Abstract: A system obtains patient data, de-identifies each patient with a unique patient key (UPK) and joins the patient data without linking to personal identities of the patients. The system further receives a search query from a user device, identifies a group of UPKs associated with patient data that satisfies criteria of the search query based on values for associated healthcare attributes, and clusters the group of UPKs with respect to healthcare events. The system then ranks the healthcare events of the clusters and sends a query result including healthcare data that is generated based on the ranking, where the query result conceals any personal identity of any of the patients.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, glean insight from the activities of the distinctive patient cohorts, and assist with additional patients with the gleaned insight.

Abstract: The disclosed embodiments include a self-service server computer that can be caused to obtain provider-patient data and provider-provider data. The obtained data is pre-process to extract service codes and parameter values associated with the service codes. The self-service server can generate a service episode including a target service and a plurality of ancillary services. The service episode has a parameter value estimated from a parameter value of a service code for the target service and a plurality of parameter values of service codes for the ancillary services. The self-service server can return the estimated parameter value of the service episode in response to a query for a parameter value of the target service such that the estimated parameter value is a proxy for the parameter value for the target service when the self-service server is queried for the target service.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, glean insight from the activities of the distinctive patient cohorts, and assist with additional patients with the gleaned insight. .

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, reconstruct timelines of healthcare events from fragmented medical data, and leverage the existing electronic health data to generate comprehensive profiles of healthcare entities.