INTEGRATION OF HOSPITAL MOBILITY SCALES WITH THE INTERNATIONAL CLASSIFICATION OF FUNCTIONING, DISABILITY AND HEALTH: A COMPARATIVE ANALYSIS

Abstract

Background: Functional mobility assessment in hospitalized patients, particularly in intensive care units, represents a fundamental component of evidence-based practice. The proliferation of assessment instruments, although beneficial, presents significant challenges for standardization, interprofessional communication, and comparative research. The International Classification of Functioning, Disability and Health (ICF) provides a theoretical framework and standardized language for describing functionality, representing an opportunity to establish correspondences between different functional assessment instruments. Objective: To establish a unified framework integrating six hospital mobility scales with the ICF, aiming to standardize functional assessment in critically ill patients. Methods: Systematic linkage analysis between ICU Mobility Scale (IMS), Johns Hopkins Highest Level of Mobility (JH-HLM), Perme Intensive Care Unit Mobility Score, Surgical Optimal Mobility Score (SOMS), Chelsea Critical Care Physical Assessment Tool (CPAx), and Physical Function in Intensive Care Test (PFIT) with ICF codes, following international guidelines for instrument mapping. Two researchers with experience in hospital rehabilitation independently analyzed each scale item, assigning relevant ICF codes, with disagreements resolved by consensus with a third expert researcher. Statistical analyses included Pearson correlation, principal component analysis, and hierarchical clustering. Results: Four functional groups (A-D) were identified representing progressive mobility levels: A (Critical Mobility), B (Assisted Mobility), C (Partial Mobility), and D (Independent Mobility), establishing correspondences between the six scales' scores and specific ICF codes. Correlation analysis revealed strong associations between all instruments (r=0.82 to 0.94), with the highest correlation between IMS and JH-HLM (r=0.94). Principal component analysis demonstrated that the first component explained 78% of total variance, confirming strong unidimensionality of the hospital mobility construct. Hierarchical clustering evidenced two main clusters: short scales focused on basic progressions (IMS, JH-HLM, SOMS, PFIT) and comprehensive scales incorporating multiple domains (Perme, CPAx). Conclusion: The proposed framework provides a common language for clinical documentation and research, facilitating interprofessional communication and longitudinal monitoring of critically ill patients across different care contexts. The integration proved feasible and scientifically grounded, supported by strong statistical convergence and clinical coherence of identified clusters, although additional empirical validation in multicenter studies is necessary for definitive consolidation of the proposal.