Improvement proposals and actions in medication error reports: Quality and strength: A cross-sectional study.

ABSTRACT

Background and Aims: Medication errors (MEs) are a significant source of preventable harm in patient care. Voluntary incident reporting and ME reporting systems are essential for managing medication safety. Analyzing aggregated ME reports instead of individual reports can reveal organizational risks. Organizational culture influences reporting activity and the effectiveness of safety improvements depends on their system-focus. This study uses aggregated ME reports to investigate the ME management process and reporting culture in medication safety. It aims to create a hierarchy for ME improvement actions and analyze their strength and management flow in aggregated reports. Methods: A retrospective, cross-sectional study was conducted to review improvement proposals and actions of ME reports in a Finnish tertiary hospital in 2017-2021. The improvement proposals and actions were categorized into strength classes during three stages reporter proposals, manager proposals, and documented actions. The report management flow was analyzed. Descriptive statistics were used to describe the characteristics and the chi-squared test for categorical variables in the statistical analysis. Results: A new strength classification hierarchy was created with three classes and corresponding numerical values "strong (3)," "medium (2)," and "weak (1)" Additionally, categories for "no action (0)" and "vague (0)" were included. Out of 5463 ME reports analyzed, improvement proposals and actions were predominantly weak, ranging from 23.4% to 54.2% across different stages of the management process. A significant proportion had no action included (20.5-49.1%) or were vague (4.2-20.6%). Conclusion: Analyzing the strength of improvement proposals and actions in aggregated ME reports provides new insights into reporting culture and the ME management. The new combined strength classification hierarchy is a suitable tool for this analysis.