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These databases enable research on health and policy issues at the national, State, and local levels, including cost and quality of health services, medical practice patterns, access to healthcare, and outcomes of treatments. AHRQ has also developed a set of software tools to be used when evaluating hospital data.
A clinical data management system or CDMS is a tool used in clinical research to manage the data of a clinical trial. The clinical trial data gathered at the investigator site in the case report form are stored in the CDMS. To reduce the possibility of errors due to human entry, the systems employ various means to verify the data.
The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure
The use of Clinical Data Repositories could provide a wealth of knowledge about patients, their medical conditions, and their outcome. The database could serve as a way to study the relationship and potential patterns between disease progression and management. The term "Medical Data Mining" has been coined for this method of research.
Clinical data standards are used to store and communicate information related to healthcare so that its meaning is unambiguous. They are used in clinical practice, in activity analysis and finding, and in research and development. There are many existing and proposed standards and many bodies working in this field.
A cloud database is a database that typically runs on a cloud computing platform and access to the database is provided as-a-service. There are two common deployment models: users can run databases on the cloud independently, using a virtual machine image, or they can purchase access to a database service, maintained by a cloud database provider.
Historically, this information was collected on paper forms which were then sent to the research sponsor (e.g., a pharmaceutical company) for data entry into a database and subsequent statistical analysis environment. [1] [7] [8] However, this process had a number of shortcomings: [5] [8] data are copied multiple times, which produces errors
The Fast Healthcare Interoperability Resources (FHIR, / f aɪər /, like fire) standard is a set of rules and specifications for the secure exchange of electronic health care data. It is designed to be flexible and adaptable, so that it can be used in a wide range of settings and with different health care information systems.