Weingart S N, Iezzoni L I, Davis R B, Palmer R H, Cahalane M, Hamel M B, Mukamal K, Phillips R S, Davies D T, Banks N J
Beth Israel Deaconess Medical Center, Department of Medicine, Harvard Medical School, Charles A Dana Research Institute, and the Harvard-Thorndike Library, Boston, Massachusetts 02215, USA.
Med Care. 2000 Aug;38(8):796-806. doi: 10.1097/00005650-200008000-00004.
The use of administrative data to identify inpatient complications is technically feasible and inexpensive but unproven as a quality measure. Our objective was to validate whether a screening method that uses data from standard hospital discharge abstracts identifies complications of care and potential quality problems.
This was a case-control study with structured implicit physician reviews.
Acute-care hospitals in California and Connecticut in 1994.
The study included 1,025 Medicare beneficiaries greater than 265 years of age.
Using administrative data, we stratified acute-care hospitals by observed-to-expected complication rates and randomly selected hospitals within each state. We randomly selected cases flagged with 1 of 17 surgical complications and 6 medical complications. We randomly selected controls from unflagged cases.
Peer-review organization physicians' judgments about the presence of the flagged complication and potential quality-of-care problems.
Physicians confirmed flagged complications in 68.4% of surgical and 27.2% of medical cases. They identified potential quality problems in 29.5% of flagged surgical and 15.7% of medical cases but in only 2.1% of surgical and medical controls. The rate of physician-identified potential quality problems among flagged cases exceeded 25% in 9 surgical screens and 1 medical screen. Reviewers noted several potentially mitigating circumstances that affected their judgments about quality, including factors related to the patients' illness, the complexity of the case, and technical difficulties that clinicians encountered.
For some types of complications, screening administrative data may offer an efficient approach for identifying potentially problematic cases for physician review. Understanding the basis for physicians' judgments about quality requires more investigation.
利用行政数据识别住院并发症在技术上可行且成本低廉，但作为一种质量衡量标准尚未得到验证。我们的目的是验证一种使用标准医院出院摘要数据的筛查方法能否识别护理并发症和潜在的质量问题。
这是一项采用结构化隐性医师评审的病例对照研究。
1994年加利福尼亚州和康涅狄格州的急症医院。
该研究纳入了1025名年龄大于65岁的医疗保险受益人。
利用行政数据，我们根据观察到的与预期的并发症发生率对急症医院进行分层，并在每个州内随机选择医院。我们从17种手术并发症和6种内科并发症中随机选择标记出的病例。我们从未标记的病例中随机选择对照。
同行评审组织医师对标记出的并发症的存在情况以及潜在护理质量问题的判断。
医师确认在68.4%的手术病例和27.2%的内科病例中存在标记出的并发症。他们在29.5%的标记出的手术病例和15.7%的内科病例中识别出潜在质量问题，但在仅2.1%的手术和内科对照病例中识别出潜在质量问题。在9个手术筛查和1个内科筛查中，标记出的病例中医师识别出的潜在质量问题发生率超过25%。评审人员指出了一些可能影响他们对质量判断的潜在缓解情况，包括与患者病情、病例复杂性以及临床医生遇到的技术困难相关的因素。
对于某些类型的并发症，筛查行政数据可能为识别潜在问题病例以供医师评审提供一种有效的方法。了解医师对质量判断的依据需要更多的研究。
