Presley Caroline A, Min Jea Young, Chipman Jonathan, Greevy Robert A, Grijalva Carlos G, Griffin Marie R, Roumie Christianne L
Veterans Health Administration-Tennessee Valley Healthcare System, Geriatric Research Education Clinical Center (GRECC), HSR&D Center, Nashville, Tennessee, USA.
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
BMJ Open. 2018 Mar 25;8(3):e020455. doi: 10.1136/bmjopen-2017-020455.
We aimed to validate an algorithm using both primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes to identify hospitalisations due to decompensated heart failure (HF) in a population of patients with diabetes within the Veterans Health Administration (VHA) system.
Validation study.
Veterans Health Administration-Tennessee Valley Healthcare System PARTICIPANTS: We identified and reviewed a stratified, random sample of hospitalisations between 2001 and 2012 within a single VHA healthcare system of adults who received regular VHA care and were initiated on an antidiabetic medication between 2001 and 2008. We sampled 500 hospitalisations; 400 hospitalisations that fulfilled algorithm criteria, 100 that did not. Of these, 497 had adequate information for inclusion. The mean patient age was 66.1 years (SD 11.4). Majority of patients were male (98.8%); 75% were white and 20% were black.
To determine if a hospitalisation was due to HF, we performed chart abstraction using Framingham criteria as the referent standard. We calculated the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for the overall algorithm and each component (primary diagnosis code (ICD-9), DRG code or both).
The algorithm had a PPV of 89.7% (95% CI 86.8 to 92.7), NPV of 93.9% (89.1 to 98.6), sensitivity of 45.1% (25.1 to 65.1) and specificity of 99.4% (99.2 to 99.6). The PPV was highest for hospitalisations that fulfilled both the ICD-9 and DRG algorithm criteria (92.1% (89.1 to 95.1)) and lowest for hospitalisations that fulfilled only DRG algorithm criteria (62.5% (28.4 to 96.6)).
Our algorithm, which included primary discharge diagnosis and DRG codes, demonstrated excellent PPV for identification of hospitalisations due to decompensated HF among patients with diabetes in the VHA system.
我们旨在验证一种算法，该算法同时使用主要出院诊断（国际疾病分类第九版（ICD - 9））和诊断相关组（DRG）编码，以在退伍军人健康管理局（VHA）系统中的糖尿病患者群体中识别因失代偿性心力衰竭（HF）而住院的情况。
验证研究。
退伍军人健康管理局 - 田纳西河谷医疗系统
我们在一个VHA医疗系统中，识别并审查了2001年至2012年期间住院患者的分层随机样本，这些成年患者接受常规VHA护理，并在2001年至2008年期间开始使用抗糖尿病药物。我们抽取了500例住院病例；其中400例符合算法标准，100例不符合。在这些病例中，497例有足够信息可供纳入。患者的平均年龄为66.1岁（标准差11.4）。大多数患者为男性（98.8%）；75%为白人，20%为黑人。
为确定住院是否因HF所致，我们以弗明汉标准作为参考标准进行病历摘要分析。我们计算了整个算法以及每个组成部分（主要诊断编码（ICD - 9）、DRG编码或两者）的阳性预测值（PPV）、阴性预测值（NPV）、敏感性和特异性。
该算法的PPV为89.7%（95%置信区间86.8至92.7），NPV为93.9%（89.1至98.6），敏感性为45.1%（25.1至65.1），特异性为99.4%（99.2至99.6）。对于同时符合ICD - 9和DRG算法标准的住院病例，PPV最高（92.1%（89.1至95.1）），而对于仅符合DRG算法标准的住院病例，PPV最低（62.5%（28.4至96.6））。
我们的算法包括主要出院诊断和DRG编码，在VHA系统中糖尿病患者群体中识别因失代偿性HF而住院的情况时，显示出出色的PPV。
