Abstract: Methods, systems, and techniques for provider-level erroneous electronic medical claim record detection. The records encode medical services providers, medical activities performed by the medical services providers, and specialties of the medical services providers. A cohort of the medical services providers are identified by specialty. Activity feature vectors respectively corresponding to the medical activities performed by the medical services providers of the cohort are generated. A mixture model having components fit to the activity feature vectors is determined and a provider feature vector for each of at least one of the medical services providers is generated. This generating involves mapping activities performed by each of the at least one of the medical services providers in accordance with the mixture model.

Abstract: Methods, systems, and techniques for claim-level erroneous electronic medical claim record detection. An electronic medical claim record, which encodes a diagnosis for a patient by a medical services provider, is obtained. The diagnosis is input into a classifier trained using training diagnoses and training medical services provided in response to the training diagnoses. A predicted medical service provided by the medical services provider to the patient in response to the diagnosis is obtained as an output from the classifier.