Department of Psychiatry, University of Toronto, Toronto, Canada.
Institute for Clinical Evaluative Sciences, Toronto, Canada.
Soc Psychiatry Psychiatr Epidemiol. 2018 Feb;53(2):139-149. doi: 10.1007/s00127-017-1450-5. Epub 2017 Nov 9.
Psychiatric readmission is a common negative outcome. Predictors of readmission may differ by sex. This study aimed to derive and internally validate sex-specific models to predict 30-day psychiatric readmission.
We used population-level health administrative data to identify predictors of 30-day psychiatric readmission among women (n = 33,353) and men (n = 32,436) discharged from all psychiatric units in Ontario, Canada (2008-2011). Predictor variables included sociodemographics, health service utilization, and clinical characteristics. Using derivation data sets, multivariable logistic regression models were fit to determine optimal predictive models for each sex separately. Results were presented as adjusted odds ratios (aORs) and 95% confidence intervals (CI). The multivariable models were then applied in the internal validation data sets.
The 30-day readmission rates were 9.3% (women) and 9.1% (men). Many predictors were consistent between women and men. For women only, personality disorder (aOR 1.21, 95% CI 1.03-1.42) and positive symptom score (aOR 1.41, 95% CI 1.09-1.82 for score of 1 vs. 0; aOR 1.44, 95% CI 1.26-1.64 for ≥ 2 vs. 0) increased odds of readmission. For men only, self-care problems at admission (aOR 1.20, 95% CI 1.06-1.36) and discharge (aOR 1.44, 95% CI 1.26-1.64 for score of 1 vs. 0; aOR 1.79, 95% CI 1.17-2.74 for 2 vs. 0), and mild anxiety rating (score of 1 vs. 0: aOR 1.30, 95% CI 1.02-1.64, derivation model only) increased odds of readmission. Models had moderate discriminative ability in derivation and internal validation samples for both sexes (c-statistics 0.64-0.65).
Certain key predictors of psychiatric readmission differ by sex. This knowledge may help to reduce psychiatric hospital readmission rates by focusing interventions.
精神科再入院是一种常见的负面结果。再入院的预测因素可能因性别而异。本研究旨在制定并内部验证适用于预测女性和男性 30 天精神科再入院的性别特异性模型。
我们使用人群水平的健康管理数据，确定了加拿大安大略省所有精神科病房出院的女性（n=33353）和男性（n=32436）30 天内精神科再入院的预测因素。预测变量包括社会人口统计学、卫生服务利用和临床特征。使用推导数据集，对多变量逻辑回归模型进行拟合，以确定每个性别各自的最佳预测模型。结果以调整后的优势比（aOR）和 95%置信区间（CI）表示。然后将多变量模型应用于内部验证数据集。
30 天再入院率为 9.3%（女性）和 9.1%（男性）。许多预测因素在女性和男性之间是一致的。仅对女性而言，人格障碍（aOR 1.21，95%CI 1.03-1.42）和阳性症状评分（aOR 1.41，95%CI 1.09-1.82，评分 1 与 0 相比；aOR 1.44，95%CI 1.26-1.64，评分≥2 与 0 相比）增加了再入院的几率。仅对男性而言，入院时（aOR 1.20，95%CI 1.06-1.36）和出院时（aOR 1.44，95%CI 1.26-1.64，评分 1 与 0 相比；aOR 1.79，95%CI 1.17-2.74，评分 2 与 0 相比）自我护理问题以及轻度焦虑评分（评分 1 与 0 相比：aOR 1.30，95%CI 1.02-1.64，仅推导模型）增加了再入院的几率。在推导和内部验证样本中，两种性别模型的区分能力均为中等（C 统计量为 0.64-0.65）。
某些精神科再入院的关键预测因素因性别而异。这些知识可能有助于通过重点干预措施降低精神科住院再入院率。
