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The objective of this study was to measure organization factors that can influence the ability of nursing staff to prevent and detect ADEs in public hospitals using Systems Engineering Initiative for Patient Safety (SEIPS) model. Methods: This was a multi-center cross-sectional study. The study included a self-administered paper-based survey which was distributed and collected between October through December 2019. The study participants were nurses from 11 public hospitals located in two Iraqi provinces. Binary logistic regression was used to measure the relationship between the independent SEIPS factors (persons, organizations, tools, tasks, and environments) and the incidence of ADEs (outcome variable). Results: The study recruited 603 nurses (68.3% men) from 11 public hospitals across two provinces. Less than half (48.8%) of the nurses received enough training to detect ADEs, 43.1% had adequate experience to detect ADEs, and 69.8% had to report ADEs in a special record. More than three-quarters (78.4%) believed that their jobs need fast work. Two of the five SEIPS model domains had significant negative association with the incidence of ADEs including organization (nurse-physician collaboration) and nurse experience in ADE detection. Conclusions: Nursing staff face several challenges to prevent and minimize ADEs including shortages in nurses, inadequate nurse experience in ADE detection, no training for ADE detection was received, fear of reporting ADEs, and a lack in monitoring equipment. Increasing nurse/patient ratio and providing more monitoring equipment and training courses can minimize ADEs and enhance their detection.

The objective of this study was to measure organization factors that can influence the ability of nursing staff to prevent and detect ADEs in public hospitals using Systems Engineering Initiative for Patient Safety (SEIPS) model. This was a multi-center cross-sectional study. The study included a self-administered paper-based survey which was distributed and collected between October through December 2019. The study participants were nurses from 11 public hospitals located in two Iraqi provinces. Binary logistic regression was used to measure the relationship between the independent SEIPS factors (persons, organizations, tools, tasks, and environments) and the incidence of ADEs (outcome variable). The study recruited 603 nurses (68.3% men) from 11 public hospitals across two provinces. Less than half (48.8%) of the nurses received enough training to detect ADEs, 43.1% had adequate experience to detect ADEs, and 69.8% had to report ADEs in a special record. More than three-quarters (78.4%) believed that their jobs need fast work. Two of the five SEIPS model domains had significant negative association with the incidence of ADEs including organization (nurse-physician collaboration) and nurse experience in ADE detection. Nursing staff face several challenges to prevent and minimize ADEs including shortages in nurses, inadequate nurse experience in ADE detection, no training for ADE detection was received, fear of reporting ADEs, and a lack in monitoring equipment. Increasing nurse/patient ratio and providing more monitoring equipment and training courses can minimize ADEs and enhance their detection. [ABSTRACT FROM AUTHOR]

The concept of patient safety has been developed due to the increased incidence of medical error in Indonesia. Although incidents related to patient safety occurs in health servicessuch as the Independent Practice of Midwifery or BidanPraktikMandiri(BPM), it has not received enough attention from the stakeholders. This research discusses the implementationof Patient Safety Model atthe Independent Practice of Midwiferyin Bogor District, West Java Province. The research was conducted with mixed method approach, using threeway phase. The first phase is the construction on patient safety goals in BPM by doing focus group discussion on 3 groups and 2 in-depth interviews with 2 informants. The second phase is the model development in the form of validation based on findings in the first phase. Additionally, phase 2 is done by using crosssectional design of 90 midwives and SEM analysis using PLS. The third phase is conducting a quantitative evaluation model with pre and post design at 30 BPM which have had training on Patient Safety Model. The findings show allvariables (patient safety goals, knowledge, attitudes, motivations, and behaviors related to the patient safety) are valid in shaping Patient Safety Model. The results on Model application evaluation (phase 3) indicate that the model effective in increasing knowledge (p 0.000), attitude (p 0.000), motivation (p 0.000) and behavior (p 0.001) on patient safety in BPM. [ABSTRACT FROM AUTHOR]