The development and validation instrument for the cognitive medical errors: structural equation modeling approach

Despite the great efforts of healthcare providers, medical errors are inevitable, and the consequences of these errors may vary from little or no harm (near-miss) to being ultimately fatal to patients. Many taxonomies have been used to classify medical errors. Yet, medical errors can be classified—according to cognitive taxonomy—into: mistakes, slips, and lapses. Because there is no any instrument to measure the cognitive medical errors. The main objective of this study is to develop and validate cognitive medical errors measurement instrument. The study employed a cross-sectional design. A survey was developed based on previous relevant studies. Data was collected from 400 healthcare providers (physicians and registered nurses) using the convenience sampling method, between July and October 2020. The survey assessed healthcare providers' attitudes and perceptions about the cognitive medical errors in three major hospitals. Structural equation modeling was used to validate the cognitive medical errors. The convergent and discriminant validity of the constructs were estimated through average variance extraction (AVE) and shared variance (SV). The study results confirm the proposed cognitive medical errors model, and show that the cognitive medical errors consist of three items (one item for mistakes, one item for slips, and one item for lapses). Practically, this research contributes to enhancing the medical error classification and to understanding of cognitive medical errors in the health sector, also offer validate instrument for cognitive medical errors. Accurate measurement informs interventions and/or policy and practices that can be targeted to reduce medical errors and improving patient safety.