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Background: Controlled substances (CS) are ‘diverted’ (stolen) from healthcare facilities via many integrated and diverse mechanisms due to a lack of safeguards. There remains a gap in understanding how healthcare workers (HCWs) leverage their social networks (e.g., their role/tasks and interactions with other roles/tasks) within the medication use process (MUP) that contribute to diversion. Social network analysis (SNA) is an analytic approach used to map and analyze social connections, which can help identify influential interdependence between HCWs and tasks susceptible to drug diversion. Objectives: To map the social network structures of MUP tasks vulnerable to CS diversion in two Inpatient pharmacies and compare diversion risks by identifying influential tasks and HCWs. Methods: This was an exploratory sequential mixed methods study conducted in the Inpatient pharmacies at two large hospitals in Toronto, Canada. Initial analysis used previously collected clinical observation data to identify key pharmacy roles and tasks vulnerable to CS diversion. Subsequently, a cross-sectional survey was conducted to collect demographic information on HCWs and assess their engagement in the identified vulnerable tasks. Clinical observations and survey data were used to perform two-mode SNA to identify connections between HCWs and tasks susceptible to drug diversion. Results: The analysis identified different network structures across both sites but highlighted the importance of strategic Pharmacist or Technician Supervisor oversight to moderate-high vulnerability tasks. Pharmacy technicians were found to be the network's most central actors, while Pharmacists had a more supportive role on the network's periphery, providing oversight. Across both sites, there was strong connectivity between HCWs and tasks, indicating a higher level of security against potential undetected diversion. Conclusion: By strategically involving Pharmacists or Technician Supervisors, diversion risk can be mitigated through cross-checking and quality control. Through identifying the network structure of each unit, hospitals can identify opportunities for future interventions to prevent diversion.