Department of Health Systems Management, Tulane University, 1440 Canal Street, Suite 1900, New Orleans, LA 70112, USA.
Health Serv Res. 2011 Oct;46(5):1575-91. doi: 10.1111/j.1475-6773.2011.01259.x. Epub 2011 Mar 30.
To assess the internal consistency and agreement between the Health Care Information and Management Systems Society (HIMSS) and the Leapfrog computerized provider order entry (CPOE) data.
Secondary hospital data collected by HIMSS Analytics, the Leapfrog Group, and the American Hospital Association from 2005 to 2007.
Dichotomous measures of full CPOE status were created for the HIMSS and Leapfrog datasets in each year. We assessed internal consistency by calculating the percent of full adopters in a given year that report full CPOE status in subsequent years. We assessed the level of agreement between the two datasets by calculating the κ statistic and McNemar's test. We examined responsiveness by assessing the change in full CPOE status rates, over time, reported by HIMSS and Leapfrog data, respectively.
Findings indicate minimal agreement between the two datasets regarding positive hospital CPOE status, but adequate agreement within a given dataset from year to year. Relative to each other, the HIMSS data tend to overestimate increases in full CPOE status over time, while the Leapfrog data may underestimate year over year increases in national CPOE status.
Both Leapfrog and HIMSS data have strengths and weaknesses. Those interested in studying outcomes associated with CPOE use or adoption should be aware of the strengths and limitations of the Leapfrog and HIMSS datasets. Future development of a standard definition of CPOE status in hospitals will allow for a more comprehensive validation of these data.
评估医疗保健信息和管理系统学会(HIMSS)和 Leapfrog 计算机化医嘱录入(CPOE)数据之间的内部一致性和一致性。
HIMSS Analytics、Leapfrog 集团和美国医院协会在 2005 年至 2007 年期间收集的二级医院数据。
在每年的 HIMSS 和 Leapfrog 数据集中创建了 CPOE 完全采用状态的二分测量。我们通过计算在给定年份中报告完全 CPOE 状态的完全采用者的百分比来评估内部一致性。我们通过计算κ统计量和 McNemar 检验来评估两个数据集之间的一致性水平。我们通过评估 HIMSS 和 Leapfrog 数据分别报告的完全 CPOE 状态率随时间的变化来检查响应能力。
研究结果表明,这两个数据集在阳性医院 CPOE 状态方面的一致性很小,但在给定数据集内,每年的一致性都很好。相对于彼此,HIMSS 数据往往会高估随时间增加的完全 CPOE 状态,而 Leapfrog 数据可能会低估全国 CPOE 状态的逐年增加。
Leapfrog 和 HIMSS 数据都有其优势和劣势。那些有兴趣研究与 CPOE 使用或采用相关的结果的人应该了解 Leapfrog 和 HIMSS 数据集的优势和局限性。未来在医院中开发 CPOE 状态的标准定义将允许更全面地验证这些数据。