Nienke Maria Luijcks

Objectives: The functional resonance analysis method (FRAM) is increasingly used to analyse healthcare processes. FRAM uses four steps to analyse a process and its potential variability. We systematically reviewed studies using FRAM in healthcare on how the four steps in FRAM are reported, defined and supported by data. Design: Systematic review following the preferred reporting items for systematic reviews and meta-analyses 2020 guidelines. Data sources: Web of Science, PubMed, Embase, Scopus, PsycINFO, Dimensions and Lens were searched up to December 2025. Eligibility criteria for selecting studies: All peer-reviewed studies using FRAM in a healthcare context that presented a FRAM visualisation were included. The papers had to be written in English. Data extraction and synthesis: Two independent reviewers screened titles and abstracts, and subsequently the full text of selected papers. Data was extracted reporting on the steps of FRAM, how functions were supported by data, and the functions and couplings of the visualisations. Results: Sixty-eight papers were included, of which 20 (29%) reported at least one aspect of all four steps in FRAM. While most studies (85%) described how functions were supported by data, the methods used varied widely. Terminology was interpreted differently concerning variability, the output of variability and the effect of combined variability. Conclusion: Most FRAM studies in healthcare do not report all steps of FRAM, and interpretations of key terms differ. FRAM studies should more clearly describe which steps of the method are conducted, and how data is collected and analysed. Refinement of FRAM guidelines, particularly on data use and terminology, would enhance consistency and comparability across studies. PROSPERO registration number: CRD42024592858.

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 their 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 was also useful for formulating and testing improvement strategies. However, adjustments to the visualisations are necessary to enable professionals to participate in identifying improvement strategies.