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首页> 外文期刊>BMJ Open Quality >Development of a prediction model for 30-day acute readmissions among older medical patients: the influence of social factors along with other patient-specific and organisational factors
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Development of a prediction model for 30-day acute readmissions among older medical patients: the influence of social factors along with other patient-specific and organisational factors

机译：老年医学患者30天急性再入院预测模型的开发：社会因素以及其他患者特定和组织因素的影响

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Background Readmission rate is one way to measure quality of care for older patients. Knowledge is sparse on how different social factors can contribute to predict readmission. We aimed to develop and internally validate a comprehensive model for prediction of acute 30-day readmission among older medical patients using various social factors along with demographic, organisational and health-related factors. Methods We performed an observational prospective study based on a group of 770 medical patients aged 65 years or older, who were consecutively screened for readmission risk factors at an acute care university hospital during the period from February to September 2012. Data on outcome and candidate predictors were obtained from clinical screening and administrative registers. We used multiple logistic regression analyses with backward selection of predictors. Measures of model performance and performed internal validation were calculated. Results Twenty percent of patients were readmitted within 30 days from index discharge. The final model showed that low educational level, along with male gender, contact with emergency doctor, specific diagnosis, higher Charlson Comorbidity Index score, longer hospital stay, cognitive problems, and medical treatment for thyroid disease, acid-related disorders, and glaucoma, predicted acute 30-day readmission. Area under the receiver operating characteristic curve (0.70) indicated acceptable discriminative ability of the model. Calibration slope was 0.98 and calibration intercept was 0.01. In internal validation analysis, both discrimination and calibration measures were stable. Conclusions We developed a model for prediction of readmission among older medical patients. The model showed that social factors in the form of educational level along with demographic, organisational and health-related factors contributed to prediction of acute 30-day readmissions among older medical patients.
机译：背景再入院率是衡量老年患者护理质量的一种方法。关于不同的社会因素如何有助于预测再入院的知识很少。我们旨在开发和内部验证一个综合模型，该模型使用各种社会因素以及人口统计，组织和健康相关因素来预测老年医学患者的急性30天再入院。方法我们对2012年2月至2012年9月在急诊大学医院连续筛查再次入院危险因素的770名65岁以上的医疗患者进行了一项观察性前瞻性研究。从临床检查和行政登记处获得。我们使用了多个逻辑回归分析，并向后选择了预测变量。计算了模型性能和进行的内部验证的度量。结果指数出院后30天内有20％的患者重新入院。最终模型显示，受教育程度较低，以及男性，与急诊医生接触，明确诊断，更高的查尔森合并症指数得分，住院时间更长，认知问题以及甲状腺疾病，酸相关性疾病和青光眼的药物治疗，预计急性30天再入院。接收器工作特性曲线（0.70）下的区域表示模型具有可接受的判别能力。校准斜率为0.98，校准截距为0.01。在内部验证分析中，判别和校准措施均稳定。结论我们建立了一个预测老年医学患者再入院的模型。该模型显示，受教育程度形式的社会因素以及人口，组织和健康相关因素有助于预测老年医学患者的急性30天再入院率。

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