Vijay Krishnamoorthy is associate professor in the Critical Care and Perioperative Population Health Research (CAPER) Unit, Department of Anesthesiology, Division of Critical Care Medicine, and in the Department of Population Health Sciences, Duke University, Durham, North Carolina.
Tetsu Ohnuma is a research associate, CAPER Unit, Department of Anesthesiology, Duke University.
Am J Crit Care. 2021 Jul 1;30(4):320-324. doi: 10.4037/ajcc2021818.
The COVID-19 pandemic created pressure to delay inpatient elective surgery to increase US health care capacity. This study examined the extent to which common inpatient elective operations consume acute care resources.
This cross-sectional study used the Premier Healthcare Database to examine the distribution of inpatient elective operations in the United States from the fourth quarter of 2015 through the second quarter of 2018. Primary outcomes were measures of acute care use after 4 common elective operations: joint replacement, spinal fusion, bariatric surgery, and coronary artery bypass grafting. A framework for matching changing demand with changes in supply was created by overlaying acute care data with publicly available outbreak capacity data.
Elective coronary artery bypass grafting (n = 117 423) had the highest acute care use: 92.8% of patients used intensive care unit beds, 89.1% required postoperative mechanical ventilation, 41.0% required red blood cell transfusions, and 13.3% were readmitted within 90 days of surgery. Acute care use was also substantial after spinal fusion (n = 203 789): 8.3% of patients used intensive care unit beds, 2.2% required postoperative mechanical ventilation, 9.2% required red blood cell transfusions, and 9.3% were readmitted within 90 days of surgery. An example of a framework for matching hospital demand with elective surgery supply is provided.
Acute care needs after elective surgery in the United States are consistent and predictable. When these data are overlaid with national hospital capacity models, rational decisions regarding matching supply to demand can be achieved to meet changing needs.
COVID-19 大流行导致人们不得不推迟非紧急住院择期手术,以增加美国的医疗保健能力。本研究旨在探讨常见的住院择期手术在多大程度上消耗了急性护理资源。
本横断面研究使用 Premier Healthcare Database,调查了 2015 年第四季度至 2018 年第二季度美国常见住院择期手术的分布情况。主要结果是 4 种常见择期手术(关节置换术、脊柱融合术、减肥手术和冠状动脉旁路移植术)后的急性护理使用情况的衡量指标。通过将急性护理数据与公开的疫情容量数据叠加,创建了一个用于匹配需求变化与供应变化的框架。
择期冠状动脉旁路移植术(n=117423)的急性护理使用率最高:92.8%的患者使用了重症监护病房床位,89.1%需要术后机械通气,41.0%需要输注红细胞,13.3%在术后 90 天内再次入院。脊柱融合术(n=203789)的急性护理使用率也很高:8.3%的患者使用了重症监护病房床位,2.2%需要术后机械通气,9.2%需要输注红细胞,9.3%在术后 90 天内再次入院。提供了一个用于匹配医院需求与择期手术供应的框架示例。
美国择期手术后的急性护理需求是一致且可预测的。当这些数据与国家医院容量模型叠加时,可以做出合理的供需匹配决策,以满足不断变化的需求。