Development and validation of a continuous measure of patient condition using the Electronic Medical Record
Development and validation of a continuous measure of patient condition using the Electronic Medical Record
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DOI：
10.1016/j.jbi.2013.06.011
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发表时间：
2013-10-01
影响因子：
4.5
通讯作者：
Beals, Joseph
中科院分区：
文献类型：
--
作者：
Rothman, Michael J.;Rothman, Steven I.;Beals, Joseph
患者状况是临床医生之间沟通的关键因素。然而，没有一个普遍接受的定义，病人的条件是独立的诊断和跨越急性水平。我们报告了一种独立于诊断的一般患者状况的连续测量方法的开发和验证，该方法可用于内科手术以及重症监护患者。电子病历数据的调查确定了常见的、经常收集的非静态候选变量，作为一般的、持续更新的患者状况评分的基础。我们使用了一种新的方法来估计与这些变量相关的住院风险。通过比较最终的出院前测量值与出院后1年死亡率，计算每个候选输入的风险函数。逐步逻辑回归的变量对1年死亡率被用来确定每个变量的重要性。最后一组选定的变量包括四个类别的26个临床测量：护理评估，生命体征，实验室结果和心律。然后，我们构建了一个启发式模型，通过对单变量风险进行求和来量化患者状况（总体风险）。该模型的有效性是根据来自170，000名内科手术和重症监护患者的结果进行评估的，使用来自三家美国医院的数据。当将临终关怀/死亡与所有其他出院类别分开时，跨医院的结果验证产生0.92的受试者工作特征曲线下面积（AUC），预测24小时死亡率时的AUC为0.93，预测30天再入院时的AUC为0.62。与反映整个急性谱的患者状况的结果相对应，表明在内外科病房和重症监护病房中的实用性。我们称之为Rothman指数的模型输出可以为临床医生提供患者状况的纵向视图，以帮助解决护理人员沟通，护理连续性和早期检测急性趋势中的已知挑战。(C)2013作者爱思唯尔公司出版All rights reserved.
Patient condition is a key element in communication between clinicians. However, there is no generally accepted definition of patient condition that is independent of diagnosis and that spans acuity levels. We report the development and validation of a continuous measure of general patient condition that is independent of diagnosis, and that can be used for medical-surgical as well as critical care patients.A survey of Electronic Medical Record data identified common, frequently collected non-static candidate variables as the basis for a general, continuously updated patient condition score. We used a new methodology to estimate in-hospital risk associated with each of these variables. A risk function for each candidate input was computed by comparing the final pre-discharge measurements with 1-year post-discharge mortality. Step-wise logistic regression of the variables against 1-year mortality was used to determine the importance of each variable. The final set of selected variables consisted of 26 clinical measurements from four categories: nursing assessments, vital signs, laboratory results and cardiac rhythms. We then constructed a heuristic model quantifying patient condition (overall risk) by summing the single-variable risks. The model's validity was assessed against outcomes from 170,000 medical-surgical and critical care patients, using data from three US hospitals.Outcome validation across hospitals yields an area under the receiver operating characteristic curve (AUC) of 0.92 when separating hospice/deceased from all other discharge categories, an AUC of 0.93 when predicting 24-h mortality and an AUC of 0.62 when predicting 30-day readmissions. Correspondence with outcomes reflective of patient condition across the acuity spectrum indicates utility in both medical-surgical units and critical care units. The model output, which we call the Rothman Index, may provide clinicians with a longitudinal view of patient condition to help address known challenges in caregiver communication, continuity of care, and earlier detection of acuity trends. (C) 2013 The Authors. Published by Elsevier Inc. All rights reserved.