Introduction
Adverse events in healthcare represent a major source of morbidity and mortality and result in substantial societal costs.1–4 Hospitals in numerous countries, such as the Netherlands, the USA, Canada, Australia and the UK, aim to learn from previous events by thoroughly investigating these. In particular, hospitals invest in studying the events that have caused temporary or permanent disability, death or prolonged hospital stay, also known as sentinel events or serious adverse events (SAEs).5–10 After hospitals investigate a SAE, they write a detailed report. This report starts with a comprehensive reconstruction of the event and concludes with a root cause analysis (RCA), in which hospitals search for root causes and formulate recommendations to prevent recurrence.11 SAE investigations and the associated reports offer great potential for hospitals to learn from each other and improve patient safety. However, SAE investigations and analyses are being criticised for oversimplification,12 resulting in weak solutions,10 11 13 and overall ineffectiveness.11 13–15 Two important shortcomings impede hospitals in particular in their ambition to learn from SAEs.
First, SAE investigations often neglect the complexity of healthcare.13 15 Current methods applied for SAE analysis, focus on finding one linear root cause, even though SAEs are more likely to arise from interactions and combinations of causes and contributing factors in the complex healthcare system.10 13 14 SAE analysis thus needs a shift from focusing on finding the ‘one’ linear root cause towards searching for the combination of interrelated contributing factors and causes. The incorporation of human factors thinking in SAE analysis is assumed to induce this shift.16–20 Human factors is concerned with the understanding of interactions and interdependencies between humans and other elements of a work system.21–23 It searches for opportunities to design healthcare systems that have a greater tolerance of faults and thus might improve the resilience of the system.24–26 One model that integrated principles of human factors into the healthcare domain is the Systems Engineering Initiative for Patient Safety (SEIPS).27–32 This theoretical model is used to study patient safety hazards and adverse events in various healthcare settings.16 30–35 SEIPS is based on the well-known structure–process–outcome model for healthcare quality.36 It therefore is assumed to be familiar to audiences working in healthcare quality and patient safety.31 Although the potential of SEIPS to improve patient safety is proven,31 adoption of the model in retrospective SAE analysis is still limited and should be refined and accelerated.16 30
A second shortcoming of current SAE investigations is that hospitals typically focus on single events within their own organisation,13 14 even though attempts to learn from aggregate analysis of multiple events across hospitals, as already performed in Australia37 and the USA,38 39 are believed to improve learning.38–41 It helps to discover combinations of recurring, underlying, patterns of causes and contributing factors42 and may improve the formulation of more effective, system-aimed recommendations.14 38 However, methods for analysing SAEs vary substantially,10 which complicates aggregate cross-hospitals analysis of SAEs. For example, in the Netherlands, where aggregate analysis of SAEs is scarce, hospitals use three differing methods for analysing SAEs41 43 44: Prevention and Recovery Information System for Monitoring and Analysis (PRISMA-medical),45 Tripod Beta46 and Systemic Incident Reconstruction and Evaluation (SIRE).47 These methods are useful for a structured analysis of SAEs, yet based on their description in scientific articles,41 44 48 49 anecdotal evidence43 46 47 and experience, each method has its own approach, focus and limitations. PRISMA-medical, for example, is highly analytical and categorises latent (technical and organisational) as well as active (human) failures.45 However, the absence of organisational or technical barriers that could prevent SAEs are not considered a root cause in this method.50 Tripod Beta, however, thoroughly investigates system failures and organisational barriers that could prevent SAEs. However, human errors are also explained as organisational or system failures,46 49 even though evidence indicates that flaws in the system and cognitive factors play an important role in the emergence of human error.51–53 SIRE, in turn, emphasises particularly on the primary process and provides a comprehensive narrative description of the event.47 54 To ease aggregate cross-hospital analysis of SAEs, Smits et al43 made a primary attempt to integrate the structures and foci of PRISMA-medical, SIRE and Tripod Beta into a generic framework. Anecdotal evidence of the benefits of this framework to perform an aggregate cross-hospital analysis was presented, but the study emphasised the importance of further development and evaluation.43
Addressing the complexity of healthcare13 and using a consistent method10 41 could thus improve learning from SAEs. This could help to formulate more effective recommendations to enhance patient safety. An alternative approach to study SAEs is therefore necessary. This study aims to develop a novel generic analysis method (GAM) that integrates the SEIPS model31 32 and the PRISMA-medical, SIRE and Tripod Beta framework43 to: (1) facilitate a more holistic analysis using a human factors perspective and (2) ease aggregate analysis across hospitals.