Evidence map›Paper›PMID 38974203›Full record

ArticleInternational journal of integrated care

The Impact of the Covid-19 Pandemic on an Integrated Care Programme for Older People with Different Frailty Levels (OPDFL): A Qualitative Study with Service Providers in the East of England.

Nimra Khan, David Hewson, Gurch Randhawa

Abstract read
In one paragraph

Article in International journal of integrated care. 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. 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

3 authors.

Nimra KhanDepartment of Psychiatry, University of Oxford, Warneford Hospital, Warneford Ln, Headington, Oxford OX3 7JX, UK.
David HewsonInstitute for Health Research, University of Bedfordshire, Hitchin Road, Luton, LU2 8LE, UK.
Gurch RandhawaInstitute for Health Research, University of Bedfordshire, Hitchin Road, Luton, LU2 8LE, UK.ORCID https://orcid.org/0000-0002-2289-5859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: While populations of all ages were affected by the pandemic, older people with frailty had much worse outcomes. The NHS England has mandated identifying and proactively managing older people with moderate and severe frailty in the General medical services (GMS) contract 2017/18. As a result of this policy, an integrated care programme for older people with different frailty levels (OPDFL) was introduced in Luton in 2018 (known as, Luton Framework for Frailty - LFF). This study was conducted to explore the views of service providers in Luton regarding the impact of the COVID-19 pandemic on the implementation of LFF. Methods: Semi-structured interviews were conducted with service providers in Luton between April 2021 to July 2021. The data were analysed using thematic analysis. Results: Eighteen service providers took part in the study. Three main themes were identified, the first of which was that proactive and frailty-related health promotion services were halted. Secondly, existing relationships due to the LFF facilitated the implementation of services for care home residents during the pandemic. Finally, participants identified that some of the challenges impacting the delivery of health promotion services were those that affected the health system in general, such as healthcare staff feeling stressed and the centralised decision-making by the government. Conclusion: The lessons learnt from this study could be useful in managing services for older people with frailty in times of emergencies or epidemics.

Indexed as

COVID-19Englandfrailtyintegrated careLutonolder people

Identifiers

PMID38974203
PMCPMC11225545

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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.