Bonner James, Love Christopher J, Bhat Vipul, Siegler James E
Department of Emergency Medicine, Inspira Medical Center, Mullica Hill, NJ, USA.
Viz.ai, San Francisco, CA, USA.
Interv Neuroradiol. 2024 Aug 14:15910199241272652. doi: 10.1177/15910199241272652.
A key decision facing nonthrombectomy capable (spoke) hospitals is whether to transfer a suspected large vessel occlusion (LVO) patient to a comprehensive stroke center (CSC). In a retrospective cohort study, we investigated the rate of transfers resulting in endovascular thrombectomy (EVT) and associated costs before and after implementation of an artificial intelligence (AI)-based software.
All patients with a final diagnosis of acute ischemic stroke presenting across a five-spoke community hospital network in affiliation with a CSC were included. The Viz LVO (Viz.ai, Inc.) software was implemented across the spokes with image sharing and messaging between providers across sites. In a cohort of patients before (pre-AI, December 2018-October 2020) and after (post-AI, October 2020-August 2022) implementation, we compared the EVT rate among ischemic stroke patients transferred out of our health system to the CSC. Secondary outcomes included the EVT rate based on spoke computed tomography angiography (CTA) and estimated transfer costs.
A total of 3113 consecutive eligible patients (mean age 71 years, 50% female) presented to the spoke hospitals with 162 transfers pre-AI and 127 post-AI. The rate of transfers treated with EVT significantly increased (32.1% pre-AI vs. 45.7% post-AI, p = 0.02). There was a sharp increase in CTA use post-AI at the spoke hospitals for all patients and transfers that likely contributed to the increased EVT transfer rate, but prior spoke CTA use alone was not sufficient to account for all improvement in EVT transfer rate (37.2% pre-AI vs. 49.2% post-AI, p = 0.12). In a binary logistic regression model, the odds of an EVT transfer in the intervention period were 1.85 greater as compared to preintervention (adjusted odds ratio 1.85, 95% confidence interval 1.12-3.06). The decrease in non-EVT transfers resulted in an estimated annual benefit of $206,121 in spoke revenue and $119,921 in payor savings (all US dollars).
The implementation of an automated image interpretation and communication platform was associated with increased CTA use, more transfers treated with EVT, and potential economic benefits.
对于没有血栓切除术能力(辐条式)的医院而言,一个关键决策是是否将疑似大血管闭塞(LVO)患者转运至综合卒中中心(CSC)。在一项回顾性队列研究中,我们调查了在基于人工智能(AI)的软件实施前后,导致血管内血栓切除术(EVT)的转运率及相关成本。
纳入所有在与一家CSC相关联的五辐条社区医院网络中最终诊断为急性缺血性卒中的患者。Viz LVO(Viz.ai公司)软件在各辐条医院实施,实现了各站点之间的图像共享和信息传递。在实施前(人工智能前,2018年12月至2020年10月)和实施后(人工智能后,2020年10月至2022年8月)的患者队列中,我们比较了转出我们医疗系统至CSC的缺血性卒中患者的EVT率。次要结局包括基于辐条医院计算机断层扫描血管造影(CTA)的EVT率和估计的转运成本。
共有3113例连续符合条件的患者(平均年龄71岁,50%为女性)就诊于辐条医院,人工智能前有162例转运,人工智能后有127例转运。接受EVT治疗的转运率显著提高(人工智能前为32.1%,人工智能后为45.7%,p = 0.02)。人工智能后,辐条医院对所有患者和转运患者的CTA使用量大幅增加,这可能是EVT转运率提高的原因,但仅先前的辐条医院CTA使用不足以解释EVT转运率的所有改善(人工智能前为37.2%,人工智能后为49.2%,p = 0.12)。在二元逻辑回归模型中,与干预前相比,干预期内进行EVT转运的几率高1.85倍(调整后的优势比为1.85,95%置信区间为1.12 - 3.06)。非EVT转运的减少估计每年为辐条医院带来206,121美元的收益,为付款方节省119,921美元(均为美元)。
自动化图像解读和通信平台的实施与CTA使用增加、更多接受EVT治疗的转运以及潜在的经济效益相关。