<p>Frailty and multimorbidity are critical concepts in healthcare, reflecting the vulnerability of individuals to adverse outcomes. In this work, we aim to explore the associations among diseases, multimorbidity, and frailty-related outcomes, including death, disability, hospitalization, femur fracture, and emergency room visits with high priority. To this end, we use a network-based analytical framework that allows us to describe and characterize the structure of disease interconnections and to examine how this structure relates to subsequent health outcomes. Moreover, building on this analysis, we develop a novel network-based indicator of frailty-related vulnerability at the individual level, defined through proximity to the death node within the estimated disease network. We analyze anonymized administrative healthcare data from 213,689 individuals aged 65 or older in the province of Padova, Italy. Using chain graphical models, we model conditional dependencies among 19 dichotomous variables grouped into four temporal blocks: demographics, diseases (2016–2017), adverse outcomes (2018), and death (2018). The proposed frailty measure, which integrates diseases and adverse outcomes, effectively captures vulnerability. It achieved a high predictive accuracy with an area under the curve of 0.91 (95% CI: 0.906–0.916), supporting its potential as a practical tool for identifying at-risk older adults using administrative data.</p>