• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用退伍军人事务部手术质量改进计划风险计算器降低死亡率方法的开发与验证

Development and Validation of a Methodology to Reduce Mortality Using the Veterans Affairs Surgical Quality Improvement Program Risk Calculator.

作者信息

Keller Deborah S, Kroll Donald, Papaconstantinou Harry T, Ellis C Neal

机构信息

Department of Surgery, Baylor University Medical Center, Dallas, TX.

Gulf Coast Veterans Health Care System, Biloxi, MS.

出版信息

J Am Coll Surg. 2017 Apr;224(4):602-607. doi: 10.1016/j.jamcollsurg.2016.12.033. Epub 2017 Jan 11.

DOI:10.1016/j.jamcollsurg.2016.12.033
PMID:28088600
Abstract

BACKGROUND

To identify patients with a high risk of 30-day mortality after elective surgery, who may benefit from referral for tertiary care, an institution-specific process using the Veterans Affairs Surgical Quality Improvement Program (VASQIP) Risk Calculator was developed. The goal was to develop and validate the methodology. Our hypothesis was that the process could optimize referrals and reduce mortality.

STUDY DESIGN

A VASQIP risk score was calculated for all patients undergoing elective noncardiac surgery at a single Veterans Affairs (VA) facility. After statistical analysis, a VASQIP risk score of 3.3% predicted mortality was selected as the institutional threshold for referral to a tertiary care center. The model predicted that 16% of patients would require referral, and 30-day mortality would be reduced by 73% at the referring institution. The main outcomes measures were the actual vs predicted referrals and mortality rates at the referring and receiving facilities.

RESULTS

The validation included 565 patients; 90 (16%) had VASQIP risk scores greater than 3.3% and were identified for referral; 60 consented. In these patients, there were 16 (27%) predicted mortalities, but only 4 actual deaths (p = 0.007) at the receiving institution. When referral was not indicated, the model predicted 4 mortalities (1%), but no actual deaths (p = 0.1241).

CONCLUSIONS

These data validate this methodology to identify patients for referral to a higher level of care, reducing mortality at the referring institutions and significantly improving patient outcomes. This methodology can help guide decisions on referrals and optimize patient care. Further application and studies are warranted.

摘要

背景

为了识别择期手术后30天死亡风险高的患者,这些患者可能会从转诊至三级医疗机构中获益,我们开发了一种使用退伍军人事务部外科质量改进计划(VASQIP)风险计算器的机构特定流程。目标是开发并验证该方法。我们的假设是该流程可以优化转诊并降低死亡率。

研究设计

为在一家退伍军人事务(VA)机构接受择期非心脏手术的所有患者计算VASQIP风险评分。经过统计分析,选择预测死亡率为3.3%的VASQIP风险评分作为转诊至三级护理中心的机构阈值。该模型预测16%的患者需要转诊,转诊机构的30天死亡率将降低73%。主要结局指标是转诊机构和接收机构实际与预测的转诊情况及死亡率。

结果

验证纳入了565例患者;90例(16%)的VASQIP风险评分高于3.3%,被确定为需要转诊;60例同意转诊。在这些患者中,接收机构预测有16例(27%)死亡,但实际只有4例死亡(p = 0.007)。当未建议转诊时,该模型预测有4例死亡(1%),但实际无死亡(p = 0.1241)。

结论

这些数据验证了这种识别需要转诊至更高护理级别的患者的方法,降低了转诊机构的死亡率并显著改善了患者结局。这种方法有助于指导转诊决策并优化患者护理。有必要进一步应用和开展研究。

相似文献

1
Development and Validation of a Methodology to Reduce Mortality Using the Veterans Affairs Surgical Quality Improvement Program Risk Calculator.使用退伍军人事务部手术质量改进计划风险计算器降低死亡率方法的开发与验证
J Am Coll Surg. 2017 Apr;224(4):602-607. doi: 10.1016/j.jamcollsurg.2016.12.033. Epub 2017 Jan 11.
2
Outcomes of Women Undergoing Noncardiac Surgery in Veterans Affairs Compared With Non-Veterans Affairs Care Settings.退伍军人事务部与非退伍军人事务部护理环境中接受非心脏手术的女性的结果比较。
JAMA Surg. 2024 May 1;159(5):501-509. doi: 10.1001/jamasurg.2023.8081.
3
Changes over time in risk profiles of patients who undergo coronary artery bypass graft surgery: the Veterans Affairs Surgical Quality Improvement Program (VASQIP).接受冠状动脉旁路移植术的患者风险特征随时间的变化:退伍军人事务部手术质量改进计划(VASQIP)。
JAMA Surg. 2015 Apr;150(4):308-15. doi: 10.1001/jamasurg.2014.1700.
4
Assessing the Veterans Affairs Surgical Quality Improvement Program Risk Calculator in Cholecystectomy.评估退伍军人事务部胆囊切除术手术质量改进计划风险计算器
Am Surg. 2018 Jun 1;84(6):1039-1042.
5
A study to reduce readmissions after surgery in the Veterans Health Administration: design and methodology.一项旨在降低退伍军人健康管理局术后再入院率的研究:设计与方法
BMC Health Serv Res. 2017 Mar 14;17(1):198. doi: 10.1186/s12913-017-2134-2.
6
Comparing Veterans Affairs and Private Sector Perioperative Outcomes After Noncardiac Surgery.比较非心脏手术后退伍军人事务部和私营部门的围手术期结局。
JAMA Surg. 2022 Mar 1;157(3):231-239. doi: 10.1001/jamasurg.2021.6488.
7
Use of the surgical Apgar score to enhance Veterans Affairs Surgical Quality Improvement Program surgical risk assessment in veterans undergoing major intra-abdominal surgery.使用手术阿普加评分来加强退伍军人事务部手术质量改进计划对接受大型腹部手术退伍军人的手术风险评估。
Am J Surg. 2017 Apr;213(4):696-705. doi: 10.1016/j.amjsurg.2016.05.017. Epub 2016 Jul 21.
8
The effect of a regional hepatopancreaticobiliary surgical program on clinical volume, quality of cancer care, and outcomes in the Veterans Affairs system.区域肝胆胰外科学术计划对退伍军人事务系统中临床量、癌症护理质量和结果的影响。
JAMA Surg. 2014 Nov;149(11):1153-61. doi: 10.1001/jamasurg.2014.1711.
9
Decreasing 30-day surgical mortality in a VA Medical Center utilizing the ACS NSQIP Surgical Risk Calculator.在一家退伍军人事务部医疗中心使用美国外科医师学会国家外科质量改进计划(ACS NSQIP)手术风险计算器降低30天手术死亡率。
J Surg Res. 2017 Jul;215:28-33. doi: 10.1016/j.jss.2017.03.030. Epub 2017 Apr 1.
10
Thirty-Day Postoperative Mortality Risk Estimates and 1-Year Survival in Veterans Health Administration Surgery Patients.退伍军人事务部手术患者的 30 天术后死亡率估计和 1 年生存率。
JAMA Surg. 2016 May 1;151(5):417-22. doi: 10.1001/jamasurg.2015.4882.

引用本文的文献

1
Preoperative Care Assessment of Need Scores Are Associated With Postoperative Mortality and Length of Stay in Veterans Undergoing Knee Replacement.术前护理需求评分与接受膝关节置换术的退伍军人术后死亡率和住院时间相关。
Fed Pract. 2021 Jul;38(7):316-324. doi: 10.12788/fp.0148.
2
Surgery Reduces Risk of Complications Even in High-Risk Veterans After Endoscopic Therapy for Biliary Stone Disease.手术可降低风险,即使对于内镜治疗胆道结石病后高危的退伍军人也是如此。
Dig Dis Sci. 2018 Mar;63(3):781-786. doi: 10.1007/s10620-018-4940-8. Epub 2018 Jan 29.