OBJECTIVES: To synthesize the existing use, definitions, and variation in the application of hospital-free days (HFDs) as an outcome measure in randomized controlled trials (RCTs) of critically ill adults. DATA SOURCES: Trial registries (ISRCTN, ClinicalTrials.gov ) and electronic databases (CENTRAL, MEDLINE, Embase, and CINAHL PLUS). STUDY SELECTION: We included trial registrations, protocols, or articles reporting RCTs that included patients admitted to an adult ICU and had any variation of HFD as a primary or secondary outcome. DATA EXTRACTION: Data collected included definition of HFD, statistical analysis, minimal clinically important difference, method of data collection, and loss to follow-up. Risk of bias in the included studies was assessed using the relevant domains of the Cochrane Risk of Bias 2 tool (blinding of outcome assessment, incomplete outcome data, and selective reporting). Data were synthesized quantitatively using frequencies and percentages. DATA SYNTHESIS: We identified 110 eligible studies. We found considerable variability in how HFD was defined and reported. Incomplete reporting was common, with 69 studies (62.7%) not reporting all three individual components of HFD. Length of stay was omitted most frequently. Risk of bias related to outcome assessment and measurement was considered low. Fifty-two studies (47.3%) collected HFD data from routine healthcare records. The most common follow-up time points were 28 and 90 days. Over half of all studies (56 [50.9%]) did not report the number of HFD counted if a patient died during follow-up. CONCLUSIONS: This systematic review highlights the heterogeneity in the definition, reporting, and analysis of HFD. We propose guidance for the use of HFD and highlight areas for future research to allow standardization in the use and reporting of HFD in critical care research.
Journal article
2025-12-01T00:00:00+00:00
53
e2686 - e2697
critical illness, follow-up, outcomes, systematic review, Humans, Critical Care, Randomized Controlled Trials as Topic, Outcome Assessment, Health Care, Intensive Care Units, Length of Stay, Critical Illness