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The sampling population is volunteer-based and is not representative of the UK population.1 Investigators state that although the estimates of prevalence and incidence should be interpreted with caution, valid measures of association and estimates of causal effect can be more readily interpreted as they do “not require participants to be representative of the population at large”.2 This statement is a puzzling claim: sample selection can indeed influence measures of association. Specifically, whether or not an association observed in a study is similar in some other target population (ie, has external validity) depends on a number of factors, including the distribution of effect measure modifiers of the exposure–outcome relationship in the study sample and target population.3 Critically, a study can have restricted external validity even when it has internal validity, which might occur in a randomised trial.4 Thus, researchers should not be quick to set aside issues of representativeness in interpreting UK Biobank results. [...]larger sample size in a skewed sample only leads to confidence in answers that might not apply to the target population. [...]it is paramount that external validity be taken more seriously in the UK Biobank and other large data resources.

Internet access is not only expected by patients but also essential to shared decision making and better outcomes, says Victoria Betton. But Grant Ingrams thinks widespread deployment of wi-fi is a luxury that mustn’t take priority over other technological needs

Background To address the shortage of health information personnel within Botswana, an innovative human resources approach was taken. University graduates without training or experience in health information or health sciences were hired and provided with on-the-job training and mentoring to create a new cadre of health worker: the district Monitoring and Evaluation (M&E) Officer. This article describes the early outcomes, achievements, and challenges from this initiative. Methods Data were collected from the district M&E Officers over a 2-year period and included a skills assessment at baseline and 12 months, pre- and post-training tests, interviews during stakeholder site visits, a survey of achievements, focus group discussions, and an attrition assessment. Results An average of 2.7 mentoring visits were conducted for M&E Officers in each district. There were five training sessions over 18 months. Knowledge scores significantly increased ( p < 0.05) during the three trainings in which pre/post tests were administered. Over 1 year, there were significant improvements ( p < 0.05) in self-rated skills related to computer literacy, checking data validity, implementing data quality procedures, using data to support program planning, proposing indicators, and writing M&E reports. Out of the 34 district M&E Officers interviewed during site visits, most were conducting facility visits to review data (27/34; 79%), comparing data sets over time (31/34; 91%), backing up data (32/34; 94%), and analyzing data (32/34; 94%). Common challenges included late facility reports (28/34; 82%), lack of transportation (22/34; 65%), inaccurate facility reports (10/34; 29%), and colleagues’ misunderstanding of M&E (10/34; 29%). Six posts were vacated in the first year (6/51; 12%). A total of 49 Officers completed the achievements survey; of these, common accomplishments related to improvements in data management (35/49; 71%), data quality (31/49; 63%), data use (29/49; 59%), and capacity development (26/49; 53%). Conclusions The development of a cadre of district M&E Officers has contributed positively to the health information system in Botswana. In the absence of tertiary training related to health information, on-the-job training and mentoring of university graduates can be an effective approach for developing a new professional cadre of M&E expertise and for strengthening capacity within a national health system.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin – the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as ‘revolutionary’ and ‘disruptive’, is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is ‘fit-for-purpose’ is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

Background Climate change is a major global threat to human health and puts tremendous pressure on health systems. Therefore, a resilient health system is crucial to enhance, maintain, and restore the population’s health. This study aimed to identify interventions and actions to strengthen a climate-resilient health system to deal with the adverse health effects of climate change. Method This study was a scoping review. Five databases and Google Scholar search engine were searched using relevant keywords. Initially, 4945 documents were identified, and 105 were included in the review. Content thematic analysis method was applied using MAXQDA 10 software. Results Overall, 87 actions were identified for building a climate-resilient health system and were classified into six themes (i.e., governance and leadership; financing; health workforce; essential medical products and technologies; health information systems; and service delivery). The most commonly reported actions were formulating a national health and climate change adaptation plan, developing plans for essential services (electricity, heating, cooling, ventilation, and water supply), assessing the vulnerabilities and capacities of the health system, and enhancing surveillance systems targeting climate-sensitive diseases and their risk sources. Conclusions A holistic and systemic approach is needed to build a climate-resilient health system owing to its complex adaptive nature. Strong governance and leadership, raising public awareness, strategic resource allocation, climate change mitigation, emergency preparedness, robust health services delivery, and supporting research, are essential to building a climate-resilient health system.

Artificial intelligence (AI) and blockchain are the two disruptive technologies emerging from the Fourth Industrial Revolution (IR4.0) that have introduced radical shifts in the industry. The amalgamation of AI and blockchain holds tremendous potential to create new business models enabled through digitalization. Although research on the application and convergence of AI and blockchain exists, our understanding of the utility of its integration for business remains fragmented. To address this gap, this study aims to characterize the applications and benefits of integrated AI and blockchain platforms across different verticals of business. Using bibliometric analysis, this study reveals the most influential articles on the subject based on their publications, citations, and importance in the intellectual network. Using content analysis, this study sheds light on the subject’s intellectual structure, which is underpinned by four major thematic clusters focusing on supply chains, healthcare, secure transactions, and finance and accounting. The study concludes with 10 application areas in business that can benefit from these technologies.

PurposeThe increasing rate of environmental concern and awareness by society has attracted attention from researchers and organisations to consider how to proceed towards green supply chains. The purpose of this paper is to identify operational bottlenecks in the multi-tier supply chain to guide organisations towards where to concentrate their efforts to address their supply chain environmental challenges.Design/methodology/approachThis paper presents a literature review identifying green supply chain challenges of multi-tier supply chains. Following the literature review is a case study of the Ethiopian health supply chain with 11 interviews, 11 international and 6 national surveys and data from public health information systems. An analysis based on multi-tier supply chain modelling is used to identify environmental supply chain bottlenecks.FindingsThis research found that the supply chain actors face severe challenges towards enhanced green supply chain performance mainly because of poor inventory management (IN), inefficient tracking and tracing (TR) and fake or sub-standard products in the supply chain, especially counterfeit medicines (CO). Specific environmental bottlenecks within each of the challenge areas IN, TR and CO where identified serving as recommendations for where supply chain actors should focus their work towards greener supply chains.Research limitations/implicationsThe data come from participants in a single country, Ethiopia; although the supply chain challenges are common for developing countries in general.Practical implicationsThis research presents a modelling approach to identify supply chain activities considered as environmental bottlenecks in multi-tier supply chains. The environmental bottlenecks pinpoint supply chain activities to focus on for a transition towards green supply chains for manufacturers, public and private health organisations, hospitals and health care units.Originality/valueThis paper contributes to the literature on GSCM by developing a multi-tier modelling approach for identifying environmental supply chain bottlenecks. The applicability of the model is demonstrated by the identification of environmental bottlenecks in a healthcare supply chain supporting decisions on what challenges a green supply chain strategy should address. It serves as a basis for future research on where to implement GSCM practices in supply chains (SCs).

Industry 4.0 has been provided for the last 10 years to benefit the industry and the shortcomings; finally, the time for industry 5.0 has arrived. Smart factories are increasing the business productivity; therefore, industry 4.0 has limitations. In this paper, there is a discussion of the industry 5.0 opportunities as well as limitations and the future research prospects. Industry 5.0 is changing paradigm and brings the resolution since it will decrease emphasis on the technology and assume that the potential for progress is based on collaboration among the humans and machines. The industrial revolution is improving customer satisfaction by utilizing personalized products. In modern business with the paid technological developments, industry 5.0 is required for gaining competitive advantages as well as economic growth for the factory. The paper is aimed to analyze the potential applications of industry 5.0. At first, there is a discussion of the definitions of industry 5.0 and advanced technologies required in this industry revolution. There is also discussion of the applications enabled in industry 5.0 like healthcare, supply chain, production in manufacturing, cloud manufacturing, etc. The technologies discussed in this paper are big data analytics, Internet of Things, collaborative robots, Blockchain, digital twins and future 6G systems. The study also included difficulties and issues examined in this paper head to comprehend the issues caused by organizations among the robots and people in the assembly line.

Although most digital twin (DT) applications for health care have emerged in precision medicine, DTs can potentially support the overall health care process. DTs (twinned systems, processes, and products) can be used to optimize flows, improve performance, improve health outcomes, and improve the experiences of patients, doctors, and other stakeholders with minimal risk. This paper aims to review applications of DT systems, products, and processes as well as analyze the potential of these applications for improving health care management and the challenges associated with this emerging technology. We performed a rapid review of the literature and reported available studies on DTs and their applications in health care management. We searched 5 databases for studies published between January 2002 and January 2022 and included peer-reviewed studies written in English. We excluded studies reporting DT usage to support health care practice (organ transplant, precision medicine, etc). Studies were analyzed based on their contribution toward DT technology to improve user experience in health care from human factors and systems engineering perspectives, accounting for the type of impact (product, process, or performance/system level). Challenges related to the adoption of DTs were also summarized. The DT-related studies aimed at managing health care systems have been growing over time from 0 studies in 2002 to 17 in 2022, with 7 published in 2021 (N=17 studies). The findings reported on applications categorized by DT type (system: n=8; process: n=5; product: n=4) and their contributions or functions. We identified 4 main functions of DTs in health care management including safety management (n=3), information management (n=2), health management and well-being promotion (n=3), and operational control (n=9). DTs used in health care systems management have the potential to avoid unintended or unexpected harm to people during the provision of health care processes. They also can help identify crisis-related threats to a system and control the impacts. In addition, DTs ensure privacy, security, and real-time information access to all stakeholders. Furthermore, they are beneficial in empowering self-care abilities by enabling health management practices and providing high system efficiency levels by ensuring that health care facilities run smoothly and offer high-quality care to every patient. The use of DTs for health care systems management is an emerging topic. This can be seen in the limited literature supporting this technology. However, DTs are increasingly being used to ensure patient safety and well-being in an organized system. Thus, further studies aiming to address the challenges of health care systems challenges and improve their performance should investigate the potential of DT technology. In addition, such technologies should embed human factors and ergonomics principles to ensure better design and more successful impact on patient and doctor experiences.

•Digital supply chain information system linked to immunization registry, serves 6M.•Digital system includes stock notifications, dashboards and peer networks.•Overall stockout rate significantly lower with digital system vs. legacy system.•More time with digital system increases odds of vaccine availability. Since 2016, the Government of Tanzania has been implementing TImR, an integrated Electronic Immunization registry-logistics management information system (EIR-LMIS) that includes stock notifications. The objective of this study is to estimate the impact of this intervention on vaccine availability. Monthly stock-out data were collected from paper registers at facilities, an Excel-based system at districts, and the new system (TImR) across all 924 health facilities in Arusha, Tanga and Kilimanjaro Regions. Six months of stockout rates pre- and post-introduction, by antigen, were compared via a two-way analysis of variance (ANOVA). A mixed-effects logistic regression model with the TImR data identified predictors of vaccine availability across antigens. Post-introduction, ANOVA models estimated that overall stock-out rates declined from a monthly average of 7.1% to 2.1% (p < 0.01). Three specific vaccines had fewer stock-outs; OPV’s monthly average dropped from 12.5% to 2.1% (p < 0.01), MR from 9.4% to 1.0% (p < 0.01) and DTP-HepB-HiB from 8.1% to 1.7% (p < 0.01). In the mixed-effects logistic regression model, controlling for antigen, odds of stock-out were 4.1% (95% CI: 3.3 – 4.9) lower for each week of tenure. Compared to DTP-HepB-HiB vaccine, odds of BCG vaccine being stocked out were 4.31 as high (95% CI: 3.1 – 5.0). The odds of being stocked-out were 29.7% lower for PCV (95% CI: 8.8 – 45.8) and 26.6% (95% CI: 3.4 – 44.1) lower for rotavirus vaccines compared to DTP-HepB-HiB. The odds of stock out were 37.7% lower for MR vaccine than DTP-HepB-HiB (95% CI: 18.1 – 52.6). Tanzania’s integrated EIR-eLMIS may increase vaccine availability compared to its paper and Excel based system. Post-introduction of an eLMIS, the odds of a vaccine stock-out reduced over time. Further research could determine the impact of this intervention on vaccine wastage and replenishment response times.