Patients' experiences of, and engagement with, remote home monitoring services for COVID‐19 patients: A rapid mixed‐methods study

  1. Holly Walton
  2. Cecilia Vindrola‐Padros
  3. Nadia E. Crellin
  4. Manbinder S. Sidhu
  5. Lauren Herlitz
  6. Ian Litchfield
  7. Jo Ellins
  8. Pei Li Ng
  9. Efthalia Massou
  10. Sonila M. Tomini
  11. Naomi J. Fulop

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Abstract

Introduction

Remote home monitoring models were implemented during the COVID‐19 pandemic to shorten hospital length of stay, reduce unnecessary hospital admission, readmission and infection and appropriately escalate care. Within these models, patients are asked to take and record readings and escalate care if advised. There is limited evidence on how patients and carers experience these services. This study aimed to evaluate patient experiences of, and engagement with, remote home monitoring models for COVID‐19.

Methods

A rapid mixed‐methods study was carried out in England (conducted from March to June 2021). We remotely conducted a cross‐sectional survey and semi‐structured interviews with patients and carers. Interview findings were summarized using rapid assessment procedures sheets and data were grouped into themes (using thematic analysis). Survey data were analysed using descriptive statistics.

Results

We received 1069 surveys (18% response rate) and conducted interviews with patients ( n  = 59) or their carers ( n  = 3). ‘Care’ relied on support from staff members and family/friends. Patients and carers reported positive experiences and felt that the service and human contact reassured them and was easy to engage with. Yet, some patients and carers identified problems with engagement (e.g., hesitancy to self‐escalate care). Engagement was influenced by patient factors such as health and knowledge, support from family/friends and staff, availability and ease of use of informational and material resources (e.g., equipment) and service factors.

Conclusion

Remote home monitoring models place responsibility on patients to self‐manage symptoms in partnership with staff; yet, many patients required support and preferred human contact (especially for identifying problems). Caring burden and experiences of those living alone and barriers to engagement should be considered when designing and implementing remote home monitoring services.

Patient or Public Contribution

The study team met with service users and public members of the evaluation teams throughout the project in a series of workshops. Workshops informed study design, data collection tools and data interpretation and were conducted to also discuss study dissemination. Public patient involvement (PPI) members helped to pilot patient surveys and interview guides with the research team. Some members of the public also piloted the patient survey. Members of the PPI group were given the opportunity to comment on the manuscript, and the manuscript was amended accordingly.

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  1. Version published to 10.1111/hex.13548
  2. ScreenIT

    SciScore for 10.1101/2021.12.17.21267968: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: If they were interested in taking part, they were contacted by a researcher who sent them an information sheet and consent form.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analysis: Survey data were analysed using SPSS statistical software (version 25).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: Integration of mixed-methods data helped to provide in-depth perspectives on experiences of, and engagement with, COVID-19 remote home monitoring services. A large team of researchers (from a range of disciplines, with extensive expertise in qualitative and quantitative methods) were involved, thus strengthening interpretation of findings. Findings were shared with clinical and academic stakeholders. Our study sampled a large range of sites with a range of characteristics, thus enhancing generalisability of findings. Compared with patient onboarding data, our patient sample was under-representative of some groups (e.g. older patients, Black, Asian and minority ethnic (BAME) communities and most deprived) and over-representative of other groups [49]. The response rate for the survey was fairly low (17.5%). Additionally, we were unable to recruit interview or survey participants who had declined the service, dropped out from the service, and those who were unable or did not want to take part in surveys and interviews. Therefore, findings may not be representative of all patient groups and experiences. While we did include carers within our sample, the focus of our research as on patient experiences of remote home monitoring services. Therefore, it is possible that we have not captured carers’ experiences in detail. However, some carers shared their own experiences during the interviews and in responding to the survey. Implications: Burden of treatment...

    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.

  3. Version published to 10.1101/2021.12.17.21267968v1 on medRxiv