OBJECTIVES/GOALS: Adult spinal deformity is commonly treated by spine surgeons. Patient treatment planning and surgical candidacy are dependent on static measurements and inconsistent heuristics which lead to high complication rates and poor outcomes. This study tests the role of supplemental longitudinal and dynamic patient data in improving surgical planning. METHODS/STUDY POPULATION: Ten adult spinal deformity surgeons at Johns Hopkins Hospital were interviewed for 30 minutes by the study team. The script was reviewed by the institutional review board to alleviate any risk of bias. Two patient sets were curated utilizing previously treated, anonymized patient data sets from a non-surveyed practitioner. Each patient set was coupled with relevant radiographic imaging (MRIs, CTs, and plain radiographs) and pertinent clinical information that is collected in a standard clinic visit. Surgeons were presented with a patient and asked to note their specific surgical plan. Subsequently, surgeons were presented with four sets of supplemental dynamic spine data and asked to note their surgical plan for each set. Shaprio-Wilks and Mann-Whitney U tests were used to assess data normality and nonnormality. RESULTS/ANTICIPATED RESULTS: Preliminary data has shown inconsistency in both surgical selection and surgical type amongst physicians when presented with initial clinical findings and radiographic reports for base patient cases. There was minimal consensus among surgeons on the number of levels fused and interbody spacer usage. Early results show that dynamic spine data may be beneficial in creating consistency between surgeons, despite inter-surgeon variability in surgical planning without this data. Posture, pain location, pain severity, and quantified activity throughout the day have been referenced as the most useful dynamic spine data to consider. Amongst all providers, the availability of dynamic spine data resulted in a change in surgical planning. DISCUSSION/SIGNIFICANCE: Recent publications have shown that spine surgery patient candidacy and surgical planning are dependent on heuristics. This has led to inconsistencies amongst surgeon preferences and increases in improper patient selection for procedures. Incorporating longitudinal dynamic data may lead to increased consistency and improved patient outcomes.