Care Models for Long COVID : A Rapid Systematic Review

This article has been Reviewed by the following groups

Read the full article

Abstract

Context

More than 18M people worldwide (150K Canadians) are living with Long COVID resulting in debilitating sequalae and disabilities that impact their quality of life and capacity to return to work. A new care model is needed for persons living with this complex and multi-systemic disease.

Objectives

What is the best-available evidence about care models for persons living with Long COVID?

Design

Rapid Living Systematic Review.

Method

We systematically searched seven electronic databases (MEDLINE, Embase, Web of Science, COVID-END, L-OVE, CDRS and WHO Ovid) on May 27 th , 2021. Two independent reviewers screened titles, abstracts and full text. We included studies reporting on 1- persons living with Long COVID and 2- proposing a specific care model (i.e., dedicated clinic, care pathway). We extracted characteristic of studies (e.g., countries, study design, age group), referral pathways targeted (e.g., hospitalized, community), reporting of the care model implementation with number of patients, clinical settings of care model (e.g., primary care), healthcare professions included in the care model, care model principles (e.g., person-centred care) and care model components (e.g., standardized symptoms assessment). We used descriptive statistics and frequency count.

Results

We screened 2181 citations, read 65 full text and included 12 eligible articles reporting on care models for Long COVID. Half studies were from the United Kingdom. 7 out of 12 models reported conceptual models without a description of implementation. All but one model was designed for discharge and long-term follow-up of hospitalized patients and half models were designed for non- hospitalized or patients who lived with the disease only in the community. Nine out of 12 care models included primary care, 8 out of 12 included specialized clinics and all studies included rehabilitation services. A total of 30 healthcare professions and medical specialties were proposed for staffing Long COVID services. More than half studies proposed multidisciplinary teams, integrated/coordination of care, evidence-based care and patient-centred care as key care model principles. Standardized symptom assessment, follow-up system and virtual care were the most frequent care model components.

Conclusion

The implementation of care models for Long COVID is underway in several countries. Care models need to include both hospitalized and non-hospitalized patients. A complete care model for this population appears to design a care pathway integrating primary care, rehabilitation services and specialized clinics for medical assessment. The entry into care pathways is likely possible through a centralized referral system. It is possible to design sustainable and equitable care pathways for Long COVID in Canada integrated in current infrastructure.

Protocol/Topic Registration

CRD42021282266

Summary

An estimated 150K Canadians, mostly women, are facing debilitating sequalae and disabilities from Long COVID that impact their quality of life and capacity to return to work. A new care model is needed for persons with this complex and multi-systemic disease. We identified international care models describing the integration of primary care, rehabilitation services and specialized assessment clinics for Long COVID.

Implications

Limited evidence from this review of international care models for Long COVID point out to a care model for the Canadian context that should be co- designed with patients, clinicians, decision makers and researchers, and include: 1- A coordination unit to centrally receive referrals from both hospitalized and community-based patients; 2- Training of primary care teams to screen and support medical needs; 3- Integrated local multidisciplinary rehabilitation services; and 4- Access to medical specialty clinics for advanced testing and diagnoses.

What is the current situation?

  • More than 150K Canadians are with living the affliction of Long COVID, the patient-led term to describe long-term consequences of COVID-19. Long COVID is a multi-systemic and unpredictable disease impacting quality of life and return to work in middle aged population. To avoid widespread long-term disabilities impacting public health, Canadian provinces are seeking to organize a sustainable and equitable care model for Long COVID.

What is the objective?

  • To provide the best-available evidence about care models for persons living with Long COVID.

How was the review conducted?

  • We systematically searched seven electronic databases (MEDLINE, Embase, Web of Science, COVID-END, L-OVE, CDRS and WHO Ovid) on May 27th, 2021.

  • Two independent reviewers screened title, abstract and full text.

  • We included studies reporting on 1- persons living with Long COVID (post- hospitalized and community based) and 2- a specific care model (i.e., dedicated clinic, care pathway).

  • We extracted characteristic of studies, referral pathways, clinical settings of care model, healthcare professions included in the care models, care model principles, care model components and reporting of the care model implementation.

What did the review find?

  • We found 12 international care models for Long COVID that covers follow-up of patients discharged following a hospitalization and patients who had lived the infection in the community.

  • Most reported elements included in these care models were a coordination unit, primary care pathways, access to multidisciplinary rehabilitation and specialized medical services.

  • The impact and costs of these care models are not yet reported.

Article activity feed

  1. SciScore for 10.1101/2021.11.17.21266404: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Literature Search: We systematically searched seven databases: MEDLINE, Embase, Web of Science, COVID-END, L- OVE, CDSR, and WHO Ovid.
    MEDLINE
    suggested: (MEDLINE, RRID:SCR_002185)
    Embase
    suggested: (EMBASE, RRID:SCR_001650)
    We also searched Web of Science (Core Collection) and the Cochrane Database of Systematic Reviews.
    Cochrane Database of Systematic Reviews
    suggested: None
    We downloaded and deduped the records using EndNote 9.3.3 (Clarivate) and uploaded to DistillerSR (Evidence Partners).
    EndNote
    suggested: (EndNote, RRID:SCR_014001)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.