Background Digital health interventions have become increasingly common across health care, both before and during the COVID-19 pandemic. Health inequalities, particularly with respect to ethnicity, may not be considered in frameworks that address the implementation of digital health interventions. We considered frameworks to include any models, theories, or taxonomies that describe or predict implementation, uptake, and use of digital health interventions. Objective We aimed to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake, and use of digital health interventions; health and ethnic inequalities; and interventions for cardiometabolic disease. Methods SCOPUS, PubMed, EMBASE, Google Scholar, and gray literature were searched to identify papers on frameworks relevant to the implementation, uptake, and use of digital health interventions; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which frameworks address health inequalities, specifically ethnic inequalities; explored how they were addressed; and developed recommendations for good practice. Results Of 58 relevant papers, 22 (38%) included frameworks that referred to health inequalities. Inequalities were conceptualized as society-level, system-level, intervention-level, and individual. Only 5 frameworks considered all levels. Three frameworks considered how digital health interventions might interact with or exacerbate existing health inequalities, and 3 considered the process of health technology implementation, uptake, and use and suggested opportunities to improve equity in digital health. When ethnicity was considered, it was often within the broader concepts of social determinants of health. Only 3 frameworks explicitly addressed ethnicity: one focused on culturally tailoring digital health interventions, and 2 were applied to management of cardiometabolic disease. Conclusions Existing frameworks evaluate implementation, uptake, and use of digital health interventions, but to consider factors related to ethnicity, it is necessary to look across frameworks. We have developed a visual guide of the key constructs across the 4 potential levels of action for digital health inequalities, which can be used to support future research and inform digital health policies.

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BACKGROUND Digital health interventions (DHIs) have become increasingly common across healthcare, both before and during the COVID-19 pandemic. Health inequalities, particularly by ethnicity, are recognised across diseases, but may be excluded in frameworks addressing implementation of DHIs. OBJECTIVE Using cardiometabolic disease as an exemplar, this scoping review aims to assess how health inequalities are addressed in frameworks relevant to the implementation, uptake and use of DHIs, health and ethnic inequalities, and interventions for cardiometabolic disease. METHODS SCOPUS, PubMed, EMBASE and grey literature was searched to identify frameworks relevant to: implementation, uptake and use of DHIs; ethnically or culturally diverse populations and health inequalities; and interventions for cardiometabolic disease. We assessed the extent to which these include health inequalities, specifically regarding ethnicity; and explored how these were addressed, drawing out recommendations for good practice. RESULTS Of 58 relevant frameworks, 22 (38%) included reference to health inequalities. Inequalities were conceptualised to operate across four levels: society, system, intervention and individual. Only five frameworks considered all levels. Three frameworks considered how DHIs might interact with or exacerbate existing health inequalities; and three considered the process of implementation, uptake and use of health technologies and suggested opportunities to improve equity in digital health. Where ethnicity was considered, this was often within the broader social determinants of health. Only three frameworks explicitly addressed ethnicity: one focused on culturally tailoring DHIs; and two were applied to management of cardiometabolic disease. CONCLUSIONS Existing frameworks evaluate implementation, uptake and use of DHIs, but to consider factors related to ethnicity necessitates looking across frameworks. We have developed a guide to support future research to assess real world usability and applicability of these frameworks, to mitigate against digital health inequalities and to inform digital health policies.