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Impact of data quality assessment on development of clinical predictive models.
- Source :
-
Studies in health technology and informatics [Stud Health Technol Inform] 2015; Vol. 216, pp. 1069. - Publication Year :
- 2015
-
Abstract
- Data quality plays a very important role in predicting clinical outcomes. Data quality is multi dimensional and most relevant studies consider just one or two dimensions. In this study a systematic data quality assessment is performed using four data dimensions. The results demonstrate that performance of predictive models improves when the quality of the data is assessed and addressed systematically.
- Subjects :
- Computer Simulation
Critical Care statistics & numerical data
Datasets as Topic standards
Hospital Mortality
Incidence
Models, Statistical
New South Wales
Prognosis
Risk Assessment standards
Survival Analysis
Critical Illness mortality
Data Accuracy
Decision Support Systems, Clinical standards
Electronic Health Records standards
Electronic Health Records statistics & numerical data
Quality Assurance, Health Care methods
Subjects
Details
- Language :
- English
- ISSN :
- 1879-8365
- Volume :
- 216
- Database :
- MEDLINE
- Journal :
- Studies in health technology and informatics
- Publication Type :
- Academic Journal
- Accession number :
- 26262368