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血管外科质量指标的准确性和可靠性评估

Assessment of the Accuracy and Reliability of Vascular Surgery Quality Metrics.

作者信息

Fang Zachary B, Chao Calvin, Durocher Dawn, Flahive Julie M, Simons Jessica P, Schanzer Andres, Aiello Francesco A

机构信息

Division of Vascular and Endovascular Surgery, UMass Memorial Medical Center, University of Massachusetts Medical School Worcester, Worcester, MA.

Population and Quantitative Health Sciences, UMass Medical School, Worcester, MA.

出版信息

Ann Vasc Surg. 2020 Aug;67:134-142. doi: 10.1016/j.avsg.2020.02.036. Epub 2020 Mar 20.

Abstract

BACKGROUND

Health care quality metrics are crucial to medical institutions, payers, and patients. Obtaining current and reliable quality data is challenging, as publicly reported databases lag by several years. Vizient Clinical Data Base (previously University Health Consortium) is utilized by over 5,000 academic and community medical centers to benchmark health care metrics with results based on predetermined Vizient service lines. We sought to assess the accuracy and reliability of vascular surgery service line metrics, as determined by Vizient.

METHODS

Vizient utilizes encounter data submitted by participating medical centers and generates a diverse array of health care metrics ranging from mortality to costs. All inpatient cases captured by Vizient under the vascular surgery service line were identified at the University of Massachusetts Medical Center (fiscal year 2016). Each case within the service line was reviewed and categorized as "vascular" or "nonvascular" based on care provided by UMass vascular surgery faculty: vascular = vascular surgery was integral part of care, nonvascular = vascular surgery had minimal or no involvement. Statistical analysis comparing length of stay (LOS), cost, readmission, mortality, and complication rates between vascular and nonvascular cohorts was performed. All inpatient cases discharged by a vascular surgeon National Provider Identifier number were also reviewed and categorized according to Vizient service lines.

RESULTS

Vizient's vascular surgery service line identified 696 cases, of which 556 (80%) were vascular and 140 (20%) were nonvascular. When comparing these 2 cohorts, vascular cases had a significantly lower LOS (3.4 vs. 8.7 days; P < 0.0001), cost ($8,535 vs. $16,498; P < 0.0001), and complication rate (6.5% vs. 18%; P < 0.0001) than nonvascular. Mortality was also lower (1.6% vs. 5.7%; P < 0.01), but after risk-adjustment, this difference was not significant. When discharging vascular surgeon National Provider Identifier was used to identify vascular surgery cases, only 69% of these cases were placed within the vascular surgery service line.

CONCLUSIONS

Health care quality metrics play an important role for all stakeholders but obtaining accurate and reliable data to implement improvements is challenging. In this single institution experience, inpatient cases that were not under the direction or care of a vascular surgeon resulted in significantly negative impacts on LOS, cost, complication rate, and mortality to the vascular surgery service line, as defined by a national clinical database. Therefore, clinicians must understand the data abstracting and reporting process before implementing effective strategic plans.

摘要

背景

医疗质量指标对医疗机构、支付方和患者至关重要。获取当前可靠的质量数据具有挑战性,因为公开报告的数据库会滞后数年。超过5000家学术和社区医疗中心使用Vizient临床数据库(前身为大学健康联盟),根据预先确定的Vizient服务线结果对医疗指标进行基准评估。我们试图评估Vizient确定的血管外科服务线指标的准确性和可靠性。

方法

Vizient利用参与医疗中心提交的诊疗数据,生成从死亡率到成本等一系列不同的医疗指标。在马萨诸塞大学医学中心(2016财年)识别出Vizient在血管外科服务线捕获的所有住院病例。根据麻省大学血管外科教员提供的护理,对服务线内的每个病例进行审查并分类为“血管性”或“非血管性”:血管性 = 血管外科是护理的重要组成部分,非血管性 = 血管外科参与极少或未参与。对血管性和非血管性队列之间的住院时间(LOS)、成本、再入院率、死亡率和并发症发生率进行统计分析。所有由血管外科医生国家提供者识别码出院的住院病例也根据Vizient服务线进行审查和分类。

结果

Vizient的血管外科服务线识别出696例病例,其中556例(80%)为血管性病例,140例(20%)为非血管性病例。比较这两个队列时,血管性病例的住院时间(3.4天对8.7天;P < 0.0001)、成本(8535美元对16498美元;P < 0.0001)和并发症发生率(6.5%对18%;P < 0.0001)均显著低于非血管性病例。死亡率也较低(1.6%对5.7%;P < 0.01),但经过风险调整后,这种差异不显著。当使用血管外科医生国家提供者识别码来识别血管外科病例时,这些病例中只有69%被归入血管外科服务线。

结论

医疗质量指标对所有利益相关者都起着重要作用,但获取准确可靠的数据以实施改进具有挑战性。在这一单一机构的经验中,非血管外科医生指导或护理的住院病例对血管外科服务线的住院时间、成本、并发症发生率和死亡率产生了显著负面影响,这是由一个国家临床数据库定义的。因此,临床医生在实施有效的战略计划之前必须了解数据提取和报告过程。

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