Background: Although agricultural health has gained importance, to date, much of the existing research relies on traditional epidemiological approaches that often face limitations related to sample size, geographic scope, temporal coverage, and the range of health events examined. To address these challenges, a complementary approach involves leveraging and reusing data beyond its original purpose. Administrative health databases (AHDs) are increasingly reused in population-based research and digital public health, especially for populations like farmers, who face distinct environmental risks. Objective: We aimed to explore the reuse of AHDs in addressing health issues within farming populations by summarizing the current landscape of AHD-based research and identifying key areas of interest, research gaps, and unmet needs. Methods: We conducted a scoping review and bibliometric analysis using PubMed and Web of Science. Building upon previous reviews of AHD-based public health research, we conducted a comprehensive literature search using 72 terms related to farming population and AHDs. To identify research hotspots, trends, and gaps, we used keyword frequency, co-occurrence, and thematic mapping. We also explored the bibliometric profile of the farming exposome by mapping keyword co-occurrences between environmental factors and health outcomes. Results: Between 1975 and April 2024, 296 publications across 118 journals from 34 countries were identified, predominantly from high-income countries. Nearly one-third of these publications were associated with well-established cohorts such as AGRICAN and AHS. The most frequently used AHDs included disease registers (158/296, 53.4%), electronic health/medical records (124/296, 41.9%), insurance claims (106/296, 35.8%), population registers (95/296, 32.1%), and hospital discharge (41/296, 13.9%). Most studies included only adult participants. Fifty studies involved over 1 million participants. Although a broad range of exposure proxies were used, most studies relied on broad proxies, which failed to capture the specifics of farming tasks. Research on the farming exposome remains underexplored, with a predominant focus on the specific external exposome, in particular pesticide exposure. Furthermore, a limited range of health events have been examined, primarily cancer, mortality, and injuries. Conclusions: The increasing use of AHDs holds major potential to advance public health research within farming populations. However, substantial research gaps persist, particularly in low-income regions and among underrepresented farming subgroups, such as females, children, and contingent workers. Emerging issues, including exposure to PFAS, biological agents, microbiome, microplastics, and climate change, warrant further research. Major gaps also persist in understanding various health conditions, including cardiovascular, reproductive, ocular, sleep, age-related, and autoimmune diseases. Addressing these overlooked areas is essential for a more comprehensive understanding of the health risks faced by farming communities and to guide public health policies. Within this context, promoting AHD-based research, in conjunction with other digital data sources (e.g., mHealth, social health data, wearable sensors) and artificial intelligence approaches, represents a promising avenue for future exploration.