Using the Generic Analysis Method to Analyze Sentinel Event Reports Across Hospitals: A Retrospective Cross-Sectional Study.

OBJECTIVES: Improving patient safety by investigating sentinel events (SEs) is hampered by the focus on isolated events within hospitals and a narrow scope of traditional root cause analysis methods. We aimed to examine if performing cross-hospital aggregate analysis of SEs applying a novel generic analysis method (GAM) bearing a human factor perspective can enhance learning from SEs. METHODS: A retrospective cross-sectional review of SE reports from 28 Dutch general hospitals using the GAM to reanalyze events was performed. A qualitative approach was used to identify contributing factors and system issues. Findings were discussed with a patient safety expert panel. Descriptive statistics and measures of associations between domains were calculated. RESULTS: Sixty-nine SE reports were reviewed. Applying the GAM provided a more holistic SE analysis than a traditional method. Of the 405 identified contributing factors in all SEs, the majority was related to the persons involved (patients and professionals, n = 146 [36.2%]) and the organization (n = 121 [30%]). The most frequently recurring pattern was the combination of factors related to the persons involved, the technology used, the tasks of professionals, and organizational factors influencing the event. Cross-hospital aggregate GAM analysis of SEs helped to identify system issues and propose more system-oriented overarching recommendations. CONCLUSIONS: This study found that applying the GAM to analyze SEs across hospitals can help to improve learning from SEs and may result in proposing stronger recommendations. The method can support hospitals, working together in a network of hospitals, to jointly learn from SEs.

What Can We Learn From In-Depth Analysis of Human Errors Resulting in Diagnostic Errors in the Emergency Department: An Analysis of Serious Adverse Event Reports.

INTRODUCTION: Human error plays a vital role in diagnostic errors in the emergency department. A thorough analysis of these human errors, using information-rich reports of serious adverse events (SAEs), could help to better study and understand the causes of these errors and formulate more specific recommendations. METHODS: We studied 23 SAE reports of diagnostic events in emergency departments of Dutch general hospitals and identified human errors. Two researchers independently applied the Safer Dx Instrument, Diagnostic Error Evaluation and Research Taxonomy, and the Model of Unsafe acts to analyze reports. RESULTS: Twenty-one reports contained a diagnostic error, in which we identified 73 human errors, which were mainly based on intended actions (n = 69) and could be classified as mistakes (n = 56) or violations (n = 13). Most human errors occurred during the assessment and testing phase of the diagnostic process. DISCUSSION: The combination of different instruments and information-rich SAE reports allowed for a deeper understanding of the mechanisms underlying diagnostic error. Results indicated that errors occurred most often during the assessment and the testing phase of the diagnostic process. Most often, the errors could be classified as mistakes and violations, both intended actions. These types of errors are in need of different recommendations for improvement, as mistakes are often knowledge based, whereas violations often happen because of work and time pressure. These analyses provided valuable insights for more overarching recommendations to improve diagnostic safety and would be recommended to use in future research and analysis of (serious) adverse events.

Compliance with a time-out procedure intended to prevent wrong surgery in hospitals: results of a national patient safety programme in the Netherlands.

OBJECTIVE: To prevent wrong surgery, the WHO 'Safe Surgery Checklist' was introduced in 2008. The checklist comprises a time-out procedure (TOP): the final step before the start of the surgical procedure where the patient, surgical procedure and side/site are reviewed by the surgical team. The aim of this study is to evaluate the extent to which hospitals carry out the TOP before anaesthesia in the operating room, whether compliance has changed over time, and to determine factors that are associated with compliance. DESIGN: Evaluation study involving observations. SETTING: Operating rooms of 2 academic, 4 teaching and 12 general Dutch hospitals. PARTICIPANTS: A random selection was made from all adult patients scheduled for elective surgery on the day of the observation, preferably involving different surgeons and different procedures. RESULTS: Mean compliance with the TOP was 71.3%. Large differences between hospitals were observed. No linear trend was found in compliance during the study period. Compliance at general and teaching hospitals was higher than at academic hospitals. Compliance decreased with the age of the patient, general surgery showed lower compliance in comparison with other specialties and compliance was higher when the team was focused on the TOP. CONCLUSIONS: Large differences in compliance with the TOP were observed between participating hospitals which can be attributed at least in part to the type of hospital, surgical specialty and patient characteristics. Hospitals do not comply consistently with national guidelines to prevent wrong surgery and further implementation as well as further research into non-compliance is needed.

The ecometric properties of a measurement instrument for prospective risk analysis in hospital departments.

BACKGROUND: Safety management systems have been set up in healthcare institutions to reduce the number of adverse events. Safety management systems use a combination of activities, such as identifying and assessing safety risks in the organizational processes through retrospective and prospective risk assessments. A complementary method to already existing prospective risk analysis methods is Tripod, which measures latent risk factors in organizations through staff questionnaires. The purpose of this study is to investigate whether Tripod can be used as a method for prospective risk analysis in hospitals and whether it can assess differences in risk factors between hospital departments. METHODS: Tripod measures risk factors in five organizational domains: (1) Procedures, (2) Training, (3) Communication, (4) Incompatible Goals and (5) Organization. Each domain is covered by 15 items in the questionnaire. A total of thirteen departments from two hospitals participated in this study. All healthcare staff working in the participating departments were approached. The multilevel method ecometrics was used to evaluate the validity and reliability of Tripod. Ecometrics was needed to ensure that the differences between departments were attributable to differences in risk at the departmental level and not to differences between individual perceptions of the healthcare staff. RESULTS: A total of 626 healthcare staff completed the questionnaire, resulting in a response rate of 61.7%. Reliability coefficients were calculated for the individual level and department level. At the individual level, reliability coefficients ranged from 0.78 to 0.87, at the departmental level they ranged from 0.55 to 0.73. Intraclass correlations at the departmental level ranged from 3.7% to 8.5%, which indicate sufficient clustering of answers within departments. At both levels the domains from the questionnaire were positively interrelated and all significant. CONCLUSIONS: The results of this study show that Tripod can be used as a method for prospective risk analysis in hospitals. Results of the questionnaire provide information about latent risk factors in hospital departments. However, this study also shows that there are indications that the method is not sensitive enough to detect differences between hospital departments. Therefore, it is important to be careful when interpreting differences in potential risks between departments when using Tripod.