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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. [4]
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 has become increasingly valuable in the 21st century and new economies have been shaped by who controls it [11] —health data and the health care industry are unlikely to be an exception. An increase in PGHD has led some experts to envision a future in which patients have greater influence over the health care system. [12]
Health care quality is the degree to which health care services for individuals and populations increase the likelihood of desired health outcomes. [2] Quality of care plays an important role in describing the iron triangle of health care relationships between quality, cost, and accessibility of health care within a community. [3]
Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...
Outcomes research is applied to clinical and population based research that seeks to study and optimize the end results of healthcare in terms of benefits to the patient and society. The intent of this research is to identify shortfalls in practice and to develop strategies to improve care.
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Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning".