Medical science monitor : international medical journal of experimental and clinical research
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BACKGROUND This study aimed to develop a risk prediction model for prolonged length of stay (LOS) in stroke patients in 50 inpatient rehabilitation centers in 20 provinces across mainland China based on the International Classification of Functioning, Disability, and Health (ICF) Generic Set case mix on admission. MATERIAL AND METHODS In this cohort study, 383 stroke patients were included from inpatient rehabilitation settings of 50 hospitals across mainland China. Independent predictors of prolonged LOS were identified using multivariate logistic regression analysis. ⋯ The prediction model showed acceptable discrimination shown by an area under the curve (AUC) of 0.699 (95% CI, 0.646-0.752) and calibration (χ²=11.66; P=0.308). CONCLUSIONS The risk prediction model for prolonged LOS in stroke patients in 50 rehabilitation centers in China, based on the ICF Generic Set, showed that the scores for the type of medical insurance and the performance of daily activities (ICF, d230) on admission were independent predictors of prolonged LOS. This prediction model may allow stakeholders to estimate the risk of prolonged LOS on admission quantitatively, facilitate the financial planning, treatment regimens during hospitalization, referral after discharge, and reimbursement.