Suppr超能文献

电子决策支持规则对社区卫生系统中血沉/CRP联合检测率的影响以及对三级医疗机构和商业保险人群的预测影响。

Impact of an electronic decision support rule on ESR/CRP co-ordering rates in a community health system and projected impact in the tertiary care setting and a commercially insured population.

作者信息

Juskewitch Justin E, Norgan Andrew P, Johnson Ryan D, Trivedi Vipul A, Hanson Curtis A, Block Darci R

机构信息

Department of Laboratory Medicine & Pathology, Mayo Clinic, Rochester 55905, MN, USA.

Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester 55905, MN, USA; OptumLabs, Cambridge 02142, MA, USA; Population Health Innovation Institute, Department of Care Delivery, MetroHealth System, Cleveland 44109, OH, USA.

出版信息

Clin Biochem. 2019 Apr;66:13-20. doi: 10.1016/j.clinbiochem.2019.01.009. Epub 2019 Jan 31.

Abstract

INTRODUCTION

Erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) are common laboratory assays used as markers of inflammation. ESR suffers from higher false positive and false negative rates than CRP. To that end, the American Board of Internal Medicine's (ABIM's) Choosing Wisely campaign has recommended against ESR testing for those with undiagnosed conditions in favor of CRP testing. This study describes the impact of a computerized provider order entry (CPOE) decision support rule against ESR/CRP co-ordering within a community health system that predates the ABIM's Choosing Wisely national guidance. To demonstrate the potential impact of such a CPOE rule within other healthcare settings, ESR/CRP ordering data from a multi-site tertiary care practice and from the commercially insured population in the OptumLabs® Data Warehouse (OLDW) were analyzed and the relative reduction in ESR/CRP co-ordering achieved within the community health system was projected onto these populations.

MATERIALS AND METHODS

ESR and/or CRP orders from a community health system were assessed from 2012 to 2016. Co-ordering and test concordance rates between ESR and CRP were compared before and after CPOE decision support rule launch. Similarly, ESR/CRP co-ordering across three tertiary care sites from 2015 to 2016 and the OLDW from 2009 to 2013 were assessed and the co-ordering rate reduction achieved in the community health system was mathematically projected onto these populations. Estimated payer savings from the rule's effect were calculated within each population using Medicare reimbursement rates.

RESULTS

The CPOE decision support rule realized an unadjusted 42% relative rate reduction in ESR/CRP co-ordering within the community health system yielding an annual payer savings of $15,000 with a modest increase in ESR/CRP concordance rates. Projecting a 40% relative reduction in ESR/CRP co-ordering rates from a similarly effective CPOE rule, annual payer cost reductions exceeding $100,000 within a multi-site tertiary care setting and $1,000,000 within the OLDW would be expected.

CONCLUSION

ESR/CRP co-ordering represents an opportunity to eliminate testing waste and reduce payer costs. A CPOE decision support rule stably reduces ESR/CRP co-ordering rates. Similar results may occur as one component of new commercially available decision support platforms.

摘要

引言

红细胞沉降率(ESR)和C反应蛋白(CRP)是常用的实验室检测指标,用作炎症标志物。与CRP相比,ESR的假阳性和假阴性率更高。为此,美国内科医学委员会(ABIM)的明智选择运动建议,对于未确诊疾病的患者,不建议进行ESR检测,而应选择CRP检测。本研究描述了在社区卫生系统中,一项计算机化医嘱录入(CPOE)决策支持规则对ESR/CRP联合医嘱的影响,该社区卫生系统早于ABIM的全国明智选择指南。为了证明这种CPOE规则在其他医疗环境中的潜在影响,分析了来自多地点三级医疗实践以及OptumLabs®数据仓库(OLDW)中商业保险人群的ESR/CRP医嘱数据,并将社区卫生系统中ESR/CRP联合医嘱的相对减少量推算到这些人群上。

材料与方法

评估了2012年至2016年期间一个社区卫生系统的ESR和/或CRP医嘱。比较了CPOE决策支持规则发布前后ESR和CRP之间的联合医嘱率和检测一致性率。同样,评估了2015年至2016年期间三个三级医疗地点以及2009年至2013年OLDW中的ESR/CRP联合医嘱情况,并将社区卫生系统中联合医嘱率的降低量通过数学方法推算到这些人群上。使用医疗保险报销率计算了每个群体因该规则生效而节省的预计费用。

结果

CPOE决策支持规则使社区卫生系统中ESR/CRP联合医嘱的未调整相对率降低了42%,每年为支付方节省15,000美元,同时ESR/CRP一致性率略有提高。假设类似有效的CPOE规则使ESR/CRP联合医嘱率相对降低40%,预计在多地点三级医疗环境中每年可为支付方节省超过100,000美元,在OLDW中每年可为支付方节省1,000,000美元。

结论

ESR/CRP联合医嘱是消除检测浪费和降低支付方成本的一个机会。CPOE决策支持规则可稳定降低ESR/CRP联合医嘱率。作为新的商用决策支持平台的一个组成部分,可能会产生类似的结果。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验