Lorch Scott A, Silber Jeffrey H, Even-Shoshan Orit, Millman Andrea
Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Health Serv Res. 2009 Apr;44(2 Pt 1):519-41. doi: 10.1111/j.1475-6773.2008.00940.x. Epub 2008 Dec 30.
To determine whether travel variables could explain previously reported differences in lengths of stay (LOS), readmission, or death at children's hospitals versus other hospital types.
Hospital discharge data from Pennsylvania between 1996 and 1998.
A population cohort of children aged 1-17 years with one of 19 common pediatric conditions was created (N=51,855). Regression models were constructed to determine difference for LOS, readmission, or death between children's hospitals and other types of hospitals after including five types of additional illness severity variables to a traditional risk-adjustment model.
With the traditional risk-adjustment model, children traveling longer to children's or rural hospitals had longer adjusted LOS and higher readmission rates. Inclusion of either a geocoded travel time variable or a nongeocoded travel distance variable provided the largest reduction in adjusted LOS, adjusted readmission rates, and adjusted mortality rates for children's hospitals and rural hospitals compared with other types of hospitals.
Adding a travel variable to traditional severity adjustment models may improve the assessment of an individual hospital's pediatric care by reducing systematic differences between different types of hospitals.
确定旅行变量是否可以解释先前报告的儿童医院与其他类型医院在住院时间(LOS)、再入院率或死亡率方面的差异。
1996年至1998年宾夕法尼亚州的医院出院数据。
创建了一个1至17岁患有19种常见儿科疾病之一的儿童人群队列(N = 51,855)。构建回归模型,在传统风险调整模型中纳入五种额外的疾病严重程度变量后,确定儿童医院与其他类型医院在LOS、再入院率或死亡率方面的差异。
使用传统风险调整模型时,前往儿童医院或乡村医院路途较远的儿童调整后的住院时间更长,再入院率更高。与其他类型医院相比,纳入地理编码旅行时间变量或非地理编码旅行距离变量可使儿童医院和乡村医院的调整后住院时间、调整后再入院率和调整后死亡率降幅最大。
在传统严重程度调整模型中加入旅行变量,可能会通过减少不同类型医院之间的系统差异,改善对个别医院儿科护理的评估。