Hariman Keith, Cheng Koi Man, Lam Jenny, Leung Siu Kau, Lui Simon S Y
Department of General Adult Psychiatry, Castle Peak Hospital, Hong Kong, China.
BJPsych Open. 2020 Jan 28;6(1):e13. doi: 10.1192/bjo.2019.97.
Unplanned readmissions rates are an important indicator of the quality of care provided in a psychiatric unit. However, there is no validated risk model to predict this outcome in patients with psychotic spectrum disorders.
This paper aims to establish a clinical risk prediction model to predict 28-day unplanned readmission via the accident and emergency department after discharge from acute psychiatric units for patients with psychotic spectrum disorders.
Adult patients with psychotic spectrum disorders discharged within a 5-year period from all psychiatric units in Hong Kong were included in this study. Information on the socioeconomic background, past medical and psychiatric history, current discharge episode and Health of the Nation Outcome Scales (HoNOS) scores were used in a logistic regression to derive the risk model and the predictive variables. The sample was randomly split into two to derive (n = 10 219) and validate (n = 10 643) the model.
The rate of unplanned readmission was 7.09%. The risk factors for unplanned readmission include higher number of previous admissions, comorbid substance misuse, history of violence and a score of one or more in the discharge HoNOS overactivity or aggression item. Protective factors include older age, prescribing clozapine, living with family and relatives after discharge and imposition of conditional discharge. The model had moderate discriminative power with a c-statistic of 0.705 and 0.684 on the derivation and validation data-set.
The risk of readmission for each patient can be identified and adjustments in the treatment for those with a high risk may be implemented to prevent this undesirable outcome.
非计划再入院率是精神科护理质量的一项重要指标。然而,尚无经过验证的风险模型可用于预测精神分裂症谱系障碍患者的这一结果。
本文旨在建立一个临床风险预测模型,以预测精神分裂症谱系障碍患者从急性精神科病房出院后28天内通过急诊科的非计划再入院情况。
本研究纳入了香港所有精神科病房在5年内出院的成年精神分裂症谱系障碍患者。社会经济背景、既往病史和精神病史、当前出院情况以及国民健康结果量表(HoNOS)评分等信息被用于逻辑回归分析,以得出风险模型和预测变量。样本被随机分为两组,一组用于推导模型(n = 10219),另一组用于验证模型(n = 10643)。
非计划再入院率为7.09%。非计划再入院的风险因素包括既往入院次数较多、合并物质滥用、暴力史以及出院时HoNOS多动或攻击项目得分达到1分或更高。保护因素包括年龄较大、开具氯氮平、出院后与家人和亲属同住以及实施有条件出院。该模型具有中等判别能力,在推导数据集和验证数据集上的c统计量分别为0.705和0.684。
可以识别每位患者的再入院风险,并对高风险患者的治疗进行调整,以预防这一不良后果。