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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]
An example of a study utilizing RWE is "Clinical Features and Outcomes of Coronavirus Disease 2019 Among People Who Have HIV in the United States: A Multi-center Study From a Large Global Health Research Network (TriNetX)" In this study, Covid-19 outcomes were compared between people with HIV and HIV-negative controls from a database of de ...
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.
The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.” [7] Other journals have a more general scope than biomedical data science, but regularly publish biomedical data science research such as Health Data Science [8] and Nature Machine Intelligence. [9]
In some studies, attainment of HEDIS measures is associated with cost-effective practices or with better health outcomes. In a 2002 study, HEDIS measures "generally reflect[ed] cost-effective practices". [11] A 2003 study of Medicare managed care plans determined that plan-level health outcomes were associated with HEDIS measures. [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 ...
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".