Preoperative Anticoagulation Management in Everyday Clinical Practice: An International Comparative Analysis of Work-as-Done Using the Functional Resonance Analysis Method
- 10 July 2018
- journal article
- research article
- Published by Wolters Kluwer Health in Journal of Patient Safety
- Vol. 17 (3) , 157-165
Abstract
Objectives: Preoperative anticoagulation management (PAM) is a complex, multidisciplinary process important to patient safety. The Functional Resonance Analysis Method (FRAM) is a novel method to study how complex processes usually go right at the frontline (labeled Safety-II) and how this relates to predefined procedures. This study aimed to assess PAM in everyday practice and explore the usability and utility of FRAM. Methods: The study was conducted at an Australian and European Cardiothoracic Surgery Department. A FRAM model of work-as-imagined was developed using (inter)national guidelines. Semistructured interviews with 18 involved professionals were used to develop models reflecting work-as-done at both sites, which were presented to staff for validation. Workload in hours was estimated per process step. Results: In both centers, work-as-done differed from work-as-imagined, such as in the division of tasks among disciplines (e.g., nurses/registrars rather than medical specialists), but control mechanisms had been developed locally to ensure safe care (e.g., crosschecking with other clinicians). Centers had organized the process differently, revealing opportunities for improvement regarding patient information and clustering of clinic visits. Presenting FRAM models to staff initiated discussion on improvement of functions in the model that are vital for success. Overall workload was estimated at 47 hours per site. Conclusions: This FRAM analysis provided insight into PAM from the perspective of frontline clinicians, revealing essential functions, interdependencies and variability, and the relation with guidelines. Future studies are warranted to study the potential of FRAM, such as for guiding improvements in complex systems.Keywords
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