Complexity and Challenges of the Clinical Diagnosis and Management of Long COVID.
Complexity and Challenges of the Clinical Diagnosis and Management of Long COVID.
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DOI:
10.1001/jamanetworkopen.2022.40332
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发表时间:
2022-11-01
影响因子:
13.8
通讯作者:
Ioannou, George N.
中科院分区:
文献类型:
--
作者:
O'Hare, Ann M.;Vig, Elizabeth K.;Iwashyna, Theodore J.;Fox, Alexandra;Taylor, Janelle S.;Viglianti, Elizabeth M.;Butler, Catherine R.;Vranas, Kelly C.;Helfand, Mark;Tuepker, Anais;Nugent, Shannon M.;Winchell, Kara A.;Laundry, Ryan J.;Bowling, C. Barrett;Hynes, Denise M.;Maciejewski, Matthew L.;Bohnert, Amy S. B.;Locke, Emily R.;Boyko, Edward J.;Ioannou, George N.
What themes pertaining to long COVID can be identified in qualitative analysis of health records from the Department of Veterans Affairs health system? This qualitative study including health records from 200 randomly sampled veterans identified 2 dominant themes: (1) clinical uncertainty: it was often unclear whether particular symptoms were due to long COVID, given the medical complexity and functional limitations of many patients and absence of specific markers for this condition, which led to ongoing monitoring, diagnostic testing, and referral; and (2) care fragmentation: post–COVID-19 care processes were often siloed from other care and could be burdensome to patients. These findings highlight the complexity of diagnosing and managing long COVID in clinical settings. This qualitative study describes dominant themes pertaining to the clinical diagnosis and management of long COVID in the electronic health records of veterans with a diagnostic code for this condition. There is increasing recognition of the long-term health effects of SARS-CoV-2 infection (sometimes called long COVID). However, little is yet known about the clinical diagnosis and management of long COVID within health systems. To describe dominant themes pertaining to the clinical diagnosis and management of long COVID in the electronic health records (EHRs) of patients with a diagnostic code for this condition (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] code U09.9). This qualitative analysis used data from EHRs of a national random sample of 200 patients receiving care in the Department of Veterans Affairs (VA) with documentation of a positive result on a polymerase chain reaction (PCR) test for SARS-CoV-2 between February 27, 2020, and December 31, 2021, and an ICD-10 diagnostic code for long COVID between October 1, 2021, when the code was implemented, and March 1, 2022. Data were analyzed from February 5 to May 31, 2022. A text word search and qualitative analysis of patients’ VA-wide EHRs was performed to identify dominant themes pertaining to the clinical diagnosis and management of long COVID. In this qualitative analysis of documentation in the VA-wide EHR, the mean (SD) age of the 200 sampled patients at the time of their first positive PCR test result for SARS-CoV-2 in VA records was 60 (14.5) years. The sample included 173 (86.5%) men; 45 individuals (22.5%) were identified as Black and 136 individuals (68.0%) were identified as White. In qualitative analysis of documentation pertaining to long COVID in patients’ EHRs 2 dominant themes were identified: (1) clinical uncertainty, in that it was often unclear whether particular symptoms could be attributed to long COVID, given the medical complexity and functional limitations of many patients and absence of specific markers for this condition, which could lead to ongoing monitoring, diagnostic testing, and specialist referral; and (2) care fragmentation, describing how post–COVID-19 care processes were often siloed from and poorly coordinated with other aspects of care and could be burdensome to patients. This qualitative study of documentation in the VA EHR highlights the complexity of diagnosing long COVID in clinical settings and the challenges of caring for patients who have or are suspected of having this condition.
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DOI:
10.15585/mmwr.mm7121e1
发表时间:
2022-05-27
期刊:
Morbidity and Mortality Weekly Report
影响因子:
--
作者:
通讯作者:
--
影响因子:
64.8
作者:
Al-Aly, Ziyad;Xie, Yan;Bowe, Benjamin
通讯作者:
Bowe, Benjamin
影响因子:
3.8
作者:
Elo, Satu;Kyngaes, Helvi
通讯作者:
Kyngaes, Helvi
影响因子:
5.4
作者:
Bloeser, Katharine;McCarron, Kelly K.;McAndrew, Lisa M.
通讯作者:
McAndrew, Lisa M.
影响因子:
39.2
作者:
Nehme, Mayssam;Braillard, Olivia;Guessous, Idris
通讯作者:
Guessous, Idris