Determining the Length of Stay and Duration of Illness for Psychiatric Inpatients Using Multivariate Modelling

A. Sabharwal, Sakshi Kaushik
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Abstract

Mental and behavioural disorders is a significant contributor of global burden of disease. As per WHO estimates, this burden is likely to increase by 15 percent by 2020, significantly impacting health and major social, human rights and economic consequences in all countries of the world. This paper provides a procedure for estimation of length of stay (LOS) in the hospital, total duration of illness (TDI) and recent duration of illness (RDI) using multivariate normal (MVN) and bivariate (BVN) normal distributions. To accomplish this, a retrospective data of 146 patients with complete record history, diagnosed with mental and behavioural disorders (as per APA’s DSM-V as well as the WHO’s ICD-10) is collected from the Department of Psychiatry, Lady Hardinge Medical College & Smt. S.K, Hospital, New Delhi, India for the calendar year 2013-2014. The estimated values of the above mentioned variables are found to be consistent with the observed values. Finally MVN distribution is applied to estimate the variables LOS and TDI for the patients for whom the information on these variables is not known. The model derived in this paper will facilitate the medical fraternity to not only guide the patients about their approximate length of stay in the hospital at the time of admission, but also assist them in development and management of appropriate interventions for patients.
用多变量模型确定精神科住院病人的住院时间和病程
精神和行为障碍是造成全球疾病负担的一个重要因素。据世卫组织估计,到2020年,这一负担可能会增加15%,严重影响世界各国的健康以及重大的社会、人权和经济后果。本文采用多变量正态分布(MVN)和双变量正态分布(BVN)估计住院时间(LOS)、总病程(TDI)和最近病程(RDI)。为了实现这一目标,从哈丁格夫人医学院精神病学系收集了146名具有完整病史的患者的回顾性数据,这些患者被诊断患有精神和行为障碍(根据APA的DSM-V和WHO的ICD-10)。2013-2014历年印度新德里医院s.k.。发现上述变量的估计值与观测值一致。最后,应用MVN分布对未知变量LOS和TDI的患者进行估计。本文所建立的模型不仅有助于医学界在患者入院时指导他们的大致住院时间,而且有助于他们为患者制定和管理适当的干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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