Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for identifying supply chain issues are presented. A first supply chain dataset comprising a plurality of supply chain dimensions may be received. A subset of the dataset may be transformed into plurality of supply chain vectors. A temporal moving average plot may be generated for each supply chain vector in a subset of the plurality of supply chain vectors. A set of rules may be applied to each temporal moving average plot to determine a performance value for each corresponding supply chain vector in the subset. A determination may be made that a performance value for a specific one of the supply chain vectors is below a threshold value. An interactive user interface that indicates the performance value for the specific supply chain vector is below the threshold value may be displayed.

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 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.

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. .