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Data quality (DQ) is the degree to which a given dataset meets a user's requirements. In the primary healthcare setting, poor quality data can lead to poor patient care, negatively affect the validity and reproducibility of research results and limit the value that such data may have for public health surveillance.
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.
In mental health services these values may be quite low, especially when carried out routinely by staff rather than by trained researchers, and when using short measures that are feasible in everyday practice. Data collected must be fed back to them to maximize data quality, reliability and validity. [23]
The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
Health indicators are quantifiable characteristics of a population which researchers use as supporting evidence for describing the health of a population.Typically, researchers will use a survey methodology to gather information about a population sample, use statistics in an attempt to generalize the information collected to the entire population, and then use the statistical analysis to make ...
Interoperability between disparate clinical information systems requires common data standards or mapping of every transaction. However common data standards alone will not provide interoperability, and the other requirements are identified in "How Standards will Support Interoperability" from the Faculty of Clinical Informatics [2] and "Interoperability is more than technology: The role of ...
The use of mobile devices in health, or mHealth, creates new challenges to health data security and privacy, in ways that directly affect data quality. [ 2 ] mHealth is an increasingly important strategy for delivery of health services in low- and middle-income countries. [ 22 ]
It is the test against which new tests are compared to gauge their validity, and it is used to evaluate the efficacy of treatments. [1] The meaning of "gold standard" may differ between practical medicine and the statistical ideal. With some medical conditions, only an autopsy can guarantee diagnostic certainty. In these cases, the gold ...
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