QUALITY OF CLINICAL DATA ON PATIENT SAFETY: CURRENT STATE ASSESSMENT AND GENERALIZATION AND SCALING ISSUES

Abstract

Aim of the study. Recent studies have shown that medical errors are an increasingly common cause of patient morbidity and mortality. For this reason, there are several approaches to identifying errors and their causes. These approaches include but are not limited to retrospective reporting, error analysis, or forward-looking analysis to identify high-risk situations. In this context, the research aims to analyse a series of sources and methods that contribute to the qualitative assessment of data used in patient safety risk analysis. Results. The results of our study show that aggregating and comparing data across organizations, domains, or applications is quite complex. Our analysis highlights that multiple data representations can be helpful in risk analysis. However, other application-specific and often organization-specific pictures limit the ability to share patient safety data. To aggregate data regionally and nationally and to conduct studies of patient safety risks and interventions, we believe it is necessary to implement a standard reference data model and terminology that can be widely applied.

Keywords

• patient safety
• data quality
• data representation
• risks
• covid-19