Children and youth who are uninsured or underinsured in Canada and the USA have limited options where they can receive healthcare. In both countries, community health centres (CHCs) have been established as a solution to provide quality care to children without adequate insurance, including those who are newcomers or refugees. However, little is known about how well these models deliver paediatric care. Cross-country analysis provides an important viewpoint to identify areas of success and growth. The purpose of this scoping review is to compare quality of care for uninsured and underinsured children through CHCs in the USA and Canada.

This scoping review follows the methodological guidelines from the Joanna Briggs Institute Evidence synthesis. The protocol has been registered with the Open Science Framework Registries and can be accessed online. A search will be conducted in electronic databases of peer-reviewed literature (Ovid MEDLINE ALL, CINAHL Complete via EbscoHost, Scopus; Health Business Elite via EbscoHost and Sociological Abstracts via ProQuest) as well as the grey literature. Two reviewers will review all titles and abstracts for inclusion in full-text review. Studies that meet inclusion criteria will be included in full-text review. Data will be extracted into Covidence, using the Donabedian model as a conceptual framework. Findings will be synthesised in a narrative format.

As this study only uses publicly available data, ethics approval is not required. Findings will be shared at national and international conferences and published in a peer-reviewed journal. In addition, findings will be prepared into a policy brief or white paper to be shared with relevant policy stakeholders to advocate for a better model of care for marginalised children and youth.

Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%–40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy.

ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs.

The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.