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: Disclosed are methods and systems for identifying and profiling focus areas of healthcare providers. Embodiments include technology that identifies focus areas automatically from healthcare information such as diagnoses and procedures. As such, healthcare providers that frequently diagnose and/or treat patients for similar conditions may be automatically grouped into the same cluster. Expert knowledge may then be used to label a cluster as a focus area.

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 health care facility that diagnosis or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, care givers), 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.

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.