Lagoe R J, Arnold K A, Noetscher C M
Community-General Hospital, Syracuse, NY, USA.
Nurs Econ. 1999 Mar-Apr;17(2):75-84, 102.
The authors demonstrated that length of stay histograms can provide considerably more benchmark information concerning hospital lengths of stay than numerical benchmarks. Examples of histograms described the complete distribution of hospital stays, as well as levels of outliers, rather than simple numerical averages. Gathering such data led to a clearer understanding of the significant LOS impact of certain DRG outliers in the two different hospitals in Syracuse, NY. Given that the other two communities represented, Seattle, Washington and San Diego, California, were more influenced by extensive managed care penetration, variations in histogram data were less in evidence there. Histograms were designed with bars to show LOS distributions at the 50th, 75th, and 90th percentiles for each of the above DRGs. The greatest variations could be shown when comparing the 1997 LOS data on the various DRGs at the two Syracuse hospitals. At both hospitals the presence of a large contingent of outliers (for different types of mostly medical patients) could be seen as the major factor in driving up their overall LOS.
作者证明，住院时间直方图能够比数值基准提供更多有关医院住院时间的基准信息。直方图的示例描述了住院时间的完整分布以及异常值水平，而不仅仅是简单的数值平均值。收集此类数据有助于更清楚地了解纽约州锡拉丘兹市两家不同医院中某些诊断相关分组（DRG）异常值对住院时间的重大影响。鉴于所代表的其他两个社区，华盛顿州西雅图市和加利福尼亚州圣地亚哥市，受广泛的管理式医疗渗透影响更大，那里的直方图数据变化不太明显。直方图设计为用条形表示上述每个DRG在第50、75和90百分位数处的住院时间分布。比较锡拉丘兹市两家医院2007年各DRG的住院时间数据时，差异最为明显。在两家医院，大量异常值（主要针对不同类型的内科患者）的存在都被视为推高其总体住院时间的主要因素。
