Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening

作者
Allison Cole,Bethann M. Pflugeisen,Malaika Schwartz,Sophie Cain Miller
出处
期刊:BMC Research Notes [BioMed Central]
卷期号:11 (1): 14-14 被引量:31
标识
DOI:10.1186/s13104-018-3124-0
摘要

OBJECTIVE: Lung cancer is the leading cause of cancer death in the United States [Siegel et al. in CA Cancer J Clin 66:7-30, 1]. However, evidence from clinical trials indicates that annual low-dose computed tomography screening reduces lung cancer mortality [Humphrey et al. in Ann Intern Med 159:411-420, 2]. The objective of this study is to report results of a study designed to assess the sensitivity, specificity, and positive and negative predictive value of an electronic health record (EHR) query in comparison to patient self-report, to identify patients who may benefit from lung cancer screening. Cross sectional study comparing patient self report to EHR derived assessment of tobacco status and need for lung cancer screening. We invited 200 current or former smokers, ages 55-80 to complete a brief paper survey. 26 responded and 24 were included in the analysis. RESULTS: For 30% of respondents, there was not adequate EHR data to make a lung cancer screening determination. Compared to patient self-report, EHR derived data has a 67% sensitivity and 82% specificity for identifying patients that meet criteria for lung cancer screening. While the degree of accuracy may be insufficient to make a final lung cancer screening determination, EHR data may be useful in prompting clinicians to initiate conversations with patients in regards to lung cancer screening.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
仁爱晓兰发布了新的文献求助10
1秒前
酷炫小松鼠完成签到,获得积分10
1秒前
1秒前
1秒前
所所应助徐行采纳,获得10
2秒前
tzttzttzt发布了新的文献求助10
3秒前
4秒前
momo完成签到,获得积分10
4秒前
4秒前
XiaoLi发布了新的文献求助10
4秒前
5秒前
5秒前
小林子完成签到,获得积分10
5秒前
土豆胖墩墩完成签到 ,获得积分10
6秒前
cdercder应助qiqi0426采纳,获得10
6秒前
思源应助心灵美鑫采纳,获得10
6秒前
yjw0526发布了新的文献求助10
7秒前
7秒前
shuichong完成签到,获得积分10
7秒前
香蕉觅云应助wayhome采纳,获得10
7秒前
1.1发布了新的文献求助10
7秒前
科研通AI6.2应助1111111采纳,获得10
7秒前
乐乐乐发布了新的文献求助10
8秒前
Noimpty完成签到,获得积分20
8秒前
丘比特应助失眠的纸鹤采纳,获得10
9秒前
9秒前
9秒前
9秒前
wanci应助酷炫的发带采纳,获得10
10秒前
10秒前
bkagyin应助仁爱晓兰采纳,获得10
10秒前
周子淦发布了新的文献求助10
10秒前
10秒前
11秒前
12秒前
12秒前
12秒前
13秒前
无花果应助wcli采纳,获得10
13秒前
lhz完成签到,获得积分10
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Organic Reactions, Volume 116 1500
VALIDATION OF THE TAYLOR, ALAMEL AND VPSC MODELS FOR PLASTIC ANISOTROPY MODELING OF SHEET METALS 1000
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Machine Learning for Asset Management and Pricing 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7405290
求助须知:如何正确求助?哪些是违规求助? 9010064
关于积分的说明 19187913
捐赠科研通 7038766
什么是DOI,文献DOI怎么找? 3232126
关于科研通互助平台的介绍 2394298
邀请新用户注册赠送积分活动 2214123