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Patients' readiness for discharge: Predictors and effects on unplanned readmissions, emergency department visits and death.
Journal of Nursing Management 2018 September
AIM: To determine the variables that affect patients' perceptions about their readiness for discharge and to elucidate the effects of these perceptions on patient outcomes such as unplanned readmission to the hospital, emergency department visits and death within 30 days after discharge.
BACKGROUND: In recent years, it has become even more important to assess patients' readiness for discharge as patients tend to be discharged more quickly.
METHODS: For the determination of patients' self-assessment, the Readiness for Hospital Discharge Scale/Short Form was utilized. This 1-year prospective cohort study included 1,601 patients. Data were analysed using a chi-square test, Mann-Whitney U test, univariate logistic regression analysis and multiple logistic regression analysis.
RESULTS: The results of multiple logistic regression analysis revealed that age, sex, marital status, educational status, presence of someone to help at home after discharge and length of stay were predictors of patients' readiness for hospital discharge. Furthermore, being unready for discharge increased the risk of 30 day unplanned readmission and 30 day death.
CONCLUSIONS: Considering these predictors, patients' perceptions of readiness for discharge must be assessed before deciding to discharge them.
IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers can consider the predictors of patients' readiness for discharge, thus the risk of unplanned readmission and death may be reduced.
BACKGROUND: In recent years, it has become even more important to assess patients' readiness for discharge as patients tend to be discharged more quickly.
METHODS: For the determination of patients' self-assessment, the Readiness for Hospital Discharge Scale/Short Form was utilized. This 1-year prospective cohort study included 1,601 patients. Data were analysed using a chi-square test, Mann-Whitney U test, univariate logistic regression analysis and multiple logistic regression analysis.
RESULTS: The results of multiple logistic regression analysis revealed that age, sex, marital status, educational status, presence of someone to help at home after discharge and length of stay were predictors of patients' readiness for hospital discharge. Furthermore, being unready for discharge increased the risk of 30 day unplanned readmission and 30 day death.
CONCLUSIONS: Considering these predictors, patients' perceptions of readiness for discharge must be assessed before deciding to discharge them.
IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers can consider the predictors of patients' readiness for discharge, thus the risk of unplanned readmission and death may be reduced.
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