克朗巴赫阿尔法
医学
比例(比率)
探索性因素分析
急诊科
心理干预
可靠性(半导体)
验证性因素分析
出院
病历
急诊医学
护理部
医疗急救
家庭医学
心理测量学
结构方程建模
临床心理学
统计
重症监护医学
放射科
功率(物理)
物理
量子力学
数学
作者
Kathleen L. Bobay,Marianne Weiss,Debra L. Oswald,Olga Yakusheva
出处
期刊:Nursing Research
[Ovid Technologies (Wolters Kluwer)]
日期:2018-07-01
卷期号:67 (4): 305-313
被引量:15
标识
DOI:10.1097/nnr.0000000000000293
摘要
Statistical models for predicting readmissions have been published for high-risk patient populations but typically focus on patient characteristics; nurse judgment is rarely considered in a formalized way to supplement prediction models.The purpose of this study was to determine psychometric properties of long and short forms of the Registered Nurse Readiness for Hospital Discharge Scale (RN-RHDS), including reliability, factor structure, and predictive validity.Data were aggregated from two studies conducted at four hospitals in the Midwestern United States. The RN-RHDS was completed within 4 hours before hospital discharge by the discharging nurse. Data on readmissions and emergency department visits within 30 days were extracted from electronic medical records.The RN-RHDS, both long and short forms, demonstrate acceptable reliability (Cronbach's alphas of .90 and .73, respectively). Confirmatory factor analysis demonstrated less than adequate fit with the same four-factor structure observed in the patient version. Exploratory factor analysis identified three factors, explaining 60.2% of the variance. When nurses rate patients as less ready to go home (<7 out of 10), patients are 6.4-9.3 times more likely to return to the hospital within 30 days, in adjusted models.The RN-RHDS, long and short forms, can be used to identify medical-surgical patients at risk for potential unplanned return to hospital within 30 days, allowing nurses to use their clinical judgment to implement interventions prior to discharge. Use of the RN-RHDS could enhance current readmission risk prediction models.
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