Predictors of length of stay for transurethral prostatectomy in Victoria.

M Z Ansari, C R MacIntyre, M J Ackland, E Chandraraj, D Hailey
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引用次数: 4

Abstract

Background: Transurethral resection of prostate (TURP) is among the top 10 surgical conditions that account for hospital admission in Victoria. Bed utilization for TURP is an increasing concern in current times. This paper describes trends in length of stay (LOS) and identifies predictors of LOS for TURP in Victoria.

Methods: Trends in TURP were studied using ICD-9-CM coded Victorian hospital morbidity data from public hospitals from 1987/88 to 1994/95. Detailed morbidity data from the same source for the financial year 1995/96 were used to study predictors of LOS by logistic regression.

Results: Length of stay decreased significantly between 1987 and 1995 from 10.6 to 6.1 days. The strongest predictor of increased LOS was admission through the emergency room (odds ratio (OR) 14.7; 95% confidence interval (CI) 11.8-18.3). Other significant predictors were older age, lower socio-economic status, presence of comorbid conditions, occurrence of procedural morbidity, and hospital type and location.

Conclusions: The trend in decreasing LOS may be explained by increasingly efficient bed management in hospitals who are faced with an increasing need for cost control. Advances in surgical techniques and peri-operative care have also contributed to the decrease in LOS. Other factors that influence LOS can be divided into three categories: intrinsic patient factors, such as co-morbid conditions; procedure-specific factors such as peri-operative morbidity; and intrinsic hospital factors relating to capacity and resources. Such determinants of LOS may be of value to policy makers when considering the effective application of newer methods for treatment of benign prostatic hyperplasia.

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维多利亚州经尿道前列腺切除术住院时间的预测因素。
背景:经尿道前列腺切除术(TURP)是维多利亚州住院的十大外科手术之一。TURP的床层利用率日益受到关注。本文描述了停留时间(LOS)的趋势,并确定了维多利亚州TURP的LOS预测因素。方法:采用ICD-9-CM编码的维多利亚州公立医院1987/88年至1994/95年的发病率数据,研究TURP的趋势。1995/96财政年度同一来源的详细发病率数据被用于通过逻辑回归研究LOS的预测因素。结果:住院时间从1987年的10.6天明显减少到1995年的6.1天。通过急诊室入院是LOS增加的最强预测因子(优势比(OR) 14.7;95%置信区间(CI) 11.8-18.3)。其他重要的预测因素包括年龄较大、社会经济地位较低、合并症的存在、程序性发病的发生以及医院类型和地点。结论:医院病床管理效率的提高可能解释了住院时间减少的趋势,医院面临着越来越多的成本控制需求。手术技术和围手术期护理的进步也有助于LOS的减少。影响LOS的其他因素可分为三类:患者的内在因素,如合并症;手术特定因素,如围手术期发病率;以及与医院能力和资源相关的内在因素。这些LOS的决定因素可能对决策者在考虑有效应用治疗良性前列腺增生的新方法时有价值。
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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