also used the “chat” feature of the videoconferencing platform to share additional ideas and comments. Following each meeting, the PROVEN team prepared a summary of the discussion and distributed it to panel members. Products from these meetings included meeting agendas, presentations, meeting recordings, meeting chats, and summaries.The authors developed a preliminary draft of the VA EHRM research agenda using results from the literature review and first two stages of stakeholder engagement. Summaries from each stakeholder engagement session were used to triangulate common themes and ideas, which were then refined and fed back to the External Stakeholder Panel for another round of review before finalization.We present the results of each of the three stakeholder engagement meetings, followed by the resulting research agenda. The systematic review included 40 publications about transitions from one EHR to another. The review identified gaps in patient safety outcomes, data migration strategies, capacity for health information exchange, care coordination, and user practices and workarounds; in addition, more methodological approaches to studying EHR transitions were recommended, including human factors, mixed methods, and implementation science. The full review is in press.Interactive discussion at the 2019 EHRM-focused meeting yielded several key questions across multiple domains. The group also raised pragmatic questions about the conduct of research after the EHR transition, including how researchers would access analyzable data, and strategies for rapid dissemination of research and evaluation findings. Breakout groups generated several potential research questions, summarized in Table In breakout sessions that included operations partners and VA HSR&D researchers, each of the four groups identified a set of potential research questions that were priorities for operations. Each operations partner identified research questions specific to their needs. Additional questions about quality of care were identified during cross-group discussions; key questions are summarized in Table The products from the first two stages were used to draft the research agenda. For example, the content that had been under “Implementation, change management, and organizational structures” from stage 1 and “Implementation” in stage 2 was synthesized under the “Operations” heading, which encompasses implementation, training, learning health systems, and organizational structures, along with EHR governance, data quality, and conduct of research.Expert stakeholder panelists broadly endorsed the draft research agenda. They also identified high-priority research questions that would be impactful in the short term, related to VA research replicability using data from the new EHR, Veteran engagement in the EHR implementation process, human factors engineering, and organizational factors associated with EHR transitions. Given the unique opportunity of this large-scale transition, expert panelists recommended using pragmatic study designs, such as a multicenter, stepped wedge trial that could take advantage of the progressive EHR implementation across the VA. These recommendations were integrated into the research agenda. Panelists also made recommendations to develop infrastructure to expand and accelerate research on the EHR transition, including a specific funding portfolio and establishment of learning labs. Similar to discussions in the preceding HSR&D meetings, they emphasized the need for agile research that was responsive to the short-term needs of operational partners.Table With well over 200,000 healthcare personnel at nearly 1300 facilities, the VA transition from VistA/CPRS to a new EHR is among the largest EHR-to-EHR transitions attempted. Its occurrence in a national integrated delivery system with embedded research infrastructure has created unprecedented opportunities to conduct research and evaluation on all aspects of the EHR transition. Using a multi-level stakeholder engagement process, we developed a comprehensive EHR-focused research agenda to identify high-priority, operationally aligned research topics. The PROVEN Hub was funded early on to coordinate research and evaluation, prevent duplicative work, and limit burden on frontline staff faced with fundamental changes to their clinical and administrative workflows. The resulting agenda includes a broad range of topics that encompass both pragmatic operational issues and fundamental changes to healthcare delivery across VA, increasing EHR-focused granularity compared to broad informatics research agendas. Carrying out this agenda will necessitate expansion of the VA informatics research workforce, funding mechanisms to support rapid-pace research and evaluation, and ready access to needed data.–23 EHRM leadership and governance—key to effective transitions—have also undergone many changes, necessitating continuous relationship building between research and operations leaders. To that end, PROVEN continues to engage with EHRM-IO, numerous clinical program offices, local and regional operations leaders, and the research community. Patient safety events and other problems have been documented by the VA Office of the Inspector General.,25 Program leaders have been called to multiple hearings before the US House of Representatives and Senate committees that have oversight responsibility for the EHR’s modernization.,26 Problems were also identified with end-user training effectiveness. And, the VA EHR transition represents a cultural transformation toward national standardization of procedures and documentation across diverse healthcare facilities. Collectively contributing to implementation delays, these and other challenges have complicated the advancement of EHR-focused research.There are numerous challenges to implementing this research agenda. Not surprisingly, the new EHR is undergoing changes with each implementation wave to increase capabilities and correct problems; thus, the tool itself is evolving. Different data structures and clinical workflows between old and new EHRs also hinder comparative research between VistA/CPRS and Cerner sites. Implementation of the new EHR also began in October 2020, with front-line staff as primary end users already overtaxed from months of providing healthcare in the context of the COVID-19 pandemic.Nonetheless, research and evaluation have progressed in many areas. VA QUERI has supported two partnered evaluation initiatives related to the EHR transition. The first is a mixed-methods evaluation that is designed to understand clinician and staff experiences with the EHR transition with a goal of identifying challenges and promoting improvement opportunities for successive waves of the transition. The second focuses on the needs of health professions trainees, who play a critical role in care delivery across the VA, and will assess specific solutions to improve their experience with the EHR transition. Through the PROVEN Hub, VA HSR&D has supported ten pilot projects addressing a range of research areas including patient safety, referrals management, governance, organizational readiness for change, women’s health, data quality, and Veteran experience. PROVEN also facilitates a Patient Safety and Human Factors Research Workgroup to help researchers collaboratively develop new projects. VA HSR&D recently funded a new study focused on employee burnout related to the EHR transition.,29 using a different set of methods may have resulted in different priorities. Our portfolio review was also limited to active projects funded by VA HSR&D and QUERI. We may have missed projects funded by other agencies.There are other approaches to developing a research agenda;The VA’s transition to a new EHR presents an unprecedented opportunity to pursue research capable of improving implementation and outcomes. This research agenda was designed to guide development of future science aimed at generating actionable results to address the needs of operations partners, clinicians, patients, and other stakeholders. The VA has already made substantial investments in supporting this area of research. Continued investment in research and evaluation from both research and operations divisions of VA will be critical to executing the research agenda, ensuring its salience and value to the health system and its end users, and ultimately realizing the promise of this EHR transition.


Numerous environmental factors have a negative impact on the physiology and yields of plants . A numbeManzoor et al., these authors looked at the use of different NPs against four abiotic stresses including heavy metals, drought, salinity, and heat stress. This review has demonstrated the ability of NPs to protect crop plants from various abiotic stresses and the methods by which NPs may accumulate in plants. The application of NPs dramatically enhanced the abiotic stress tolerance of plants by enhancing cellular antioxidants, nutrient absorption, photosynthetic efficiency, and biochemical/molecular mechanism regulation. Although nano-fertilizers provide a cost-effective method for enhancing the abiotic stress tolerance of plants by supplying necessary nutrients, their widespread use has raised concerns about their potentially harmful impacts on the environment. Aguirre-Becerra et al. reviewed the use of NPs against different abiotic stresses: drought and salinity stresses, temperature stress, soil contamination with trace metals, and light stress. This review provides an overview of the effect of nanomaterials (NMs) on the abiotic stress resistance of plants. Implementing NMs and NPs is one of the primary solutions advocated for substituting traditional fertilizers, herbicides, and pesticides in agriculture and improving the influence of growth regulators and plant defenses. This relatively new method produces various results depending on the crop, NM content, application type, and application frequency. The specific effect of each NP is determined by its size, surface area, thermal stability, crystallinity, concentration, electromagnetic-optical properties, and origin. Biosynthesis of NPs implementing bacteria, fungi, and plant extracts resulted in enhanced plant resistance to abiotic stress and decreased phytotoxicity. In addition, the nutrient diversity, regulated release, and rapid absorption of NPs make them viable tools for the agri-food industry, resulting in increased crop growth and yield and accelerated germination processes. In the review by El-Saadony et al., the authors provide an overview of the implementation of NPs in abiotic stress tolerance  with special reference to Si NPs, Ag NPs, TiO2 NPs, and Zn NPs. By activating plant defense systems via the stimulation of reactive oxygen species (ROS) scavenging system, NPs, such as TiO2, SiO2, and Ag NPs, can minimize the deleterious impacts of abiotic stress. Due to their small size, NPs can also easily permeate plant tissues, where they exert a favorable influence on plant morphological, physiological, and biochemical processes, enhance plant development, and boost crop output in plants subjected to a variety of abiotic challenges. In addition, the vast surface area of NPs enhances the absorption and delivery of numerous specific nutrients.Three articles focused on providing comprehensive reviews of the role of NPs utilized to tolerate different abiotic stresses in plants. In the review by Verma et al. reviewed the role of Si NPs in alleviating drought stress. It has been determined that Si NPs play an important role in agroecosystems and enhance stress resistance qualities for future sustainable agriculture. The paper by Riaz et al. examined the effect of nanosilicon on the regulation of ascorbate-glutathione contents, antioxidant defense system, and growth of copper-stressed wheat seedlings. Si NPs can relieve Cu2+ stress in wheat seedlings, according to the study’s findings. This research may aid in increasing wheat yield in Cu2+-contaminated soils. Desoky et al. examined the integrated application of bacterial carbonate precipitation and Si NPs and found that they enhance the productivity, physiological attributes, and antioxidant defenses of wheat under semiarid conditions. This treatment significantly activated the antioxidant defense system to minimize the detrimental effects of oxidative stress, hence boosting tolerance and enhancing wheat plant output in sandy soils under semiarid climatic conditions.Three articles discussed the potential of silicon NPs in alleviating different abiotic stresses. Dola et al. showed that nanoiron oxide accelerated the growth, yield, and quality of Glycine max seeds in water deficit conditions. The results indicated that exogenous foliar sprays were more effective than other treatments in enhancing drought tolerance and can be utilized to reduce productivity losses caused by drought stress in soybean-growing areas. Gao et al. showed that zinc oxide NPs improved the lettuce plant tolerance to cadmium by stimulating antioxidant defense, enhancing lignin content and reducing metal accumulation and translocation.The study by In summary, the work presented in this Research Topic documents showed how different types of NPs could be effectively applied to mitigate abiotic stresses and improve growth and productivity of different plants. Nanoparticles can activate ROS-scavenging system (compounds and enzymes) synthesis alongside other metabolic processes that support plants to tolerate different environmental stresses. In spite of this, the applications of NPs in crop enhancement and sustainable agriculture are still in their earliest years, and the existing research in the subject is limited and inconsistent. In order to prevent the negative impacts of NPs on ecosystems and crops, it is necessary to carry out further research into the following issues: a) the response of nanoparticles with plants and metabolic processes at the molecular and cellular levels, as well as the optimization of nanoparticles’ size and concentration prior to field application; b) the impacts of NPs and their potential toxicity in various plant species; c) the influence of NPs on gene regulation and expression in plants subjected to diverse abiotic stressors; d) the behaviour and destination of NPs in plants and the environment; e) the influence of soil characteristics and plant species on the efficacy of NPs; (f) the classification of NPs as stress in activators; and (g) the combined impact of NPs with other active components and biotic stressors in plants.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


High quality intervention research is needed to inform evidence-based practice and policy for Aboriginal and Torres Strait Islander communities. We searched for studies published from 2008–2020 in the PubMed database. A narrative review of intervention literature was conducted, where we identified researcher reported strengths and limitations of their research practice. A total of 240 studies met inclusion criteria which were categorised as evaluations, trials, pilot interventions or implementation studies. Reported strengths included community engagement and partnerships; sample qualities; Aboriginal and Torres Strait Islander involvement in research; culturally appropriate and safe research practice; capacity building efforts; providing resources or reducing costs for services and communities; understanding local culture and context; and appropriate timelines for completion. Reported limitations included difficulties achieving the target sample size; inadequate time; insufficient funding and resources; limited capacity of health workers and services; and inadequate community involvement and communication issues. This review highlights that community consultation and leadership coupled with appropriate time and funding, enables Aboriginal and Torres Strait Islander health intervention research to be conducted. These factors can enable effective intervention research, and consequently can help improve health and wellbeing outcomes for Aboriginal and Torres Strait Islander people. High quality research and evaluation that provides a sound evidence base can enable new understandings of health and disease, treatments and interventions, and directly inform the implementation of health policy that has measurable impacts on health outcomes . RecentlMany distinct types of research provide differing and complementary insights into complex health problems. Interventions and evaluations have the capacity to directly impact health outcomes and policy through the translation of evidence into practice . While rCritically, Indigenous people globally have reported negative experiences and impacts of research . HistoriThe current review is a secondary analysis of a subset of studies from a larger review . The parStudies were included if they: (i) reported original research; (ii) were focused on Aboriginal and Torres Strait Islander health in Australia; and (iii) used intervention designs, including evaluations, trials (randomised and non-randomised), pilots, and implementation studies. Descriptive research studies  and non-data-based studies  were excluded.Identified studies were classified by research type by one of three authors . Location and remoteness were extracted for all studies. For each study meeting eligibility criteria, data was extracted using NVivo by RM (non-Indigenous), MK (Wiradjuri), and FC (Gomeroi) to identify researcher reported strengths and limitations of their research practice. Strengths and limitations reported in studies applicable to both conducting research itself and research impact were extracted, as impacts on the research process ultimately impact research outcomes. FC cross-checked 20% of the studies, and no discrepancies were found. A narrative review was selected to synthesise the results as this is an appropriate method for summarising strengths and limitations to the research process . The strn = 110), pilot intervention (n = 30), trial (n = 56) or implementation (n = 44) design, which resulted in 240 studies that were included in the analysis Thirty-two studies identified properties of the sample as a strength. This included large sample size, a diverse sample, and/or generalisable sample. A large sample size was considered to give confidence of comprehensive results and provide rigour, while a diverse sample was considered to contribute to the broad representation of participants and geographical reach of the programs. Most of the studies that spoke of diversity as a strength predominantly referred to this in terms of geographic location or ability to reach remote settings, rather than in relation to age or gender.“The Aboriginal leadership of the project was crucial in enabling the VACCHO nutrition team to build the capacity of both Aboriginal community organisations and mainstream organisations across the sector”—Genat et al., 2016 [Twenty-one studies recognised having Aboriginal and Torres Strait Islander people as part of the research team as a strength. Some noted Aboriginal leadership as key for meaningful engagement, ensuring community priority areas were met, delivering a culturally safe environment, building rapport, and enabling the research team to contribute to capacity building of communities and Aboriginal and Torres Strait Islander community organisations. Within these studies, some specifically referred to Aboriginal and/or community leadership over the whole program. Additionally, some studies highlighted the importance of Aboriginal governance in their project in decision making and guidance processes. Similarly, in several studies, Aboriginal research staff were considered important, such as helping with recruitment, program uptake, and retention rates.“On the whole, the removal of cost barriers and the creation of welcoming, culturally safe spaces appeared to make the greatest contribution to increased access to chronic illness prevention and management services by Indigenous people”—Bailie et al., 2015   and service providers. Several studies commented on the benefit of capacity building, including ensuring culturally appropriate practice, better engagement with the study by participants, and good recruitment rates.“The success of the program was the result of identifying the key issues, involving key experts in the development of the materials, and creating a supportive and robust infrastructure within the health care organisation by making the resources available for future use by staff”—Khalil et al., 2019  The most frequently reported limitation identified across studies related to difficulties achieving the target sample size, which was reported in 119 studies. This was often noted as having an impact on the generalisability of the research and contributed to lack of statistical power, particularly in randomised controlled trials. Difficulties achieving the target sample size were attributed to staff turnover, reported difficulties with participant recruitment and difficulties in engaging Aboriginal and Torres Strait Islander communities. Additionally, a number of studies reported that high attrition rates limited their findings. Some studies indicated that attrition impacted statistical power, increased potential bias, reduced researchers’ ability to interpret findings, and created challenges for participant follow-up.“The project’s timeframe further limited the potential sample size. Funding was allocated in September 2016, recruitment commenced in November 2016, and due to the non-negotiable end date of 30 June 2018, recruitment ended in December 2017. A longer recruitment period would likely have increased participation”—Askew et al., 2019  . Longer and more flexible funding timeframes for large scale interventions and evaluations allows for respect of Aboriginal and Torres Strait Islander community timelines and timeframes required for appropriate and ethical community engagement. This is particularly important when considering the complexities of multi-state ethics processes. Shared learning and reflective practice are one approach researchers can take to do better when it comes to Aboriginal and Torres Strait Islander health research.


Digital health technologies used in primary care, referred to as, virtual primary care, allow patients to interact with primary healthcare professionals remotely though the current iteration of virtual primary care may also come with several unintended consequences, such as accessibility barriers and cream skimming. The World Health Organization (WHO) has a well-established framework to understand the functional components of health systems. However, the existing building blocks framework does not sufficiently account for the disruptive and multi-modal impact of digital transformations. In this review, we aimed to develop the first iteration of this updated framework by reviewing the deployment of virtual primary care systems in five leading countries: Canada, Finland, Germany and Sweden and the United Kingdom (England). We found that all five countries have taken different approaches with the deployment of virtual primary care, yet seven common themes were highlighted across countries: (1) stated policy objectives, (2) regulation and governance, (3) financing and reimbursement, (4) delivery and integration, (5) workforce training and support, (6) IT systems and data sharing, and (7) the extent of patient involvement in the virtual primary care system. The conceptual framework that was derived from these findings offers a set of guiding principles that can facilitate the assessment of virtual primary care in health system settings. Remote consultations in primary care feature in some health systems for several years. With the arrival of Covid-19, there was a concerted widespread effort to move towards remote consultations. But there may be negative impacts on patient care when consultations are not in person. To better understand the impact of remote consultations in primary care we conducted a narrative review and map the findings against the World Health Organization framework of the functional features of health systems. We develop the first iteration of this updated framework that accounts for the heterogenous nature of digital transformations and review the deployment of virtual primary care systems in five leading nations: Canada, Finland, Germany and Sweden and the United Kingdom (England). Seven common themes emerge: the stated policy objectives, regulation and governance, financing and reimbursement, delivery and integration, workforce training and support, IT systems and data sharing, and the extent of patient involvement in the virtual primary care system. Digital health technologies represent a growing market share due in part to rapid advances in wireless technology and computing power as well as increasing interest in the application of artificial intelligence (AI) in health systems and service delivery, but also patient interest in having faster and easier access to medical care . DigitalThe World Health Organization (WHO) has a well-established framework to understand the functional components of health systems, comprised of six building blocks  , which aIn this article, we aimed to develop the first iteration of this updated framework by reviewing the deployment of VPC systems in five leading countries: Canada, Finland, Germany, Sweden, United Kingdom (UK) with a focus on England ,13–16. TWe performed a narrative review to identify gaps in the existing WHO building blocks framework and develop the conceptual framework. Five databases  and Google Scholar were searched. Articles were included if they comprised empirical research, systematic reviews and review articles and were published between 2011 to the first quarter of 2022. Grey literature was identified through Google (Scholar) searches, websites of national institutions, and institutions that conduct health policy analyses . Two autFindings of the review were first clustered in seven overarching categories, which were derived from the original WHO building blocks framework: (1) stated policy objectives, (2) regulation and governance, (3) financing and reimbursement, (4) delivery and integration, (5) workforce training and support, (6) IT systems and data sharing, and (7) the extent of patient involvement in the VPC system.The narrative review identified forty relevant articles –47 Tabl. The seaWith respect to objectives, the studied countries reflect a mix of federal and sub-national arrangements in health policy planning and delivery. All studied countries had developed national digital health strategies at the time of this study –22. All objectives, most decision-making is devolved to the provincial level, which leads to varying requirements across the country , p, p43], pIn Canada, there is a need for greater focus on streamlining requirements for VPC systems across the country, strengthening interoperability, putting a greater emphasis on user-centred approaches, and increasing support for health professionals in their training ,20. The In Finland, the government has prioritised the digital health infrastructure over several years ,27. For In Germany, the federal push towards remote consultations has contributed to its widespread availability. For example, over 25,000 practices offer a virtual consultation; but there is a need for more training and support of healthcare professionals in using these platforms . IntegraIn Sweden, further policy work is needed to ensure better coordination of care by integrating services, including coordinating IT systems and improving data sharing for better regulatory oversight of the private platform providers of VPC systems, as well as evaluating the current modes of payment and reimbursement of virtual consultations . BuildinIn England, the multiplicity of decision-making bodies poses a real challenge with coordination and communication, making it difficult to provide a clear national steer to facilitate the implementation of a robust VPC system . For exaThere are limitations in our analysis that should be noted. Our study focussed on five countries to capture differences in the policy development, implementation and delivery of VPC systems. The narrative review was not systematic in design. The analysis is based on published available information and did not capture policy changes beyond 2022. We are unable to verify the published information with corroboration from field experts, though we did draw on expertise of the study team to compliment the narrative review. We note that the referenced publications are predominantly in English and so is not exhaustive of publications in each country’s native language, which may be especially relevant for our collection of grey literature. This framework has implications to understand secondary and tertiary care services, particularly around coordination of care involving electronic health records for example and is an important policy area worthy of future work but was outside the scope of this analysis .In conclusion, the implementation of VPC within a health system is a complex challenge that is contingent on many stakeholders. Our proposed digital health policy framework and guiding principles can be a useful starting point to assess how VPC systems are working in practice. The growing interest in VPC suggests that decision-makers should consider a flexible VPC offer; one that is more appropriate at identifying patients and draws on user experience to inform the design of its delivery, the health impacts and particularly for underserved populations including affordability of digital devices, and connectivity. A policy to expand VPC policies at scale requires consideration of the financial sustainability including pricing and reimbursement of VPC, the cost of putting in place the required infrastructure, data needs and a well-trained workforce to support its delivery. Ultimately, a well-designed primary care system forms the cornerstone of an effective health system. In the face of rising healthcare costs and health workforce shortages worldwide, it is vital that VPC can be mobilised effectively without the risk of exacerbating existing inequalities or further skyrocketing healthcare costs.S1 Table(PDF)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(PDF)Click here for additional data file.


Michael Peters and colleagues argue that concerted efforts to embed implementation research can improve health services, even in the most challenging operating environments As countries emerge from the acute phase of the SARS-CoV-2 covid-19) pandemic, there is a need to reflect on global systems of knowledge production and uptake. The rapidly evolving context of the covid-19 pandemic response demanded timely interpretation and translation of evidence into policy and action to reduce morbidity and mortality, yet existing systems were largely unable to keep up with demand.9 pandemiIn a research environment that historically prioritises the development of new technologies or interventions over improving the delivery of existing interventions, emphasis should be placed on strategies that enable health research to improve implementation.Models of embeddedness of implementation research depend on the relationships between researchers, policy makers, and implementers during the study process.Embedding implementation research can strengthen the communication between researchers and decision makers, and they can move towards consensus on learning agendas and co-production of knowledge. However, barriers for embedding implementation research reported in studies in LMICs include the low baseline appreciation of research from stakeholders, lack of timeliness, and difficulties with political processes and organisational cultures.In this analysis, we argue that concerted efforts to embed implementation research through organisational or pragmatic approaches can improve the impact of research on health services in LMICs, even in the most challenging operating environments, using the covid-19 response as a case study.During the early stages of the covid-19 pandemic, governments that had teams of trained and trusted researchers were better equipped to implement evidence based policy to maintain high quality care during the response.In South Africa’s Western Cape Province, pre-existing systems for embedding implementation research supported the development of clinical guidelines, interventions, and evidence based public health measures that improved health systems performance. In addition to the organisational culture of the health department, access to and use of a real time, trusted, patient level information database was instrumental in creating an effective system-wide response. Frequent “huddles,” or action orientated engagements with key evidence providers (academic partners) and stakeholders , were held throughout the early acute stages of the pandemic. Real time information on patient risk factors, covid-19 diagnosis, and outcomes provided analysts with data to respond to decision makers’ needs, which in turn enabled them to enact appropriate policy and strategies. More importantly, the same systems of data collection and review enabled decision makers to quickly identify when outcomes were worsening or becoming less equitable over time, prompting a quick response. After showing that outcomes in patients with covid-19 were worse during periods when health services were under the greatest pressure from covid-19 admissions, Western Cape Department of Health and Wellness implemented public health and social measures to reduce hospital service pressure and measured their effects. These strategies took the form of firstly, reducing covid-19 transmission through lockdowns, and secondly, reducing trauma admissions  through an alcohol ban to free up capacity to care for covid-19 patients.Programmatic approaches to embedding implementation research entail local researchers working closely with decision makers and implementers to embed research, evidence, and evaluation into routine implementation cycles of programmes or projects, rather than changing organisational cultures.PSBI is a major cause of infant mortality in sub-Saharan Africa, responsible for 37% of infant deaths each year.In Ethiopia, the Addis Ababa based research team embedded with both the federal Ministry of Health and woreda (district) level health officials to develop and then contextualise PSBI implementation strategies for two woredas. Decision makers prioritised the implementation challenges for further research, identified potential solutions and strategies, and facilitated the implementation, review, and adaptation of strategies.Researchers from Population Council-Kenya provided embedded implementation research support to government partners and implementers in two counties (Busia and Migori) to improve PSBI detection and management. As in Ethiopia, policymakers and implementers provided context specific guidance on the research questions of interest, beginning with a baseline formative assessment. Based on analysis of referral pathways collected during routine monitoring and supervision visits, the research team identified weak links between communities and health facilities as a major barrier to effective treatment of PSBI. The monthly assessment cycles brought together embedded researchers, implementers, and ministry officials and provided opportunities for real time learning and adaptation of interventions. This manifested in revising PSBI management protocols to account for covid-19 related restrictions, introducing digital support tools, and training community health workers to strengthen continuity of care. Despite initial concerns about the project’s longevity, the PSBI package was integrated into routine essential newborn health services in both counties. While both Ethiopia and Kenya had similar roles for researchers, policy makers, and implementers, the stakeholders concerned varied based on context , and existing coordination mechanisms were repurposed and strengthened to improve timely uptake of research findings.It is important to note that embeddedness can occur in varying degrees, and demand for such arrangements should ultimately come from decision makers themselves.Future health systems need to tackle today’s issues while also considering how to sustain these gains in the event of health emergencies like the covid-19 pandemic. Embedding implementation research is effective in improving delivery of life saving interventions while also building resilience to health threats. All parties in global health have roles to play: donors can include embeddedness as a criterion for funding, academics can advocate for and incentivise partnerships, and decision makers can integrate embedding into their organisations and health systems. Appropriate application of these approaches can support the incremental gains in intervention effectiveness required to continue improving population health and strengthening health systems.Embedding implementation research can improve health outcomes by ensuring research is an integrated and systematic part of health systems functionsEmbedded implementation research can occur across multiple levels, including the organisational level through integration into formal planning and budgeting processes, and the programmatic level, where research and learning collaborations are tied to specific health project cyclesEmbeddedness can prepare health systems to respond to emerging health shocks like the covid-19 pandemic and improve the quality of service delivery, even in the most challenging operating environments Donors, policymakers, implementers, and researchers all have critical part to play in prioritising embeddedness and strengthening the research and learning capacity of health systems


Commercial exergames are widely available tools that can support physical rehabilitation at home. However, the effects of the unsupervised use of commercial exergames in home environments are not yet clear. Hence, we provide a systematic review on the effects of unsupervised commercial exergaming at home on adults' physical health (RQ1) and quality of life (RQ2). We also scrutinize adults' experiences with exergaming at home regarding participant support, adherence, and adverse outcomes (RQ3).We searched Web of Science, PsycINFO, PubMed, Embase, and CINAHL for peer-reviewed randomized controlled trials with adults in need of rehabilitation. Overall, 20 studies  met our inclusion criteria. The quality of evidence was assessed with the Cochrane risk of bias tool.Effects of unsupervised commercial exergaming at home on physical health were higher in seven studies and similar in five studies regarding the respective comparison or control conditions; eight studies reported non-significant findings. Of the 15 studies that also examined effects on quality of life, improvements were higher in seven studies and similar in two studies regarding the respective comparison or control conditions; results were non-significant in six studies. Participant support consisted of setup of the exergaming system, instructions, training, and contact with participants. Adherence was high in eight studies, moderate in six studies, and low in one study. Adverse outcomes related to exergaming were found in four studies and were at most moderate. Concerning the quality of evidence, six studies were related to a high risk of bias due to outcome reporting bias or ceiling effects in the primary outcome. Additionally, 10 studies yielded some concerns, and four studies were related to a low risk of bias.This systematic review summarizes promising evidence that the unsupervised use of commercial exergames can support and complement rehabilitation measures in home environments. Still, future studies based on larger samples and using more recent commercial exergames are needed to obtain more high-quality evidence on the effects of different exercise prescriptions. Overall, considering the necessary precautions, the unsupervised use of commercial exergames at home can improve the physical health and quality of life in adults with needs for physical rehabilitation.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341189, identifier: PROSPERO, Registration number: CRD42022341189. Concerning arm, hand, and leg rehabilitation, meta-analytic findings indicate that playing commercial exergames at home has beneficial effects on adults with neurological diseases that are at least comparable with conventional therapy or usual care  guidelines , and PubMed, Embase, and CINAHL (via CENTRAL) were searched without time restrictions. Each database was searched first on July 12, 2022. In addition, we updated our search results from each database last on January 30, 2023. The search strings are provided in Following the PICOS  statement, the inclusion and exclusion criteria of our systematic review can be found in Titles and abstracts of eligible studies were screened and coded independently by three reviewers . For all included studies, we performed data extraction and synthesis, where possible. If necessary, the authors of the included articles were contacted to request missing or additional data. The quality of evidence was assessed using the revised tool to assess the risk of bias in randomized trials (RoB 2)  checklist, three reviewers  extracted essential information from eligible studies  location, design, and participants, (2) background and aims of the studies, (3) exergaming interventions and control/comparison groups, (4) effects of exergaming on physical health, (5) effects of exergaming on quality of life, (6) experiences with the exergaming interventions, and (7) financial support and financial conflict of interest. More specific information about the exergaming interventions and control/comparison groups regarding exercise and training variables can be found in The included studies were conducted in different countries. Six studies were conducted in the United States , the studies include more male  than female participants .Overall, data were collected from 1,558 participants , with final/analyzed sample sizes ranging from 10 participants  included only Wii Fit games   specified the intensity at which participants were exercising  reported information on session duration only in terms of minimum or maximum values, three of which only reported prescribed duration per week (session duration unknown). No information on session duration was provided for the exergaming group in overall five studies (25%), and six studies (30%) used control groups that were not instructed to exercise, so session duration was not applicable see .Fourth, the frequency in the studies ranged from two times per week    was realized in each study and included setting up the exergaming system, training with the exergaming system, and contact with participants see . First, Adherence with the intervention (RQ3b) was reported in 15 studies see . AdherenInformation on adverse outcomes (RQ3c) was provided in 14 studies see . AdverseIn the context of commercial exergames, financial support of the studies and financial conflicts of interest of the study authors could be of relevance. Concerning financial support, one study (5%) indicated no funding yet received three exergaming devices from the manufacturer  , seven of the 20 included studies (35%) found that exergaming was more effective than usual rehabilitation care, usual activities, conventional exercises, cognitive digital games, and physical activity advice. Still, three of these studies were related to a high risk of bias in terms of outcome reporting bias regarding the primary outcome. Moreover, four studies yielded some concerns due to missing protocol and analysis plans so that only one study was related to an overall low risk of bias. In addition, similar improvement was found in five studies (25%) that compared exergaming to tailored exercises, usual activities, or conventional exercises. Three of these studies were related to some concerns, and two were related to low risk of bias. Eight studies (40%) found no significant changes in both groups and ranged from low to high risk of bias. In sum, considering that effects on some primary outcomes remain unclear due to reporting bias, most studies reported similar or higher effects of unsupervised exergaming at home on physical health in relation to comparison interventions.Concerning the 15 studies that evaluated the effects of exergaming on quality of life (RQ2), seven studies (47%) reported better outcomes for the exergaming groups compared to usual rehabilitation care, usual activities, conventional exercises, and cognitive digital games. Two of these studies had a high risk of bias in terms of ceiling effects or outcome reporting bias regarding the primary outcome. Quality of life was also found to increase similarly in two studies (13%) that compared exergaming to tailored or conventional exercises and had a low risk of bias. No significant changes were found in six studies (40%), which ranged from low to high risk of bias. Overall, most studies reported that the unsupervised use of commercial exergames in home environments had similar or higher beneficial effects on adults' quality of life in relation to comparison interventions.Concerning experiences with the exergaming interventions, we focused on participant support in relation to the intervention (RQ3a), adherence with the intervention (RQ3b), and adverse outcomes related to the intervention (RQ3c).Participant support was realized in all studies and included setting up the exergaming system, training with the exergaming system, and contact with participants during the unsupervised phase of the intervention. Participant support regarding setting up the exergaming system was reported in 10 studies (50%), whereas the installation remains unknown in the other studies. Additional instructions were mentioned in 10 studies (50%), and training with the exergaming system was reported in 16 studies (80%). Contact with participants during the unsupervised phase of the intervention was most often realized via phone calls from professionals in 11 studies (55%), one of which also included contact via face-to-face and email. In two studies (10%), participants had regular physiotherapist meetings. In one study each (5%), participants were free to contact in case of technical or health issues, or were living in a nursing home. In the remaining five studies (25%), no contact with participants was mentioned regarding the unsupervised phase of the intervention. Overall, each study on unsupervised exergaming at home included some participant support mechanisms to ensure the fidelity of the intervention.Adherence was reported in 15 studies and was high  in eight studies (53%), moderate in six studies (40%), and low  in one study (7%). Twelve of these 15 studies (80%) have made use of diaries and daily play logs to assess adherence, similar to previous research  that investigated adverse outcomes found no adverse outcomes related to exergaming. The remaining four studies (29%) reported mostly mild and some moderate adverse outcomes, such as back pain or knee pain. These findings are in line with previous work that reported mild to moderate adverse events in few studies on using exergames in supervised and home environments  used Wii hardware and software, 10 of which used Wii Fit games (50%). Relatedly, several therapists found the Wii Fit to be a motivating and effective tool to complement conventional therapy, for instance, regarding weight shift and balance training  exergaming is initiated and adhered to, which also depends on whether the intervention is affordable. Concerning the largest study included in this systematic review  was investigated in at most four studies, nine pathologies were investigated by one study each, and there are other pathologies to take into account. So, the included studies can still be considered pilot work and indicate the need for further research. Moreover, it should be noted that exergaming was found to have positive effects on healthy adults, indicating the potential of exergaming for prevention of pathologies and maintenance of physical activity . Hence, our review emphasizes that the integration of unsupervised exergaming phases can be an effective and cost-efficient way compared to conventional rehabilitation and supervised exergaming. Still, supervision and participant support were realized in different ways and contexts, for instance, in a clinic , although enjoyment and fun have been discussed as integral parts in exergaming and physical activity to elicit health benefits  and MS and KK (supporting) revised the manuscript. All authors approved submission.


Food safety risk prediction is crucial for timely hazard detection and effective control. This study proposes a novel risk prediction method for food safety called TabNet-GRA, which combines a specialized deep learning architecture for tabular data (TabNet) with a grey relational analysis (GRA) to predict food safety risk. Initially, this study employed a GRA to derive comprehensive risk values from fused detection data. Subsequently, a food safety risk prediction model was constructed based on TabNet, and training was performed using the detection data as inputs and the comprehensive risk values calculated via the GRA as the expected outputs. Comparative experiments with six typical models demonstrated the superior fitting ability of the TabNet-based prediction model. Moreover, a food safety risk prediction and visualization system (FSRvis system) was designed and implemented based on TabNet-GRA to facilitate risk prediction and visual analysis. A case study in which our method was applied to a dataset of cooked meat products from a Chinese province further validated the effectiveness of the TabNet-GRA method and the FSRvis system. The method can be applied to targeted risk assessment, hazard identification, and early warning systems to strengthen decision making and safeguard public health by proactively addressing food safety risks. Food safety has emerged as a significant global public health concern in recent years, impacting people’s health and wellbeing . Within Machine learning (ML), the process through which computers learn from substantial historical data via statistical algorithms, generate empirical models, and make predictions or decisions , has emeRandom forests, clustering methods, and ensemble models have been investigated, and specific strategies, such as cross-validation, have been used to address well-known issues such as over-fitting . For insOn the other hand, artificial neural networks (ANNs) are increasingly used to solve classification and regression prediction problems due to their ability to learn more complex data patterns. For instance, neural networks such as extreme learning machines (ELMs) , radial TabNet is a highly efficient standard deep neural network architecture designed specifically for tabular data . It emplWhen developing a food safety risk prediction model, it is essential to analyze detection data and obtain comprehensive risk values in order to train the model. The analytic hierarchy process (AHP) is often employed for this purpose, but it is limited by its subjective weight-assignment method. Grey relation analysis (GRA), an important multivariate analysis method and part of grey system theory , measureVisualization techniques are widely recognized as an effective means for analyzing and interpreting data ,25. InteThe primary contributions of this work are as follows: (1) a novel risk prediction method for food safety, TabNet-GRA, which enables a rapid and precise determination of fine-grained risk values for food samples based on detection data by combining the advantages of TabNet and GRA, (2) a food safety risk prediction and visualization system, called FSRvis system, in conjunction with the TabNet-GRA method, which can facilitate food safety risk prediction and interactive visual analysis based on detection data, and (3) a case study employing detection data from cooked meat products in a Chinese province, which the results of validate the effectiveness of the TabNet-GRA method and the FSRvis system.The framework of the TabNet-GRA method and FSRvis system is illustrated in TabNet-GRA is considered a food safety risk prediction method that utilizes the combination of TabNet and GRA, which can predict the risk of food products by employing food safety detection data. In this section, the principles and construction process of TabNet-GRA will be introduced.The Pipeline of the TabNet-GRA method is illustrated in Step 1: Data processing. The food safety detection data are processed for deleting useless attributes, data format conversion, deleting redundant data and “undetected” result filling, etc., and the data are processed into a data matrix Step 2: Using GRA to calculate the comprehensive risk value of each food sample in a detection dataset. Firstly, GRA is used to calculate the weight vector Step 3: Construction and training of a TabNet-based food safety risk prediction model. The predictive model was constructed based on the TabNet. During the training process of the model, the food safety detection data matrix Grey relational analysis (GRA) is a multi-indicator decision-making evaluation method developed from the gray system theory. Its fundamental concept involves quantifying the geometric similarity between reference data sequences and multiple comparative data sequences to establish their level of association. This analytical approach enables the assessment and evaluation of correlations and influences among multiple indicators, facilitating comprehensive decision-making progress . In the In order to clearly describe the process of calculating the sample’s comprehensive risk value, the definitions of the symbols used in it are first stated. Let The process of calculating the comprehensive risk value of food samples using GRA is as follows: (1) Dimensionless data. The difference in the physical significance of each indicator results in data that are not always of similar magnitude, which does not facilitate comparisons or makes it difficult to obtain correct conclusions when making comparisons. Dimensionless data processing is required for grey relational analysis. Equation (1) is used for dimensionless processing.(2) The grey correlation coefficients of (3) The correlation coefficient between the two sequences (4) Each indicator acts as a reference sequence once, and the correlation coefficient matrix (5) Determining indicator weights. According to the correlation coefficient matrix Normalize (6) Calculation of risk values for food samples. The ratio of the detection value of the risk indicator to its limit value is used to express the risk of individual indicators on the sample, calculated by the equation TabNet is a novel high-performance standard deep learning architecture designed for tabular data; it has demonstrated remarkable performance in tasks such as the classification and regression of tabular-type data. TabNet is applied to predict food safety in this work. The architecture of the TabNet-based food safety risk prediction model is shown in Step 1: Normalization and initialization.The BN layer processes the sampling data matrix Initialize the related variables of TabNet: Step 2: Let The Mask module implements the selection of significant features, which made the model focus on the risk indicators that mainly contribute to the risk when learning, thus improving the learning efficiency of the model. The importance of the features was realized by the At module, which implements feature selection for the current decision step by learning a Mask matrix as in Equation (8).Step 3: The risk feature matrix The feature selection for the current decision step was achieved by multiplying Step 4: The significant feature Step 5: The processed risk features The processed risk features Step 6: Determine whether Step 7: TabNet draws on the idea of tree model aggregation to aggregate the output vectors After the above steps, a food safety risk prediction model based on TabNet was constructed, with the detection data matrix This work presents an analysis using the safety detection data of cooked meat products provided by the food detection department of a Chinese province in 2018 and 2019. Firstly, the raw data were processed, adhering to the principles of the comprehensiveness, scientific state, and operability of the risk evaluation indicator system [The detection data used in this work comprised 87,260 raw data records, a part of the raw data is shown in To address the issues with the data, the following processing steps were undertaken: (1) Useless attributes were eliminated, retaining only twelve relevant attributes, including nine risk indicators, sample number, limit standards, and standard detection limits. (2) Data formats were converted, and the redundant non-numerical symbols in the data were removed, e.g., “<0.005” to “0.005”. (3) Redundant data were removed, for example, if there were multiple numbers in the detection result; the maximum value was taken as its detection result. (4) “Undetected” results were addressed by filling them with half of the standard detection limit rather than assigning a value of zero. (5) Outlier detection was performed on the data to identify and exclude abnormal samples. The processed data are presented in Based on the processed cooked meat products detection data, correlation analysis was performed using the GRA method on 7885 sample data from January 2018 to November 2019 to obtain the weights of nine evaluation indicators, and the comprehensive risk values of the samples were obtained by fusing the data on the detected contents of hazards in cooked meat product samples with the indicator weights. The correlation coefficient between each risk indicator was obtained using Equations (1)–(3), and the correlation coefficient represented the correlation degree between the indicators; the larger the correlation coefficient, the greater the correlation degree between the two indicators. The correlation degree and heat map matrix between the evaluation indicators are shown in In constructing the food safety risk prediction model using the pytorch-tabnet package, 7835 samples were used as the training set for TabNet model training, and the remaining 50 samples were used as the test set; The root mean squared error (The framework of the FSRvis system developed in this work is shown in In the detection data view A in the 1) can effectively discover the distribution of different sample risks in the form of a scatter plot; the subview (2) can visually compare the risk level of adjacent or different samples in the form of a bar chart; and the subview (3) can obviously observe the trend of sample risks in the form of a line graph. For problems such as graphical overlap caused by a large number of samples, a brush tool is designed to enable the swiping of samples, which can increase the distance between markers in the view, and this tool is also applicable to views (2) and (3). For further analysis, a function for downloading risk results was designed in each subview of view (The risk prediction results view C present subview C2 can vi subview C3 can obto views C2 and (F (2) and C3. For f of view C.The sample details information view D uses a In the risk composition of the samples view F, the re in view C, here t in view G mainly First, the proposed GRA-based quantitative risk assessment method can calculate fine-grained risk values of food products in detection data, enabling a more accurate identification of food safety risks. This method calculated the correlation between each risk indicator by using the GRA approach and obtained the weight of each indicator, subsequently calculating the risk value based on the weighted sum of all indicator detections. In comparison with qualitative risk assessment methods, this quantitative approach allowed for a more precise evaluation of food risks, overcoming the limitations of subjectivity and difficulties in quantifying risks to a certain extent.Second, the proposed food safety risk prediction method, TabNet-GRA, provided a rapid and direct comprehensive risk value for food based on detection data, exhibiting a superior predictive ability when compared with typical prediction models. The TabNet-GRA method first derives the comprehensive risk value of fused detection data using GRA. It then constructs a risk prediction model based on TabNet, trained using the detection data as the input and the comprehensive risk value calculated via the GRA as the expected output. Subsequently, users can employ this trained model to directly predict the comprehensive risk value of food based on new detection data, eliminating the need for previous complex calculation processes. As a result, food safety risks can be promptly identified. Comparative experimental results demonstrated that the TabNet-based prediction model exhibits lower error rates than the current typical models, including RF, GBDT, XGBoost, BP, ELM, and RBF, showcasing its superior fitting ability and ability to predict food safety risk more accurately and efficiently.Third, the developed FSRvis system offers support for food safety risk assessment, prediction, and visual analysis in a more intuitive and effective manner. The system integrated the risk prediction model constructed based on the TabNet-GRA method and employed multi-view collaborations, providing multiple views of detection data, detection content for each risk indicator, risk prediction results, risk composition, sample detail information, etc. This approach enabled risk prediction and multi-faceted interactive visual analysis of new detection data, thereby enhancing the efficiency and accuracy of risk analysis. Food safety supervision departments can utilize this system to conduct in-depth analysis of detection data and subsequently implement targeted food safety monitoring, early warning, and control measures based on risk analysis outcomes. For example, the FSRvis system can be employed to focus on monitoring and controlling high-risk food products and safety hazards, ultimately improving the cost-efficiency of supervision efforts.In conclusion, this work addressed the critical aspect of data-driven food safety risk early warning, which was a pivotal method for ensuring effective food safety supervision. This study proposed an innovative risk prediction method for food safety, namely TabNet-GRA, which harnessed the advantages of TabNet and GRA to empower accurate and expeditious fine-grained risk prediction based on detection data. To substantiate its efficacy, this study conducted a comprehensive case study and method evaluation using a dataset comprising 87,260 original records of cooked meat products detection from a Chinese province. The comparative evaluation unequivocally demonstrated the superiority of the TabNet-based prediction model over six typical models  under equivalent conditions.Additionally, this study has implemented an intelligent visualization system named the FSRvis system which is built upon the TabNet-GRA method. This advanced system facilitated food safety risk prediction and multi-dimensional interactive visual analysis, elevating the efficiency and scope of food safety risk analysis to new heights.In future work, the intention is to explore two pivotal research directions. Firstly, the goal involves parameter optimization of the risk prediction model by employing particle swarm optimization (PSO) and Bayesian optimization techniques, aiming to further elevate the prediction accuracy. Secondly, attention will be directed towards devising an automated warning report generation method, which is capable of generating comprehensive analysis reports for users following risk analysis and prediction of detection data. These improvements will substantially amplify the practicality and real-world applicability of the TabNet-GRA method.