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OMOP Common Data Model: model that defines how electronic health record data, medical billing data or other healthcare data from multiple institutions can be harmonized and queried in unified way. It is maintained by Observational Health Data Sciences and Informatics consortium.
Health data are classified as either structured or unstructured. Structured health data is standardized and easily transferable between health information systems. [4] For example, a patient's name, date of birth, or a blood-test result can be recorded in a structured data format.
The standards allow for easier 'interoperability' of healthcare data as it is shared and processed uniformly and consistently by the different systems. This allows clinical and non-clinical data to be shared more easily, theoretically improving patient care and health system performance. [1]
Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...
Some of the problems tackled by CRI are: creation of data warehouses of health care data that can be used for research, support of data collection in clinical trials by the use of electronic data capture systems, streamlining ethical approvals and renewals (in US the responsible entity is the local institutional review board), maintenance of ...
Medical billing, a payment process in the United States healthcare system, is the process of reviewing a patient's medical records and using information about their diagnoses and procedures to determine which services are billable and to whom they are billed. [1] This bill is called a claim. [2]
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Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [26] Big data requires a set of techniques and technologies with new forms of integration to reveal insights from data-sets that are diverse, complex, and of a massive scale. [27]