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内科患者再次入院的预测因素:安德森模型的应用。

Predictors of hospital readmissions in internal medicine patients: Application of Andersen's Model.

作者信息

Kaya Sıdıka, Sain Guven Gulay, Aydan Seda, Toka Onur

机构信息

Department of Health Care Management, Faculty of Economics and Administrative Sciences, Hacettepe University, Ankara, Turkey.

Department of General Internal Medicine, Faculty of Medicine, Hacettepe University, Ankara, Turkey.

出版信息

Int J Health Plann Manage. 2019 Jan;34(1):370-383. doi: 10.1002/hpm.2648. Epub 2018 Sep 17.

Abstract

OBJECTIVE

This study aimed to identify predictors of internal medicine patients' readmission to hospital, using Andersen's behavioral model.

METHODS

This prospective cohort study included 2622 patients aged ≥18 years, who were admitted to internal medicine wards at a university hospital between 1 February 2015 and 31 January 2016. Independent variables were divided into four groups (predisposing, enabling, need, and utilization), based on Andersen's model, and included in stepwise logistic regression analysis.

RESULTS

Younger age, male sex, a main diagnosis of neoplasm, longer length of stay, higher comorbidity scores, and weaker coping ability predicted all readmission. Predictors of unplanned readmission included having someone to help at home following discharge, comorbidity scores, and length of stay. Predictors of unplanned, related, and preventable readmissions included having someone to help at home following discharge, having a regular physician, and the main diagnosis at discharge. The most powerful predictors influencing readmission were need-related variables.

CONCLUSION

Although some predictors of readmission were unalterable, they could be used to identify high-risk patients. Innovative approaches targeting discharge planning and postdischarge care for patients with high comorbidity scores and long length of stay could reduce internal medicine patients' unplanned readmission.

摘要

目的

本研究旨在运用安德森行为模型确定内科患者再次入院的预测因素。

方法

这项前瞻性队列研究纳入了2622名年龄≥18岁的患者,这些患者于2015年2月1日至2016年1月31日期间入住一家大学医院的内科病房。根据安德森模型,将自变量分为四组( predisposing、 enabling、 need和 utilization),并纳入逐步逻辑回归分析。

结果

年龄较小、男性、肿瘤主要诊断、住院时间较长、合并症评分较高以及应对能力较弱可预测所有再次入院情况。计划外再次入院的预测因素包括出院后家中有人帮忙、合并症评分和住院时间。计划外、相关且可预防的再次入院的预测因素包括出院后家中有人帮忙、有固定的医生以及出院时的主要诊断。影响再次入院的最有力预测因素是与需求相关的变量。

结论

虽然一些再次入院的预测因素无法改变,但它们可用于识别高危患者。针对合并症评分高和住院时间长的患者的出院计划和出院后护理的创新方法可减少内科患者的计划外再次入院。

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