Abstract: Patients being treated successfully with a drug of abuse and at low risk for abusing the drug nevertheless may be at high risk of being misidentified as a high risk of abuse. These patients may need and benefit from treatment with the drug but restricted or cut off from the treatment altogether due to the misidentification and then abandoned. Evaluating a patient's risk of drug treatment change due to a category misidentification may include developing a model for identifying such abandoned patients, applying the model to data of a patient, and determining a patient risk score for the patient based on a result of applying the model.

Abstract: Methods and systems to stratify risks for adverse health outcomes include aggregating data sets culled over a predetermined period of time; adjusting at least two variables within the aggregated data sets; and executing a regression analysis to identify an average causal effect between aggregated variables against at least one particular adverse health outcome.

Abstract: A method, system, and computer-readable medium to stratify a health risk acquires structured information and unstructured information from a plurality of sources, converts at least some of the unstructured information to structured information, and geocodes the acquired structured information and converted structured information to produce geocoded data. Health information of a plurality of subjects are similarly geocoded to produce geocoded subject health data and merged with the geocoded data and mapped to a dashboard.