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ObjectivesExcessive opioid prescribing is a contributing factor to the opioid epidemic in the USA. We aimed to develop, implement and evaluate the usability of a clinical decision-making mobile application (app) for opioid prescription after surgery.MethodsWe developed two clinical decision trees, one for opioid prescription after adult laparoscopic cholecystectomy and one for posterior spinal fusion surgery in adolescents. We developed a mobile app incorporating the two algorithms with embedded clinical decision-making, which was tested by opioid prescribers. A survey collected prescription intention prior to app use and participants’ evaluation. Participants included opioid prescribers for patients undergoing (1) laparoscopic cholecystectomy in adults or (2) posterior spinal fusion in adolescents with idiopathic scoliosis.ResultsEighteen healthcare providers were included in this study (General Surgery: 8, Paediatrics: 10). Intended opioid prescription before app use varied between departments (General Surgery: 0–10 pills (mean=5.9); Paediatrics: 6–30 pills (mean=20.8)). Intention to continue using the app after using the app multiple times varied between departments (General Surgery: N=3/8; Paediatrics: N=7/10). The most reported reason for not using the app is lack of time.ConclusionsIn this project evaluating the development and implementation of an app for opioid prescription after two common surgeries with different prescription patterns, the surgical procedure with higher intended and variable opioid prescription (adolescent posterior spinal fusion surgery) was associated with participants more willing to use the app. Future iterations of this opioid prescribing intervention should target surgical procedures with high variability in both patients’ opioid use and providers’ prescription patterns.