2017
DOI: 10.1007/978-3-319-67144-4_8
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Data Quality in Rare Diseases Registries

Abstract: In the field of rare diseases, registries are considered power tool to develop clinical research, to facilitate the planning of appropriate clinical trials, to improve patient care and healthcare planning. Therefore high quality data of rare diseases registries is considered to be one of the most important element in the establishment and maintenance of a registry. Data quality can be defined as the totality of features and characteristics of data set that bear on its ability to satisfy the needs that result f… Show more

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Cited by 72 publications
(108 citation statements)
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“…To improve our knowledge of longer-term outcomes in patients with all types of EB, enrollment of patients, including those with milder forms of EB, will be critical. 17 …”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…To improve our knowledge of longer-term outcomes in patients with all types of EB, enrollment of patients, including those with milder forms of EB, will be critical. 17 …”
Section: Discussionmentioning
confidence: 99%
“…Each Epidermolysis Bullosa Clinical Research Consortium site collaborates in the Epidermolysis Bullosa Clinical Characterization and Outcomes Database (EBCCOD) to catalog well-described patient cohorts with EB for future studies and to generate longitudinal data about the course, complications, and treatment of patients with EB. 17 …”
mentioning
confidence: 99%
“…Appropriate design, implementation and deployment of patient registries enables rapid decision making and ongoing data mining, ultimately leading to improved patient outcomes. [7,19,20] In the speci c eld of rare diseases, the use of registries increases research accessibility for individuals, while providing clinicians/investigators with a coherent data ecosystem necessary to boost research. The IRD-PT module of retina.pt will facilitate the e cient capture of accurate, longitudinal, country-wide data for IRDs.…”
Section: Discussionmentioning
confidence: 99%
“…The quality of data is defined by attributes such as completeness, accuracy, timeless, usefulness, interoperability, accessibility, and data security [13]. All these attributes are interrelated and it is important to define objectives for data quality and to find a good balance among them.…”
Section: Data Qualitymentioning
confidence: 99%
“…Based on geographic coverage, registries can be classified as: population-based registries, which refer to a geographically defined population and their aim is to register all cases in that population; and non-population-based registries, which are based on selected bodies, clinical centres or other types of structures where the population coverage may not be comprehensive [13]. …”
Section: Introductionmentioning
confidence: 99%