N.M. Luijcks
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Building a functional resonance analysis method (FRAM) in healthcare
A systematic review on how steps are reported, defined and supported by data
Review
(2026)
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N.M. Luijcks, Tom Bazuin, A. Adriaensen, Annelies Visser , Dave A. Dongelmans, J. Groeneweg, Maarten J. van der Laan, P.J. Marang-van de Mheen
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. ...
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. ...
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.
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.
Formal responsibility and task execution
The importance of modelling task delegation in FRAM to optimise the identification of potential improvement strategies
Journal article
(2026)
-
N. M. Luijcks, T. Bazuin, P. J. Marang-van de Mheen, M. J. van der Laan, J. Groeneweg
Objective To investigate how task delegation for perioperative anticoagulation management is reported in protocols and daily practice, and how this translates to additional information in work-as-imagined and work-as-done using FRAM to identify improvement possibilities. MethodsExisting FRAM visualisations of perioperative anticoagulant management in a Dutch academic hospital were extended to include task delegation in protocols using document analysis and in daily practice using a focus group of eight healthcare professionals, analysed using content analysis.ResultsDistinguishing between formal responsibility and task execution revealed additional functions and roles in both work-as-done and work-as-imagined, resulting in more discrepancies between work-as-done and work-as-imagined. Professionals experienced responsibility for delegated tasks, even without formal accountability, and needed to feel qualified and capable as well as complete clear information to accept these tasks. ConclusionsIncluding task delegation in FRAM models improves the understanding of healthcare processes, communication about distribution of responsibilities and thereby development of more effective improvement strategies.
...
Objective
To investigate how task delegation for perioperative anticoagulation management is reported in protocols and daily practice, and how this translates to additional information in work-as-imagined and work-as-done using FRAM to identify improvement possibilities.
Methods
Existing FRAM visualisations of perioperative anticoagulant management in a Dutch academic hospital were extended to include task delegation in protocols using document analysis and in daily practice using a focus group of eight healthcare professionals, analysed using content analysis.
Results
Distinguishing between formal responsibility and task execution revealed additional functions and roles in both work-as-done and work-as-imagined, resulting in more discrepancies between work-as-done and work-as-imagined. Professionals experienced responsibility for delegated tasks, even without formal accountability, and needed to feel qualified and capable as well as complete clear information to accept these tasks.
Conclusions
Including task delegation in FRAM models improves the understanding of healthcare processes, communication about distribution of responsibilities and thereby development of more effective improvement strategies.
Using FRAM visualisations in quality improvement projects
Identifying and testing strategies to improve anticoagulant use in the perioperative process
Journal article
(2025)
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N.M. Luijcks, Annelies Visser , Dave A. Dongelmans, D.M.G. van Dongen, E.L. de Graaf, J. Groeneweg, Maarten J. van der Laan, P.J. Marang-van de Mheen
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. ...
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
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.
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.
From FRAM Guidelines to Reality
Incorporating Stakeholder Variability in Work-as-Done in Healthcare
Journal article
(2025)
-
N.M. Luijcks, P.J. Marang-van de Mheen, Maarten J. van der Laan, J. Groeneweg
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: 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.