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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.
The patient health record is the primary legal record documenting the health care services provided to a person in any aspect of the health care system. The term includes routine clinical or office records, records of care in any health related setting, preventive care, lifestyle evaluation, research protocols and various clinical databases.
Most frequently registries vary in sophistication from simple spreadsheets that only can be accessed by a small group of physicians to very complex databases that are accessed online across multiple institutions. [2] They can provide health providers (or even patients) with reminders to check certain tests in order to reach certain quality goals.
Example of a spreadsheet holding data about a group of audio tracks. A spreadsheet is a computer application for computation, organization, analysis and storage of data in tabular form. [1] [2] [3] Spreadsheets were developed as computerized analogs of paper accounting worksheets. [4] The program operates on data entered in cells of a table.
Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics, Biomedical informatics, and machine learning, with the goal of understanding biological and medical data.
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.
Data independence is of particularly high value for analytics. Data need no longer reside in spreadsheets. Instead the functional database acts as a central information resource. The spreadsheet acts as a user interface to the database, so the same data can be shared by multiple spreadsheets and multiple users.