Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery.
Local Instrumental Variable Methods to Address Confounding and Heterogeneity when Using Electronic Health Records: An Application to Emergency Surgery.
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DOI：
10.1177/0272989x221100799
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发表时间：
2022-11
影响因子：
3.6
通讯作者：
O'Neill, Stephen
中科院分区：
文献类型：
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作者：
Moler-Zapata, Silvia;Grieve, Richard;Lugo-Palacios, David;Hutchings, A.;Silverwood, R.;Keele, Luke;Kircheis, Tommaso;Cromwell, David;Smart, Neil;Hinchliffe, Robert;O'Neill, Stephen
关键词：
电子健康记录（EHR）为比较有效性研究提供了机会，为决策提供信息。然而，为了提供有用的证据，这些研究必须根据未测量的预后因素解决混杂和治疗效果异质性。局部工具变量（LIV）方法可以帮助研究解决这些挑战，但尚未应用于EHR数据。本文批判性地探讨了LIV方法，以评估急诊手术（ES）的成本效益，为常见的急性条件，从EHR。本文使用2010年至2019年英格兰175家急症医院因急性阑尾炎、憩室病和腹壁疝急诊入院的医院发作统计（HES）数据。对于每次急诊入院，ES接收的工具变量是每个医院的ES率在急诊入院前一年。LIV方法提供了对ES的增量质量调整生命年、成本和净货币效益的个人水平估计，这些估计被汇总到总体人群和感兴趣的亚群，并与传统的IV和风险调整方法进行了对比。该研究包括268，144例（阑尾炎），138，869例（憩室病）和106，432例（疝）患者。该工具被认为是强大的，并尽量减少协变量的不平衡。对于憩室疾病，结果因方法而异;尽管传统方法报告总体而言ES不具有成本效益，但LIV方法报告ES具有成本效益，但具有广泛的统计不确定性。对于所有3种情况，LIV方法发现在人群亚组中的成本-效果估计值存在异质性：特别是，ES对于严重虚弱患者不具有成本-效果。EHR可以与LIV方法相结合，以提供常规干预措施的成本效益证据，同时充分认识到异质性。本文讨论了在评估电子健康记录（EHR）数据的比较有效性时出现的混杂和异质性，通过应用局部工具变量（LIV）方法来评估急诊手术（ES）与替代策略的成本效益，用于常见急性疾病（阑尾炎，憩室病和腹壁疝）患者。工具变量，医院的倾向，操作，被发现是强烈相关的ES接收和最大限度地减少不平衡的基线特征之间的比较组。LIV方法发现，对于每种情况，根据基线特征，成本效益估计值存在异质性。该研究说明了如何将LIV方法应用于EHR数据，以提供识别异质性的成本效益估计，并可用于为决策提供信息，以及为进一步研究生成假设。
Electronic health records (EHRs) offer opportunities for comparative effectiveness research to inform decision making. However, to provide useful evidence, these studies must address confounding and treatment effect heterogeneity according to unmeasured prognostic factors. Local instrumental variable (LIV) methods can help studies address these challenges, but have yet to be applied to EHR data. This article critically examines a LIV approach to evaluate the cost-effectiveness of emergency surgery (ES) for common acute conditions from EHRs. This article uses hospital episodes statistics (HES) data for emergency hospital admissions with acute appendicitis, diverticular disease, and abdominal wall hernia to 175 acute hospitals in England from 2010 to 2019. For each emergency admission, the instrumental variable for ES receipt was each hospital’s ES rate in the year preceding the emergency admission. The LIV approach provided individual-level estimates of the incremental quality-adjusted life-years, costs and net monetary benefit of ES, which were aggregated to the overall population and subpopulations of interest, and contrasted with those from traditional IV and risk-adjustment approaches. The study included 268,144 (appendicitis), 138,869 (diverticular disease), and 106,432 (hernia) patients. The instrument was found to be strong and to minimize covariate imbalance. For diverticular disease, the results differed by method; although the traditional approaches reported that, overall, ES was not cost-effective, the LIV approach reported that ES was cost-effective but with wide statistical uncertainty. For all 3 conditions, the LIV approach found heterogeneity in the cost-effectiveness estimates across population subgroups: in particular, ES was not cost-effective for patients with severe levels of frailty. EHRs can be combined with LIV methods to provide evidence on the cost-effectiveness of routinely provided interventions, while fully recognizing heterogeneity. This article addresses the confounding and heterogeneity that arise when assessing the comparative effectiveness from electronic health records (EHR) data, by applying a local instrumental variable (LIV) approach to evaluate the cost-effectiveness of emergency surgery (ES) versus alternative strategies, for patients with common acute conditions (appendicitis, diverticular disease, and abdominal wall hernia). The instrumental variable, the hospital’s tendency to operate, was found to be strongly associated with ES receipt and to minimize imbalances in baseline characteristics between the comparison groups. The LIV approach found that, for each condition, there was heterogeneity in the estimates of cost-effectiveness according to baseline characteristics. The study illustrates how an LIV approach can be applied to EHR data to provide cost-effectiveness estimates that recognize heterogeneity and can be used to inform decision making as well as to generate hypotheses for further research.