数字质量指标在Epic Cosmos中用于癌症诊断的应用。
Application of a digital quality measure for cancer diagnosis in Epic Cosmos.
作者信息
Zimolzak Andrew J, Khan Sundas P, Singh Hardeep, Davila Jessica A
机构信息
Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center (MEDVAMC) and Baylor College of Medicine, Houston, TX 77030, United States.
Department of Medicine, Baylor College of Medicine, Houston, TX 77030, United States.
出版信息
J Am Med Inform Assoc. 2025 Jan 1;32(1):227-229. doi: 10.1093/jamia/ocae253.
OBJECTIVES
Missed and delayed cancer diagnoses are common, harmful, and often preventable. We previously validated a digital quality measure (dQM) of emergency presentation (EP) of lung cancer in 2 US health systems. This study aimed to apply the dQM to a new national electronic health record (EHR) database and examine demographic associations.
MATERIALS AND METHODS
We applied the dQM (emergency encounter followed by new lung cancer diagnosis within 30 days) to Epic Cosmos, a deidentified database covering 184 million US patients. We examined dQM associations with sociodemographic factors.
RESULTS
The overall EP rate was 19.6%. EP rate was higher in Black vs White patients (24% vs 19%, P < .001) and patients with younger age, higher social vulnerability, lower-income ZIP code, and self-reported transport difficulties.
DISCUSSION
We successfully applied a dQM based on cancer EP to the largest US EHR database.
CONCLUSION
This dQM could be a marker for sociodemographic vulnerabilities in cancer diagnosis.
目的
癌症诊断的漏诊和延迟诊断很常见，有害且往往是可预防的。我们之前在美国的两个医疗系统中验证了一种肺癌急诊就诊（EP）的数字质量指标（dQM）。本研究旨在将该dQM应用于一个新的全国电子健康记录（EHR）数据库，并研究其与人口统计学的关联。
材料与方法
我们将dQM（急诊就诊后30天内确诊为新发肺癌）应用于Epic Cosmos，这是一个去识别化的数据库，涵盖1.84亿美国患者。我们研究了dQM与社会人口学因素的关联。
结果
总体EP率为19.6%。黑人患者的EP率高于白人患者（24%对19%，P < 0.001），年龄较小、社会脆弱性较高、邮政编码地区收入较低以及自我报告有交通困难的患者的EP率也较高。
讨论
我们成功地将基于癌症EP的dQM应用于美国最大的EHR数据库。
结论
这种dQM可能是癌症诊断中社会人口学脆弱性的一个指标。
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