Complexity and Challenges of the Clinical Diagnosis and Management of Long COVID 2022 O'Hare et al

Discussion in 'Long Covid research' started by Andy, Nov 4, 2022.

  1. Andy

    Andy Committee Member

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    Key Points

    Question What themes pertaining to long COVID can be identified in qualitative analysis of health records from the Department of Veterans Affairs health system?

    Findings 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.

    Meaning These findings highlight the complexity of diagnosing and managing long COVID in clinical settings.


    Abstract
    Importance 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.

    Objective 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).

    Design, Setting, and Participants 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.

    Main Outcomes and Measures 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.

    Results 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.

    Conclusions and Relevance 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.

    Open access, https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2798146
     
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  2. rvallee

    rvallee Senior Member (Voting Rights)

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    Location:
    Canada
    Healthcare is terrible at dealing with chronic health issues, evidence #96926494634932649326432946324983264239846329436.

    But let's change nothing, as is tradition, and not bother with anything. Surely someone will figure it out and this problem will just stop bothering them. Surely.
     
    alktipping and Peter Trewhitt like this.

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