Data Quality Management and Analysis

Good data quality management in pharmacovigilance can be relied only on information gathered from the collection of individual case safety reports and other pharmacoepidemiological data. Quality management consists of quality planning, quality control, quality assurance and quality improvements. The pharmacovigilance data processing cycle starts with data collection and, in computerised systems, data entry; the next step is data storage and maintenance; followed by data selection, retrieval and manipulation. The resulting data output is analysed and assessed. Finally, conclusions are drawn and decisions made. The quality of a pharmacovigilance data system can be defined as a measure of excellence or a state of being free from defects, deficiencies and significant variations and the  data quality management includes all the activities that organizations use to direct, control and coordinate the quality of data. Several functioning, well documented and transparent quality management systems will assist in data collection management and output production and in addition will help the pharmacovigilance end users and patients.

  • Data Quality Control and Assurance
  • Quality Planning and Improvement
  • Data Safety Monitoring

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