Background: The Functional Resonance Analysis Method (FRAM) analyses discrepancies between written protocols (Work-as-Imagined) and real-world practice (Work-as-Done) in healthcare. Work-as-Done is created based on multiple stakeholders, leading to variability in reported functions. No guidance exists how to manage this variability. This study examines between-stakeholder variation in Work-as-Done and its impact on differences from Work-as-Imagined in FRAM visualisations. Methods: Two FRAM studies were analysed: delirium diagnosis and treatment (1) and perioperative anticoagulant management in two hospitals (2). Heatmaps visualised between-stakeholder variability of reported functions in Work-as-Done. We assessed the impact of including only functions shared by multiple stakeholders on Work-as-Imagined versus Work-as-Done comparisons. Results: In study 1, 23 of 33 functions were shared among at least two stakeholders. In study 2, stakeholders shared 30 of 33 functions in Hospital 1 and 29 of 32 functions in Hospital 2. Including or excluding functions, e.g., only mentioned by one stakeholder, influenced the observed differences between Work-as-Imagined and Work-as-Done. Conclusions: Between-stakeholder variability in both studies influenced differences between Work-as-Imagined and Work-as-Done, which often is the starting point improving the process. Showing between-stakeholder variability in FRAM studies enhances transparency in researcher decision-making. This supports more informed analysis and discussion in process improvement efforts.

Background
To improve healthcare processes, gaining a thorough understanding of the work is important. The Functional Resonance Analysis Method (FRAM) is a method that can be used for this purpose by visualising how different steps in a process interact. However, little research is available on the use and feasibility of FRAM in quality improvement studies. Therefore, the objective of this study is to assess the feasibility of using FRAM visualisations in a quality improvement study to identify, formulate and test improvement strategies regarding anticoagulant use in the perioperative process in two Dutch University Medical Centres.

Methods
Through multiple Plan-Do-Study-Act cycles, FRAM visualisations of work-as-imagined and work-as-done were created, which were validated and discussed with healthcare professionals through focus groups. Improvement suggestions were collected as input for improvement strategies from frontline clinicians. These strategies were tested and evaluated using questionnaires and interviews. The interviews were analysed using content analysis to further explore the value of the FRAM visualisations for identifying and employing improvement strategies.

Results
The FRAM visualisations were perceived as confusing by professionals given their limited knowledge of FRAM, and it was time-intensive to identify possible improvements in the perioperative process. Using a simplified visualisation that showed the key FRAM information resulted in multiple improvement suggestions which were successfully tested as improvement strategies. The content analysis revealed three themes related to the use of FRAM: how care could be organised efficiently and safely, bringing stakeholders together to highlight the roles and responsibilities of professionals, and identifying how documentation of patient information is often scattered or incomplete.

Conclusions
FRAM visualisations in quality improvement studies can provide valuable insights into the working process, which are also useful for formulating and testing improvement strategies. However, adjustments to the visualisations are necessary to enable professionals to participate in identifying improvement strategies.

Background The recurrence of sentinel events (SEs) is a persistent problem worldwide, despite repeated analyses and recommendations formulated to prevent recurrence. Research suggests this is partly attributable to the quality of the recommendations, and determining if a recommendation will be effective is not yet covered by an adequate guideline. Our objectives were to (1) develop and validate criteria for high-quality recommendations, and (2) evaluate recommendations using the criteria developed. Methods (1) Criteria were developed by experts using the bowtie method. Medical doctors then determined if the recommendations of Dutch in-hospital SE analysis reports met the criteria, after which interobserver variability was tested. (2) Researchers determined which recommendations of Dutch perioperative SE analysis reports produced from 2017 to 2018 met the criteria. Results The criteria were: (1) a recommendation needs to be well defined and clear, (2) it needs to specifically describe the intended changes, and (3) it needs to describe how it will reduce the risk or limit the consequences of a similar SE. Validation of criteria showed substantial interobserver agreement. The SE analysis reports (n=115) contained 442 recommendations, of which 64% failed to meet all criteria, and 28% of reports did not contain a single recommendation that met the criteria. Conclusion We developed and validated criteria for high-quality recommendations. The majority of recommendations did not meet our criteria. It was disconcerting to find that over a quarter of the investigations did not produce a single recommendation that met the criteria, not even in SEs with a fatal outcome. Healthcare providers have an obligation to prevent SEs, and certainly their recurrence. We anticipate that using these criteria to determine the potential of recommendations will aid in this endeavour.