Purpose
Properly functioning health systems globally require medical devices and equipment for vital care. Despite promising innovations, many medical devices face adoption barriers such as regulatory issues, interoperability and data exchange challenges. In low-resource settings, contextual factors influencing adoption and diffusion have not been synthesized into an overview to guide future medical device and equipment suppliers. Our study provides a scientific inventory of frameworks, theories, models, and guidelines describing the adoption and diffusion of medical devices and equipment in low-resource settings.

Methods
We searched both the PubMed and Scopus databases to identify studies within the health and broader non-health domains. Our search yielded 2.124 results after de-duplication. Extended attributes on the type of the paper, adoption and diffusion focus, medical devices and equipment use cases, and country settings revealed patterns of underpinning and emerging frameworks for adoption and diffusion.

Results
We included 28 studies in our review. The most researched device types were telemedicine, telehealth, m-health, and e-health. Among a larger variety, the most utilized underpinning frameworks were the Diffusion of Innovation Framework, and the Technology Acceptance Model. These frameworks led to the development of emerging models, such as a modified version based on Kifle’s Adoption Model or the Intervention-Context-Actors-Mechanism-Outcome Model.

Conclusions
Our findings offer initial insights for further research in identifying mechanisms for improving access to and utilization of medical devices and equipment in low-resource settings. Researchers can use this comprehensive review to guide continued research, addressing gaps in theoretical understanding and empirical evidence on medical device adoption and diffusion in low-resource settings.

Purpose (stating the main purposes and research question): Anthropogenic resource use contributes to pollution, violent conflict over scarce resources, loss of biodiversity, and diminished quality of life for humans. Moreover, the “safe” amount of carbon dioxide—350 parts per million—has been exceeded. The health care industry is responsible for 4–5% of total world emissions,[i] which is similar to the global food sector.[ii] Health care carbon emissions come from health care infrastructures, supply chains and health care delivery. Increasingly, health care delivery is reliant on technologies which require the use of artificial intelligence to provide supportive care, such as triage algorithms, electronic patient records, and robotics.[iii] While these technological innovations have advanced health care significantly, they also contribute to the negative effects on the environment, among others, through carbon emissions. The environmental impacts of artificial intelligence (AI) in health care—in particular—are understudied. This research seeks to fill this gap. Methods: Our team ran an exploratory search in Scopus and PubMed to identify studies that integrate environmental sustainability, artificial intelligence, and health. Results: Our research initially yielded 735 studies. 77 of these studies focused on an environmental concern of a health technology or AI-application in a health care setting, but most of the articles in this subset addressed lowering energy consumption of a specific technology, such as a sensor or monitoring technology. Conclusions: While there have been studies looking at AI in health care; sustainability in AI; and sustainability in health care, little attention has been paid to the interface between all three. [i] Karliner, J., Slotterback, S., Boyd, R., Ashby, B., & Steele, K. 2019. Health Care’s Climate Footprint: How the Health Sector Contributes to the Global Climate Crisis and Opportunities for Action Healthcare Without HarmARUP; September. [ii] Pichler, P. P., Jaccard, I. S., Weisz, U., & Weisz, H. 2019 International Comparison of Health Care Carbon Footprints, Environmental Research Letters 14, no. 6: 064004. [iii] Khaliq, Abdul, Ali Waqas, Qasim Ali Nisar, Shahbaz Haider, and Zunaina Asghar. 2022. Application of AI and robotics in hospitality sector: A resource gain and resource loss perspective. Technology in Society 68: 101807.

Background: Health systems worldwide struggled to obtain sufficient personal protective equipment (PPE) and ventilators during the COVID-19 pandemic due to global supply chain disruptions. Our study’s aim was to create a proof-of-concept model that would simulate the effects of supply strategies under various scenarios, to ultimately help decision-makers decide on alternative supply strategies for future similar health system related crises. Methods: We developed a system dynamics model that linked a disease transmission model structure (susceptible, exposed, infectious, recovered (SEIR)) with a model for the availability of critical supplies in hospitals; thereby connecting care demand (patients’ critical care in hospitals), with care supply (available critical equipment and supplies). To inform the model structure, we used data on critical decisions and events taking place surrounding purchase, supply, and availability of PPE and ventilators during the first phase of the COVID-19 pandemic within the English national health system. We used exploratory modelling and analysis to assess the effects of uncertainties on different supply strategies in the English health system under different scenarios. Strategies analysed were: (i) purchasing from the world market or (ii) through direct tender, (iii) stockpiling, (iv) domestic production, (v) supporting innovative supply strategies, or (vi) loaning ventilators from the private sector. Results: We found through our exploratory analysis that a long-lasting shortage in PPE and ventilators is likely to be apparent in various scenarios. When considering the worst-case scenario, our proof-of-concept model shows that purchasing PPE and ventilators from the world market or through direct tender have the greatest influence on reducing supply shortages, compared to producing domestically or through supporting innovative supply strategies. However, these supply strategies are affected most by delays in their shipment time or set-up. Conclusion: We demonstrated that using a system dynamics and exploratory modelling approach can be helpful in identifying the purchasing and supply chain strategies that contribute to the preparedness and responsiveness of health systems during crises. Our results suggest that to improve health systems’ resilience during pandemics or similar resource-constrained situations, purchasing and supply chain decision-makers can develop crisis frameworks that propose a plan of action and consequently accelerate and improve procurement processes and other governance processes during health-related crises; implement diverse supplier frameworks; and (re)consider stockpiling. This proof-of-concept model demonstrates the importance of including critical supply chain strategies as part of the preparedness and response activities to contribute to health system resilience.

Despite its fundamental role in diagnostic and curative care, radiology has been described as a neglected essential service in many low and middle-income countries (LMICs). Previous studies have demonstrated basic equipment and infrastructure shortages in LMIC settings, but no studies to date have gone further in understanding the perceptions and experiences of staff delivering radiology services, as a way of identifying their perspectives on barriers and facilitators for delivering services, and the potential for where improvements can be made. Our qualitative study aimed to: (a) identify barriers for delivering radiology services, and (b) suggest potential facilitators for improvement of radiology service delivery in the Zimbabwean context; from the perspective of radiology staff. We conducted semi-structured interviews (n = 13) and three focus groups (n = 24 radiographers), followed by four half- to full- days of field observations to validate insights from the interviews and focus groups in all three public hospitals and one private hospital in the Harare metropolitan area. Our study identified four main barriers for delivering radiology services: (i) poor basic infrastructure, equipment, and consumables; (ii) suboptimal equipment maintenance; (iii) shortage of radiology staff and skills development; and (iv) lack of wider integration and support for radiology services. We also identified a strong sense of motivation among staff to keep radiology services, pointing to what may be an enabler and facilitator for improving radiology services. These findings point to potential risks to patient safety and quality of delivering radiology services. More importantly, we found a strong sense of personal motivation displayed by the staff, suggesting there is the potential to maintain and improve existing practices, but this would require investments to train and remunerate more radiology staff, as well as investing in continuing professional development.

BACKGROUND: Prompted by recent shocks and stresses to health systems globally, various studies have emerged on health system resilience. Our aim is to describe how health system resilience is operationalised within empirical studies and previous reviews. We compare these to the core conceptualisations and characteristics of resilience in a broader set of domains (specifically, engineering, socio-ecological, organisational and community resilience concepts), and trace the different schools, concepts and applications of resilience across the health literature. METHODS: We searched the Pubmed database for concepts related to 'resilience' and 'health systems'. Two separate analyses were conducted for included studies: a total of n = 87 empirical studies on health system resilience were characterised according to part of health systems covered, type of threat, resilience phase, resilience paradigm, and approaches to building resilience; and a total of n = 30 reviews received full-text review and characterised according to type of review, resilience concepts identified in the review, and theoretical framework or underlying resilience conceptualisation. RESULTS: The intersection of health and resilience clearly has gained importance in the academic discourse with most papers published since 2018 in a variety of journals and in response to external threats, or in reference to more frequent hospital crisis management. Most studies focus on either resilience of health systems generally (and thereby responding to an external shock or stress), or on resilience within hospitals (and thereby to regular shocks and operations). Less attention has been given to community-based and primary care, whether formal or informal. While most publications do not make the research paradigm explicit, 'resilience engineering' is the most prominent one, followed by 'community resilience' and 'organisational resilience'. The social-ecological systems roots of resilience find the least application, confirming our findings of the limited application of the concept of transformation in the health resilience literature. CONCLUSIONS: Our review shows that the field is fragmented, especially in the use of resilience paradigms and approaches from non-health resilience domains, and the health system settings in which these are used. This fragmentation and siloed approach can be problematic given the connections within and between the complex and adaptive health systems, ranging from community actors to local, regional, or national public health organisations to secondary care. Without a comprehensive definition and framework that captures these interdependencies, operationalising, measuring and improving resilience remains challenging.

Objectives To systematically review academic literature for studies on any processes, procedures, methods or approaches to purchasing high-cost medical devices and equipment within hospitals in high-income countries. Methods On 13 August 2020, we searched the following from inception: Cost-Effectiveness Analysis Registry, EconLit and ProQuest Dissertations & Theses A&I via ProQuest, Embase, MEDLINE, and MEDLINE in Process via Ovid SP, Google and Google Scholar, Health Management and Policy Database via Ovid SP, IEEE Xplore Digital Library, International HTA Database, NHS EED via CRD Web, Science Citation Index-Expanded, Conference Proceedings Citation Index-Science, and Emerging Sources Citation Index via Web of Science, Scopus, and Zetoc conference search. Studies were included if they described the approach to purchasing (also known as procurement or acquisition) of high-cost medical devices and/or equipment conducted within hospitals in high-income countries between 2000 and 2020. Studies were screened, data extracted and results summarised in tables under themes identified. Results Of 9437 records, 24 were included, based in 12 different countries and covering equipment types including surgical robots, medical imaging equipment, defibrillators and orthopaedic implants. We found heterogeneity in methods and approaches; including descriptions of processes taking place within or across hospitals (n=14), out of which three reported cost savings; empirical studies in which hospital records or participant data were analysed (n=8), and evaluations or pilots of proposed purchasing processes (n=2). Studies emphasise the importance of balancing technical, financial, safety and clinical requirements for device selection through multidisciplinary involvement (especially clinical engineers and clinicians) in decision-making, and the potential of increasing evidence-based purchasing decisions using approaches such as hospital-based health technology assessments, ergonomics and device 'user trials'. Conclusions We highlight the need for more empirical work that evaluates purchasing approaches or interventions, and greater specificity in study reporting (eg, equipment type, evaluation outcomes) to build the evidence base required to influence policy and practice for medical equipment purchasing. Protocol registration This review was registered in Open Science Framework: Shokraneh F, Hinrichs-Krapels S, Chalkidou A et al. Purchasing high-cost medical equipment in hospitals in OECD countries: A systematic review. Open Science Framework 2021; doi:10.17605/OSF.IO/GTXN8. Available at: https://osf.io/gtxn8/ (accessed 12 February 2022).

Implementation research is a multidisciplinary field that addresses the complex phenomenon of how context influences our ability to deliver evidence-informed healthcare. There is increasing realisation of the importance of applying robust implementation research to scale-up life-saving interventions that meet health-related sustainable development goals. However, the lack of high-quality implementation research is impeding our ability to meet these targets, globally. Within implementation research, theory refers to the proposed hypothesis and/or explanation of how an intervention is expected to interact with the local context and actors to bring about change. Although there is increasing interest in applying theory to understand how and why implementation programmes work in real-world settings, global health actors still tend to favour impact evaluations conducted in controlled environments. This may, in part, be due to the relative novelty as well as methodological complexity of implementation research and the need to draw on divergent disciplines, including epidemiology, implementation science and social sciences. Because of this, implementation research is faced with a particular set of challenges about how to reconcile different ways of thinking and constructing knowledge about healthcare interventions. To help translate some of the ambiguity surrounding how divergent theoretical approaches and methods contribute to implementation research, we draw on our multidisciplinary expertise in the field, particularly in global health. We offer an overview of the different theoretical approaches and describe how they are applied to continuously select, monitor and evaluate implementation strategies throughout the different phases of implementation research. In doing so, we offer a relatively brief, user-focused guide to help global health actors implement and report on evaluation of evidence-based and scalable interventions, programmes and practices.

Objectives ASSET (Health System Strengthening in sub-Saharan Africa) is a health system strengthening (HSS) programme involving eight work-packages (ie, a research study that addresses a specific need for HSS) that aims to develop solutions that support high-quality care. Here we present the protocol for the implementation science (IS) theme within ASSET (ASSET-ImplmentER) that aims to understand what HSS interventions work, for whom and how, and how IS methodologies can be adapted to improve the HSS interventions within resource-poor contexts. Settings Publicly funded health facilities in rural and urban areas in in Ethiopia, South Africa, Sierra Leone, and Zimbabwe. Participants Research staff including principal investigators, coinvestigators, field staff, PhD students, and research assistants. Interventions Work-packages use a mixed-methods effectiveness-effectiveness hybrid designs. At the end of the pre-implementation phase, a workshop is held whereby the IS theme, jointly with ASSET work-packages apply IS determinant frameworks to research findings to identify factors that influence the effectiveness of delivering evidence-informed care. Determinants are used to select a set of HSS interventions for further evaluation, where work-packages also theorise selective mechanisms. In the piloting and rolling implementation phase, work-packages pilot the HSS interventions. An iterative process then begins involving evaluation, reflection and adaptation. Throughout this phase, IS determinant frameworks are applied to monitor and identify barriers/enablers to implementation. Selective mechanisms of action are also investigated. Implementation outcomes are evaluated using qualitative and quantitative methods. The psychometric properties of outcome measures including acceptability, appropriateness and feasibility are also evaluated. In a final workshop, work-packages come together, to reflect and explore the utility of the selected IS methods and provide suggestions for future use. Structured templates are used to organise and analyse common and heterogeneous patterns across work-packages. Qualitative data are analysed using thematic analysis and quantitative data are analysed using means and proportions. Conclusions We use a novel combination of IS methods at a programmatic level to facilitate comparisons of determinants and mechanisms that influence the effectiveness of HSS interventions in achieving implementation outcomes across different contexts. The study also contributes conceptual development and clarification at the underdeveloped interface of IS, HSS and global health. The ASSET-ImplementER theme is considered minimal risk as we only interview researchers involved in the different work-packages. To this effect we have received approval from King's College London Ethics Committee for research that is considered minimal risk (Reference number: MRA-20/21-21772).

The purchaser–provider co-operation model is a way of increasing efficiency and quality in healthcare services. Risks associated with this model, including goal misalignment and information asymmetry, are managed through control mechanisms. Based on data from 12 clinical commissioning groups (purchasers of cancer care) in the English National Health Service, this paper describes the control mechanisms used to facilitate purchaser–provider co-operation and identifies good practices in using different control mechanisms. Effective control mechanisms were found to include stakeholder involvement (social control); co-operation and partnerships with providers (process control); and monitoring and service outcome measures for provider (outcome control). The paper fills an important gap in the literature—little scholarly attention has to date been paid about how purchaser and provider relationships are managed ex post and how performance is affected.