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利用自动化和全文医学记录评估哮喘。

Assessment of asthma using automated and full-text medical records.

作者信息

Donahue J G, Weiss S T, Goetsch M A, Livingston J M, Greineder D K, Platt R

机构信息

Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

出版信息

J Asthma. 1997;34(4):273-81. doi: 10.3109/02770909709067217.

DOI:10.3109/02770909709067217
PMID:9250251
Abstract

Automated medical records systems are used to study clinical outcomes and quality of care, but this requires accurate disease identification and assessment of severity. We sought to determine the reliability of identifying asthmatics through automated medical and pharmacy records, and the adequacy of such data for severity assessment. All adult health maintenance organization (HMO) members who received at least one asthma drug and an asthma diagnosis between April 1988 and September 1991 were identified. Records of a random sample were reviewed to validate the diagnosis and extract clinical information. Asthma drugs were dispensed to 15,491 individuals; 7583 (49%) also received an asthma diagnosis. Asthma drug use was three times greater for persons with diagnosed asthma compared to those with no diagnosis. Record review revealed that a coded asthma diagnosis had a positive predictive value of 86%. Nearly 4000 ambulatory encounters were reviewed, 10% of which were for asthma; the median number of encounters was two. Asthma symptoms were mentioned in 9% of all encounters; wheezing was most common. Peak flow and spirometry were measured in 4% and 1% of encounters, respectively. Records from recipients of asthma drugs who lacked an asthma diagnosis showed that 79% did not have asthma. Automated medical and pharmacy records from an HMO were relatively accurate when used to identify individuals with asthma. Similarly, most asthma drug recipients who lacked a coded diagnosis of asthma did not have asthma. However, conventional full-text records usually do not contain sufficient information to assess asthma severity, limiting the utility of such records for research and quality improvement.

摘要

自动化医疗记录系统用于研究临床结果和医疗质量,但这需要准确的疾病识别和严重程度评估。我们试图确定通过自动化医疗和药房记录识别哮喘患者的可靠性,以及此类数据用于严重程度评估的充分性。确定了1988年4月至1991年9月期间接受至少一种哮喘药物治疗且被诊断为哮喘的所有成年健康维护组织(HMO)成员。对随机样本的记录进行审查以验证诊断并提取临床信息。15491人使用了哮喘药物;7583人(49%)也被诊断为哮喘。与未被诊断为哮喘的人相比,被诊断为哮喘的人使用哮喘药物的频率高出三倍。记录审查显示,编码的哮喘诊断的阳性预测值为86%。审查了近4000次门诊就诊记录,其中10%是关于哮喘的;就诊次数的中位数为两次。在所有就诊记录中,9%提到了哮喘症状;喘息最为常见。分别有4%和1%的就诊记录测量了峰值流速和肺活量。缺乏哮喘诊断的哮喘药物接受者的记录显示,79%的人没有哮喘。当用于识别哮喘患者时,HMO的自动化医疗和药房记录相对准确。同样,大多数缺乏哮喘编码诊断的哮喘药物接受者没有哮喘。然而,传统的全文记录通常不包含足够的信息来评估哮喘的严重程度,限制了此类记录在研究和质量改进方面的效用。

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