59 Background: The development of “big data” methods offers an opportunity to more precisely predict patient outcomes. We explored physicians, patients, and caregivers’ perspectives about the use of predictive models in oncology practice. Methods: We conducted 12 patient, 12 provider, and 12 caregiver interviews (N = 36) from Stanford University outpatient oncology clinics. We queried participants about patient and family-centered applications of predictive models for prognosis, cost, and novel patient and family-centered outcomes. Two trained coders iteratively examined transcripts for consistent topics and used the constant comparative methods to establish themes and sub-themes. Results: Several overlapping themes emerged: 1) Outcomes of Interest, [provider] “Predictive information about side effects or adverse effects of treatment would be helpful”: 2) Barriers to Using Predictions, [patient] “If it seems too sort of set in stone, without…you know, everything has grey areas”; 3) Benefits to Using Predictions, [provider] “Some people…their cancer may be cured, but they live with these really horrible chronic illnesses and some people would say, ‘I would have rather have just died from my disease than be in this shape’; and 4) Communication Strategy, [provider] “I’m not even sure if I would bring up the models…I would kind of fall back on what I normally discuss with patients”. A theme specific to the provider group was 5) Accuracy of Model Information, [provider] “It’s hard to know whether to use in the clinical setting just the results of the model or whether you would really want to go down to the root level and actually access the raw data”. A theme specific to the patient and caregiver groups was 6) Privacy, [caregiver] “I would want to be able to have the patient authorize that”. Conclusions: There is consistency between provider strategies to communicate prognostic information and patients’ perceptions of how they would like prognostic information to be communicated to them. While providers are concerned with accuracy of predictive models, patients and caregivers are more concerned with privacy.