M Z Ansari, C R MacIntyre, M J Ackland, E Chandraraj, D Hailey
{"title":"Predictors of length of stay for transurethral prostatectomy in Victoria.","authors":"M Z Ansari, C R MacIntyre, M J Ackland, E Chandraraj, D Hailey","doi":"10.1046/j.1440-1622.1998.01467.x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":22494,"journal":{"name":"The Australian and New Zealand journal of surgery","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1998-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Australian and New Zealand journal of surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1046/j.1440-1622.1998.01467.x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.