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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.
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.
An XML element in a CDA supports unstructured text, as well as links to composite documents encoded in pdf, docx, or rtf, as well as image formats like jpg and png. [3] It was developed using the HL7 Development Framework (HDF) and it is based on the HL7 Reference Information Model (RIM) and the HL7 Version 3 Data Types. [citation needed]
The U.S. Healthcare Information Technology Standards Panel has selected the CCD as one of its standards. [citation needed] CCDs are quickly becoming one of the most ubiquitous and thorough means of transferring health data on patients as each can contain vast amounts of data based on the standard format, in a relatively easy to use and portable ...
The CCC is a nursing terminology specifically developed for computerization: e.g. electronic healthcare information systems (EHR), computer-based patient records (CPR), and Clinical Information Systems (CIS), from research which collected live patient care data. The CCC System describes the six steps of the nursing process: Assessment; Diagnosis
In the field of electronic health records (EHR), Cross Enterprise Document Sharing (XDS) is a system of standards for cataloging and sharing patient records across health institutions. [ 1 ] XDS provides a registry for querying which patient records are in an EHR repository and methods for retrieving the documents.
Cross-border and Interoperable electronic health record systems make confidential data more easily and rapidly accessible to a wider audience and increase the risk that personal data concerning health could be accidentally exposed or easily distributed to unauthorised parties by enabling greater access to a compilation of the personal data ...
A mixed random variable does not have a cumulative distribution function that is discrete or everywhere-continuous. An example of a mixed type random variable is the probability of wait time in a queue. The likelihood of a customer experiencing a zero wait time is discrete, while non-zero wait times are evaluated on a continuous time scale. [16]