Evidence map›Paper›PMID 36333948›Full record

ArticleHealth expectations : an international journal of public participation in health care and health policy2023

COVID-19 community assessment hubs in Ireland: A study of staff and patient perceptions of their value.

Eilish McAuliffe, Sophie Mulcahy Symmons, Ciara Conlon, Lisa Rogers, Aoife De Brún, Marese Mannion, Niamh Keane, Liam Glynn, Joseph Ryan, Diarmuid Quinlan

Abstract read
In one paragraph

Article in Health expectations : an international journal of public participation in health care and health policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. COVID-19 community assessment hubs in Ireland: A study of staff and patient perceptions of their value.Health expectations : an international journal of public participation in health care and health policy · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Eilish McAuliffeIRIS Centre, School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin, Ireland.ORCID 0000-0002-9714-5040
Sophie Mulcahy SymmonsIRIS Centre, School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin, Ireland.ORCID 0000-0003-0749-6582
Ciara ConlonAcademic Affairs, Trinity College Dublin, Dublin, Ireland.ORCID 0000-0001-8446-7326
Lisa RogersIRIS Centre, School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin, Ireland.
Aoife De BrúnIRIS Centre, School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin, Ireland.ORCID 0000-0003-0124-0893
Marese MannionBurren Medical Centre, Clare, Ireland.
Niamh KeaneMidwest Community Healthcare Organisation (CHO3), Limerick, Ireland.
Liam GlynnSchool of Medicine, University of Limerick & HRB Prmary Care Clinical Trials Network Ireland, Galawy, Ireland.
Joseph RyanThe Weir Clinic, Bandon, Cork, Ireland.
Diarmuid QuinlanIrish College of General Practitioners, Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCritical care bed capacity per capita in Ireland is among the lowest in Europe. The COVID-19 pandemic has put additional strain on an over-stretched healthcare system. COVID-19 community assessment hubs (CAHs) were established to prevent unnecessary admission to acute hospitals and to reduce infection spread.

objectiveThe aim of this study was to assess the effectiveness and acceptability of CAHs and identify how the service might be improved or adapted for possible future use.

designThis was a mixed methods study, incorporating co-design with clinical stakeholders. Data collection was via an online survey and semistructured telephone interviews with staff and patients conducted between January and May 2021. SETTING AND

participantsThirty-one patients completed the survey and nine were interviewed. Twenty interviews were conducted with staff.

resultsThe findings suggest that the CAH model was successful in providing a dedicated pathway for assessing patients with COVID-19 symptoms, whilst mitigating the risk of infection. Patients were particularly positive about the timely, comprehensive and holistic care they received, as well as the accessibility of the clinics and the friendly attitudes of the staff. Staff welcomed the training and clinical protocols which contributed to their feelings of safety and competency in delivering care to this cohort of patients. They also highlighted the benefits of working in a multidisciplinary environment. Both staff and patients felt that the hubs could be repurposed for alternative use, including the treatment of chronic diseases. DISCUSSION: This study describes staff and patients' experiences of these hubs. An unexpected outcome of this study is its demonstration of the true value of effective multidisciplinary working, not only for the staff who were deployed to this service but also for the patients in receipt of care in these hubs.

conclusionThis multidisciplinary patient-centred service may provide a useful model for the delivery of other services currently delivered in hospital settings. PATIENT OR PUBLIC CONTRIBUTION: An earlier phase of this study involved interviews with COVID-19-positive patients on a remote monitoring programme. The data informed this phase. Several of the authors had worked in the CAHs and provided valuable input into the design of the staff and patient interviews.

Indexed as

COVID-19Delivery of Health CareHumansIrelandPandemicsPatientscommunity assessment hubscoronavirusCOVID-19patient experiencestaff experience

Identifiers

PMID36333948
PMCPMC9854303

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.