Comparing ascertainment of chronic condition status with problem lists versus encounter diagnoses from electronic health records.
Comparing ascertainment of chronic condition status with problem lists versus encounter diagnoses from electronic health records.
复制标题
将慢性病状态的确定与问题列表与电子健康记录中的诊断进行比较。
DOI：
10.1093/jamia/ocac016
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Quiñones,AnaR
中科院分区：
文献类型：
--
作者：
Voss,RobertW;Schmidt,TeresaD;Weiskopf,Nicole;Marino,Miguel;Dorr,DavidA;Huguet,Nathalie;Warren,Nate;Valenzuela,Steele;O'Malley,Jean;Quiñones,AnaR
目的评估和比较社区卫生中心（CHC）患者问题列表和就诊诊断记录中的慢性病电子健康记录（EHR）文档。材料和方法我们评估了2012-2019年期间大型临床研究网络中的患者EHR数据。我们纳入了为年龄≥45岁的患者提供门诊、老年人初级保健的CHC，研究期间有≥2次门诊访视。我们的研究样本包括来自22个州的545个CHC的1180290名患者。我们使用了来自39个慢性疾病仓库算法的诊断代码，仅从遇到的诊断中识别慢性疾病，并与问题列表记录进行比较。我们测量的对应关系，包括协议，Kappa，患病率指数，偏差指数，和患病率调整的偏差调整Kappa.ResultsOverlap的遭遇诊断和问题列表确定为59.4%之间的慢性疾病，12.2%的条件只确定在遇到和28.4%只确定在问题列表。共鉴定率因条件而异，从7.1%到84.4%。在糖尿病（84.4%）、HIV（78.1%）和高血压（74.7%）中发现了最大的一致性。16种情况的一致性<50%，包括癌症和物质使用障碍。心理健康状况的重叠范围从焦虑的47.4%到抑郁的59.8%。需要在初级保健机构进行定期管理的疾病可能比在专科护理中诊断和治疗的疾病具有更高的一致性。结论依赖EHR就诊数据来识别慢性疾病，而不参考患者问题列表可能无法充分了解美国CHC患者的病情。
ObjectiveTo assess and compare electronic health record (EHR) documentation of chronic disease in problem lists and encounter diagnosis records among Community Health Center (CHC) patients.Materials and methodsWe assessed patient EHR data in a large clinical research network during 2012–2019. We included CHCs who provided outpatient, older adult primary care to patients age ≥45 years, with ≥2 office visits during the study. Our study sample included 1 180 290 patients from 545 CHCs across 22 states. We used diagnosis codes from 39 Chronic Condition Warehouse algorithms to identify chronic conditions from encounter diagnoses only and compared against problem list records. We measured correspondence including agreement, kappa, prevalence index, bias index, and prevalence-adjusted bias-adjusted kappa.ResultsOverlap of encounter diagnosis and problem list ascertainment was 59.4% among chronic conditions identified, with 12.2% of conditions identified only in encounters and 28.4% identified only in problem lists. Rates of coidentification varied by condition from 7.1% to 84.4%. Greatest agreement was found in diabetes (84.4%), HIV (78.1%), and hypertension (74.7%). Sixteen conditions had <50% agreement, including cancers and substance use disorders. Overlap for mental health conditions ranged from 47.4% for anxiety to 59.8% for depression.DiscussionAgreement between the 2 sources varied substantially. Conditions requiring regular management in primary care settings may have a higher agreement than those diagnosed and treated in specialty care.ConclusionRelying on EHR encounter data to identify chronic conditions without reference to patient problem lists may under-capture conditions among CHC patients in the United States.