Farhadi Hassankiadeh Roghaye, Kazemnejad Anoshirvan, Gholami Fesharaki Mohammad, Kargar Jahromi Siamak, Vahabi Nasim
Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Shariati Hospital, Medical Education Research Center, Tehran, Iran.
Med J Islam Repub Iran. 2017 Dec 17;31:91. doi: 10.14196/mjiri.31.91. eCollection 2017.
The effective use of limited health care resources is of prime importance. Assessing the length of stay (LOS) is especially important in organizing hospital services and health system. This study was conducted to identify predictors of LOS among patients who were admitted to a general surgical unit. In this cross-sectional study, the sample included all patients who were admitted to the general surgical unit of Shariati hospital in 2013 (n= 334). To determine the factors affecting LOS, Zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), and zero-inflated generalized Poisson (ZIGP) regression models were fitted using R software, and then the best model was selected. Among all 334 patients, the mean (±SD) age of the patients was 45.2 (±16.47) years and 220 (65.9%) of them were male. The results revealed that based on ZIGP model, type of surgery (appendicitis, abdomen and its contents, hemorrhoids, lung, and skin), type of insurance, comorbid diseases (hypertension, heart disease, and hyperlipidemia), place of residence (local and non-local), age, and number of tests had significant effects on the LOS of GS patients. According to the Akaike information criterion (AIC) in each fitted model, it was found that ZIGP regression model is more appropriate than ZIP and ZINB regression models in assessing LOS in GS patients, especially due to the presence of excess zeros and overdispersion in count data.
有效利用有限的医疗资源至关重要。评估住院时间（LOS）在组织医院服务和卫生系统方面尤为重要。本研究旨在确定普通外科病房收治患者住院时间的预测因素。在这项横断面研究中，样本包括2013年入住沙里亚蒂医院普通外科病房的所有患者（n = 334）。为了确定影响住院时间的因素，使用R软件拟合了零膨胀泊松（ZIP）、零膨胀负二项式（ZINB）和零膨胀广义泊松（ZIGP）回归模型，然后选择最佳模型。在所有334例患者中，患者的平均（±标准差）年龄为45.2（±16.47）岁，其中220例（65.9%）为男性。结果显示，基于ZIGP模型，手术类型（阑尾炎、腹部及其内容物、痔疮、肺部和皮肤）、保险类型、合并疾病（高血压、心脏病和高脂血症）、居住地（本地和非本地）、年龄和检查次数对普通外科患者的住院时间有显著影响。根据每个拟合模型中的赤池信息准则（AIC），发现在评估普通外科患者的住院时间方面，ZIGP回归模型比ZIP和ZINB回归模型更合适，特别是由于计数数据中存在过多零值和过度离散的情况。
