The healthcare system is an example of a complex sociotechnical system where the goal is the best possible individual treatment together with the cost-effective use of modern technology. Working in anesthesia requires medical knowledge as well as manual skills and the use of specialized technical equipment in an interdisciplinary and interprofessional setting. The susceptibility to errors and adverse events, especially in the care of critically ill patients, is high.In order to avoid unintentional hospital-induced patient harm, the healthcare system has recently taken the path of prescribing the best possible care for a large number of patients with the help of evidence-based guidelines and specific algorithms or instructions for action. Patient safety is defined accordingly as a state in which adverse events occur as rarely as possible (Safety‑I).Following this approach clinical risk management is defined as the purposeful planning, coordination, execution and control of all measures that serve to avoid unintended hospital-induced patient harm or to limit its effects. For this purpose, the focus has recently been placed on instruments such as Critical Incident Reporting Systems (CIRS) or Morbidity and Mortality Conferences (M&MC); however, it is increasingly recognized that adverse events in complex sociotechnical systems such as the healthcare system arise situationally from the interaction of numerous components of the system. The effectiveness of CIRS and M&MC is limited because they do not comprehensively take situational effects into account. Thus, only selective changes are possible which, however, do not imply a sustainable improvement of the system. Newer approaches to strengthening safety in complex sociotechnical systems understand positive as well as negative events as being equally caused by the variable adaptation of behavior to daily practice. They therefore focus on the majority of positive courses of treatment and the necessary adaptations of the health professionals involved in daily practice (Safety‑II). In this way, the adaptability of the system under unexpected conditions should be increased (Resilience Engineering). Taking this systemic approach into account, the Functional Resonance Analysis Method (FRAM) offers a variety of possibilities for the prospective analysis of a complex sociotechnical system or for retrospective incident analysis through modelling of actual everyday actions (work as done). Through interviews with the health professionals involved, document analyses and work inspections, processes and their functions as well as the associated variability are assessed and graphically presented. The FRAM models the collected information of the process as complexes of interconnected functions represented by hexagonal symbols. Each corner of the hexagon represents a given aspect, which together form the properties of the function (input, output, precondition, resource, time, control). Through this visualization and evaluation of the interview results, the actual everyday actions (work as done) can be compared with the predefined ones (work as imagined). The evaluation of the variability found in this way enables the strengths and weaknesses of processes to be uncovered. As a result, specific measures can be derived to strengthen the system. Increased consideration of the Safety‑II approach within clinical risk management can be a valuable addition to existing clinical risk management methods.
Das Gesundheitswesen ist ein Beispiel für ein komplexes soziotechnisches System, dessen Ziel die individuell bestmögliche Behandlung unter kosteneffizientem Einsatz moderner Technik ist. Die Arbeit in der Anästhesie erfolgt interdisziplinär und interprofessionell. Die Fehleranfälligkeit – insbesondere in der Versorgung kritisch kranker Patienten – ist hoch. Zur Reduktion und zur Vermeidung von unerwünschten Ereignissen im Sinne einer Qualitätsoptimierung werden Instrumente des klinischen Risikomanagements wie Critical-Incident-Reporting-Systeme oder Morbiditäts- und Mortalitätskonferenzen eingesetzt (Safety‑I). Deren Wirksamkeit ist jedoch limitiert, da sie die für unerwünschte Ereignisse verantwortliche Wechselwirkung zahlreicher Komponenten eines komplexen Systems nicht vollständig erfassen können. Daher werden neuerdings die Ursachen für die überwiegend positiven Behandlungsverläufe in den Vordergrund gestellt (Safety‑II), um die Anpassungsfähigkeit des Systems unter unerwarteten Bedingungen zu erhöhen (Resilience Engineering). Diesem Ansatz folgend bietet die Funktionale Resonanzanalysemethode (FRAM) vielfältige Möglichkeiten zur prospektiven Analyse eines komplexen soziotechnischen Systems oder zur retrospektiven Zwischenfallanalyse durch systematische Modellierung des tatsächlichen Alltagshandelns. Durch Interviews, Dokumentenanalysen und Arbeitsbegehungen werden Prozesse und deren Funktionen sowie die damit verbundene Variabilität menschlichen Handelns erfasst und grafisch dargestellt. So ermöglicht die FRAM das Aufdecken von Stärken und Schwächen von Prozessen, sodass spezifische Maßnahmen abgeleitet werden können. Die vermehrte Berücksichtigung des Safety‑II-Ansatzes kann eine wertvolle Ergänzung zu den bestehenden Methoden des klinischen Risikomanagements darstellen.
Keywords: Complex sociotechnical systems; Functional resonance analysis method; Patient safety; Resilience engineering; System safety.
© 2022. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.