Keller Deborah S, Kroll Donald, Papaconstantinou Harry T, Ellis C Neal
Department of Surgery, Baylor University Medical Center, Dallas, TX.
Gulf Coast Veterans Health Care System, Biloxi, MS.
J Am Coll Surg. 2017 Apr;224(4):602-607. doi: 10.1016/j.jamcollsurg.2016.12.033. Epub 2017 Jan 11.
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.
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.
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).
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.
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。
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。
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)。
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。