Integrating neighbourhood geo-referenced contexts to support personalized behavioural interventions using FHIR and Wikidata

Behavioral interventions play a key role in preventing and managing noncommunicable diseases (NCDs), which account for 70% of global deaths annually. However, adherence to such interventions remains low. Their effectiveness can be enhanced through personalization by considering individuals’ neighbourhood geo-referenced contexts (NGRCs), as behavioral change theories and time geography highlight the influence of physical and social environments on health behaviors. NGRCs refer to contextual physical and social attributes (“C”) within neighbourhoods (“N”) surrounding an individual’s geographic positions (“GR”), such as home addresses or daily travel routes. For example, the number of dwellings (“C”) within the neighbourhood (“N”) of an individual’s home address (“GR”) represents an NGRC. Despite their potential, current information infrastructures remain fragmented, with NGRC datasets distributed across multiple sources and lacking standardized integration. To address this challenge, this poster explores how NGRCs can be integrated into shared decision-making for behavioral interventions. We illustrate this through a use case of personalized NGRC-focused walking interventions in the Netherlands. The intervention is developed based on patients’ preferences, such as preferred walking environments (e.g., street environments or natural spaces) and their perceived neighbourhoods. Relevant NGRCs are extracted from publicly available data sources and standardized using Wikidata and FHIR to support personalized walking interventions, enabling their use in patient apps and clinical decision-support systems within health information infrastructures.