Ramasawmy Mel, Poole Lydia, Thorlu-Bangura Zareen, Chauhan Aneesha, Murali Mayur, Jagpal Parbir, Bijral Mehar, Prashar Jai, G-Medhin Abigail, Murray Elizabeth, Stevenson Fiona, Blandford Ann, Potts Henry W W, Khunti Kamlesh, Hanif Wasim, Gill Paramjit, Sajid Madiha, Patel Kiran, Sood Harpreet, Bhala Neeraj, Modha Shivali, Mistry Manoj, Patel Vinod, Ali Sarah N, Ala Aftab, Banerjee Amitava
Institute of Health Informatics, University College London, London, United Kingdom.
Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, United Kingdom.
JMIR Cardio. 2022 Aug 11;6(2):e37360. doi: 10.2196/37360.
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.
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.
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.
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.
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.
在新冠疫情之前及期间，数字健康干预措施在医疗保健领域已变得越来越普遍。在涉及数字健康干预措施实施的框架中，可能未考虑健康不平等问题，尤其是种族方面的不平等。我们所指的框架包括任何描述或预测数字健康干预措施的实施、采用和使用情况的模型、理论或分类法。
我们旨在评估在与数字健康干预措施的实施、采用和使用相关的框架中，健康不平等问题是如何得到解决的；评估健康和种族不平等情况；以及评估针对心脏代谢疾病的干预措施。
我们检索了Scopus、PubMed、EMBASE、谷歌学术以及灰色文献，以识别与数字健康干预措施的实施、采用和使用相关的框架；种族或文化多元人群与健康不平等；以及针对心脏代谢疾病的干预措施的论文。我们评估了各框架解决健康不平等问题（特别是种族不平等问题）的程度；探究了这些问题是如何得到解决的；并制定了良好实践建议。
在58篇相关论文中，22篇（38%）包含提及健康不平等的框架。不平等被概念化为社会层面、系统层面、干预层面和个体层面。只有5个框架考虑了所有层面。3个框架考虑了数字健康干预措施如何与现有健康不平等相互作用或加剧现有健康不平等，3个框架考虑了健康技术的实施、采用和使用过程，并提出了改善数字健康公平性的机会。当考虑种族因素时，通常是在更广泛的健康社会决定因素概念范围内。只有3个框架明确涉及种族问题：一个专注于对数字健康干预措施进行文化层面的调整，另外两个应用于心脏代谢疾病的管理。
现有框架评估数字健康干预措施的实施、采用和使用情况，但要考虑与种族相关的因素，有必要综合多个框架进行考量。我们已针对数字健康不平等问题在4个潜在行动层面的关键构建要素制定了一份可视化指南，可用于支持未来研究并为数字健康政策提供参考。
