Well-being of healthcare professionals (HCPs) is vital for care quality, staff retention and overall healthcare system effectiveness. This study aims to identify the organisational and workplace variables associated with sick leave and measures of engagement of HCPs on department level within a single Dutch academic hospital.

Cross-sectional study using routinely collected organisational data.

A tertiary-care academic hospital in the Netherlands.

25 clinical departments were included. Department level variables were derived from routinely collected hospital databases. Availability of data varied across variables. Analysis included information on patient population, human resources, care processes, quality of care and employee and patient experiences to assess differences, correlations and predictors for sick leave and engagement.

Primary outcome measures were (1) sick leave (%) and (2) engagement, assessed through two staff-survey items (vitality and connectedness; 0–10 Numeric Rating Scale). Both outcomes were analysed at department level.

Employee population data showed the most consistent patterns across analyses. Departments with higher staffing capacity had higher sick leave and lower engagement in group comparisons (p=0.009, p=0.030, respectively). In multivariable models, higher staffing capacity remained associated with increased sick leave (B=1.38, 95% CI 0.53 to 2.23, p=0.003). Engagement was positively associated with higher inflow (B=0.92, 95% CI 0.06 to 1.77, p=0.037) and negatively associated with outflow (B = –1.36, 95% CI –2.08 to –0.63, p=0.001). No consistent associations were found with patient population and patient experience measures.

Workforce-related factors, particularly staffing capacity and inflow and outflow, are strongly linked to sick leave and engagement. Routinely collected hospital data can be used to identify at-risk departments and inform targeted strategies for improving workforce sustainability. Future studies should explore more granular, team-level data to better support staff well-being and care quality.

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.

Systematic review following the preferred reporting items for systematic reviews and meta-analyses 2020 guidelines.

Web of Science, PubMed, Embase, Scopus, PsycINFO, Dimensions and Lens were searched up to December 2025.

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.

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.

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.

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.

CRD42024592858.