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提出一个经过验证的临床应用程序,用于预测颅外-颅内搭桥手术的住院费用。

Proposing a validated clinical app predicting hospitalization cost for extracranial-intracranial bypass surgery.

作者信息

Sun Hai, Kalakoti Piyush, Sharma Kanika, Thakur Jai Deep, Dossani Rimal H, Patra Devi Prasad, Phan Kevin, Akbarian-Tefaghi Hesam, Farokhi Frank, Notarianni Christina, Guthikonda Bharat, Nanda Anil

机构信息

Neurosurgery, Louisiana State University Health Sciences Center, Shreveport, Louisiana, United States of America.

NeuroSpine Surgery Research Group (NSURG), Barker St Randwick, Prince of Wales Private Hospital, Sydney, Australia.

出版信息

PLoS One. 2017 Oct 27;12(10):e0186758. doi: 10.1371/journal.pone.0186758. eCollection 2017.

Abstract

OBJECT

United States healthcare reforms are focused on curtailing rising expenditures. In neurosurgical domain, limited or no data exists identifying potential modifiable targets associated with high-hospitalization cost for cerebrovascular procedures such as extracranial-intracranial (ECIC) bypass. Our study objective was to develop a predictive model of initial cost for patients undergoing bypass surgery.

METHODS

In an observational cohort study, we analyzed patients registered in the Nationwide Inpatient Sample (2002-2011) that underwent ECIC bypass. Split-sample 1:1 randomization of the study cohort was performed. Hospital cost data was modelled using ordinary least square to identity potential drivers impacting initial hospitalization cost. Subsequently, a validated clinical app for estimated hospitalization cost is proposed (https://www.neurosurgerycost.com/calc/ec-ic-by-pass).

RESULTS

Overall, 1533 patients [mean age: 45.18 ± 19.51 years; 58% female] underwent ECIC bypass for moyamoya disease [45.1%], cerebro-occlusive disease (COD) [23% without infarction; 12% with infarction], unruptured [12%] and ruptured [4%] aneurysms. Median hospitalization cost was $37,525 (IQR: $16,225-$58,825). Common drivers impacting cost include Asian race, private payer, elective admission, hyponatremia, neurological and respiratory complications, acute renal failure, bypass for moyamoya disease, COD without infarction, medium and high volume centers, hospitals located in Midwest, Northeast, and West region, total number of diagnosis and procedures, days to bypass and post-procedural LOS. Our model was validated in an independent cohort and using 1000-bootstrapped replacement samples.

CONCLUSIONS

Identified drivers of hospital cost after ECIC bypass could potentially be used as an adjunct for creation of data driven policies, impact reimbursement criteria, aid in-hospital auditing, and in the cost containment debate.

摘要

目的

美国医疗保健改革专注于控制不断上涨的支出。在神经外科领域,对于诸如颅外-颅内(ECIC)搭桥等脑血管手术,识别与高住院成本相关的潜在可改变目标的数据有限或不存在。我们的研究目的是为接受搭桥手术的患者建立初始成本预测模型。

方法

在一项观察性队列研究中,我们分析了全国住院患者样本(2002 - 2011年)中接受ECIC搭桥手术的患者。对研究队列进行1:1的拆分样本随机化。使用普通最小二乘法对医院成本数据进行建模,以确定影响初始住院成本的潜在驱动因素。随后,提出了一个经过验证的估计住院成本的临床应用程序(https://www.neurosurgerycost.com/calc/ec-ic-by-pass)。

结果

总体而言,1533例患者[平均年龄:45.18±19.51岁;58%为女性]因烟雾病[45.1%]、脑闭塞性疾病(COD)[23%无梗死;12%有梗死]、未破裂[12%]和破裂[4%]动脉瘤接受了ECIC搭桥手术。住院成本中位数为37,525美元(四分位间距:16,225 - 58,825美元)。影响成本的常见驱动因素包括亚裔种族、私人付款人、择期入院、低钠血症、神经和呼吸并发症、急性肾衰竭、烟雾病搭桥、无梗死的COD、中高容量中心、位于中西部、东北部和西部地区的医院、诊断和手术总数、搭桥天数和术后住院时间。我们的模型在一个独立队列中以及使用1000次自抽样替换样本进行了验证。

结论

确定的ECIC搭桥术后医院成本驱动因素可能潜在地用作创建数据驱动政策的辅助手段、影响报销标准、协助医院审计以及参与成本控制辩论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b591/5659612/974519d6f869/pone.0186758.g001.jpg

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