Learning as a missing component of digital health, environment and climate change

Abstract

Despite its rapid advancement, digital health has little considered issues of climate change or environmental degradation. As the digital health community begin to engage with this critical issue scholars have started mapping progression in the field, typically focusing on the relationship between digital health as it applies to climate and/or environmental mitigation or climate adaptation. In this Comment, we argue that climate and environment learning for mitigation and adaptation constitutes a critical yet overlooked dimension intersecting mitigation and adaptation strategies, warranting deliberate attention. This learning category is the systematic and transparent approach that applies structured and replicable methods to identify, appraise, and make use of evidence from data analytics across decision-making processes related to mitigation and adaptation, including for implementation, and informs the exchange of new best practices in a post-climate era. The WHO’s Digital Health Classification framework offers a good option for ultimately formalising learning into practice. As a foundational step, however, learning needs to be conceptualised and developed into its own research agenda, organised around a shared language of metrics and evidence. We call on actors in the digital health field to develop this concrete strategy and initiate this process.

Fig. 1. Schematic to represent how climate/environment learning intersects climate adaptation and climate mitigation.

Climate/environment learning intersects both climate/environment adaptation and mitigation. Climate/environment adaptation and mitigation can have co-benefits, for example, telemedicine can improve healthcare adaptation and decrease transport emissions associated with healthcare appointments.