An Econometric Analysis of the Impact of Telecare on the Length of Stay in Hospital

Kevin Momanyi
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Abstract

This paper presents some preliminary results of a study investigating the effect of telecare on the length of stay in hospital using linked administrative health and social care data in Scotland. We make various assumptions about the probability distribution of the outcome measure and formulate three Negative Binomial Models to that effect i.e. a basic Negative Binomial Model, a zero-inflated Negative Binomial Model and a zero-truncated Negative Binomial Model. We then bring the models to data and estimate them using a strategy that controls for the effects of confounding variables and unobservable factors. These models provide an alternative to the Propensity Score Matching technique used by the previous studies. The empirical results show that telecare users are expected to spend a shorter time in hospital than non-users, holding other factors constant. The results also show that older individuals, males, rural residents and individuals with comorbidities have a longer length of stay in hospital, on average, than their counterparts, all things equal. Future research will involve conducting a sub-group analysis, investigating the effectiveness of various telecare devices and determining the impact of telecare on admission to hospital.
远程医疗对住院时间影响的计量经济学分析
本文介绍了一项研究的一些初步结果,该研究利用苏格兰相关的行政卫生和社会保健数据调查了远程医疗对住院时间的影响。我们对结果测度的概率分布进行了各种假设,并为此建立了三种负二项模型,即基本负二项模型、零膨胀负二项模型和零截断负二项模型。然后,我们将模型带入数据,并使用控制混杂变量和不可观察因素影响的策略来估计它们。这些模型为以前的研究使用的倾向评分匹配技术提供了另一种选择。实证结果表明,在保持其他因素不变的情况下,远程医疗用户比非远程医疗用户预计在医院花费的时间更短。结果还表明,在所有条件相同的情况下,老年人、男性、农村居民和有合并症的人平均住院时间比他们的同行更长。未来的研究将包括进行分组分析,调查各种远程医疗设备的有效性,并确定远程医疗对入院的影响。
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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