Commonalities in rehabilitation data across diverse health conditions: a comparison of seven large European databases
DOI:
https://doi.org/10.2340/jrm.v58.45495Keywords:
decision support systems, clinical, precision medicine, predictive learning models, rehabilitationAbstract
Objective: To investigate whether rehabilitation data share common characteristics across different health conditions and care settings within the EU Horizon PREPARE project.
Design: Qualitative content analysis, with a comparative study of existing clinical databases.
Subjects/Patients: Individuals with hand and wrist disorders, idiopathic scoliosis, intermittent claudication, lower limb amputation, Parkinson’s disease or Parkinsonism, hip or knee replacement, and temporomandibular disorders.
Methods: Seven rehabilitation-oriented clinical databases were analysed using the International Classification of Functioning, Disability and Health (ICF) framework. Variables were categorized as outcomes, modifiers, or baseline measurements. Commonalities and differences across data domains were identified through iterative consensus meetings among PREPARE partners.
Results: Substantial heterogeneity was observed in data type and depth. Pain and quality of life were the most commonly reported outcomes, whereas discharge status and participation-related measures were rarely reported. The most prevalent modifiers were pharmacological treatments, orthoses or prostheses, and exercise-based interventions. All databases reported baseline information on diagnosis, anthropometry, and demographics; however, assessments of gait autonomy and daily activities were inconsistently documented.
Conclusion: Despite some overlapping domains, rehabilitation data collection remains fragmented and predominantly focused on biomedical aspects. Greater standardization and systematic inclusion of psychosocial and contextual variables are needed for robust predictive modelling and personalized rehabilitation.
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Copyright (c) 2026 Carlotte Kiekens, Helena Burger, Paolo Capodaglio, Maria G. Ceravolo, Esther Janssen, Greta Jurenaite, Calogero Malfitano, Federico Pennestri, Ruud Selles, Gianluca M. Tartaglia, Stefano Negrini
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