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Big data in health research is particularly promising in terms of exploratory biomedical research, as data-driven analysis can move forward more quickly than hypothesis-driven research. [88] Then, trends seen in data analysis can be tested in traditional, hypothesis-driven follow up biological research and eventually clinical research.
A hospital information system (HIS) is an element of health informatics that focuses mainly on the administrational needs of hospitals.In many implementations, a HIS is a comprehensive, integrated information system designed to manage all the aspects of a hospital's operation, such as medical, administrative, financial, and legal issues and the corresponding processing of services.
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]
The European Committee for Standardization Standard Architecture for Healthcare Information Systems (ENV 12967), Health Informatics Service Architecture or HISA is a standard that provides guidance on the development of modular open information technology (IT) systems in the healthcare sector. Broadly, architecture standards outline frameworks ...
Galaxy is a web platform for data-intensive biology using geographically-distributed supercomputers. [56] LabKey Server is an extensible platform for integrating, analyzing and sharing all types of biomedical research data. It provides secure, web-based access to research data and includes a customizable data processing pipeline.
Structure of the TOGAF Architecture Development Method (ADM). [1] The Open Group Architecture Framework (TOGAF) is the most used framework for enterprise architecture as of 2020 [2] that provides an approach for designing, planning, implementing, and governing an enterprise information technology architecture. [3] TOGAF is a high-level approach ...
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration , for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems.