A model for predicting delay in discharge of stroke patients

Abstract

Aims: To study the factors that predict delay in discharge (DD) for stroke victims when they are admitted to hospital and to build a model for predicting DD in our hospital.

Method: A retrospective study of 214 stroke victims admitted to the Physical Medicine and Rehabilitation Service (PMRS) of a general hospital between January 1, 1994, and December 31, 2001. Seventeen clinical and sociodemographic data were studied to determine which factors were predictors of DD: age, sex, type of stroke, side affected, sphincter control, ability to communicate, level of consciousness, deep sensitivity, antecedents of cardiovascular risk, delay before admission to the PMRS, initial functional state and solitude, whether the patient was employed prior to the cerebrovascular accident, and whether the patient's place of residence had any exterior architectural barriers.

Results: A total of 26.6% of patients experienced DD. Factors influencing DD were solitude (odds ratio [OR] 6; 95% confidence interval [CI] 2.2-16.1), an initial functional independence measure (FIM) below 50 (OR 4.5; 95% CI 2.3-8.9) and age greater than 75 years (OR 2.7; 95% CI 1.2-6.1). The best model for predicting DD comprises seven variables: solitude, initial FIM below 50, older than 75 years, left hemiparesis, exterior architectonic barriers at home, cardiovascular antecedents and sex (male). This model has a specificity of 89% and a sensitivity of 40%.

Conclusion: Solitude, low initial FIM and age older than 75 years influence DD for patients with stroke admitted to hospital. A model for predicting DD is described.