Evidence map›Paper›PMID 36650559›Full record

ArticleImplementation science communications2023

Implementation, uptake and use of a digital COVID-19 symptom tracker in English care homes in the coronavirus pandemic: a mixed-methods, multi-locality case study.

Pauline A Nelson, Fay Bradley, Akbar Ullah, Will Whittaker, Lisa Brunton, Vid Calovski, Annemarie Money, Dawn Dowding, Nicky Cullum, Paul Wilson

Open access · goldAbstract read
In one paragraph

Article in Implementation science communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 1 country.

Pauline A NelsonDivision of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK. pauline.nelson@manchester.ac.uk.ORCID http://orcid.org/0000-0003-4162-4736
Fay BradleyDivision of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Akbar UllahManchester Centre for Health Economics, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Will WhittakerManchester Centre for Health Economics, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Lisa BruntonDivision of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Williamson Building, Oxford Road, Manchester, M13 9PL, UK.
Vid CalovskiDivision of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Annemarie MoneyDivision of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Dawn DowdingDivision of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Nicky CullumDivision of Nursing, Midwifery & Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Room 6.312, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Paul WilsonDivision of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Williamson Building, Oxford Road, Manchester, M13 9PL, UK.
University of Manchester · GBManchester Academic Health Science Centre · GB

Funding

National Institute for Health Research Applied Research Collaborative (ARC) Greater Manchester (GM
6 · The paper itself

Abstract

backgroundCOVID-19 spread rapidly in UK care homes for older people in the early pandemic. National infection control recommendations included remote resident assessment. A region in North-West England introduced a digital COVID-19 symptom tracker for homes to identify early signs of resident deterioration to facilitate care responses. We examined the implementation, uptake and use of the tracker in care homes across four geographical case study localities in the first year of the pandemic.

methodsThis was a rapid, mixed-methods, multi-locality case study. Tracker uptake was calculated using the number of care homes taking up the tracker as a proportion of the total number of care homes in a locality. Mean tracker use was summarised at locality level and compared. Semi-structured interviews were conducted with professionals involved in tracker implementation and used to explore implementation factors across localities. Template Analysis with the Consolidated Framework for Implementation Research (CFIR) guided the interpretation of qualitative data.

resultsUptake varied across the four case study localities ranging between 13.8 and 77.8%. Tracker use decreased in all localities over time at different rates, with average use ranging between 18 and 58%. The implementation context differed between localities and the process of implementation deviated over time from the initially planned strategy, for stakeholder engagement and care homes' training. Four interpretative themes reflected the most influential factors appearing to affect tracker uptake and use: (1) the process of implementation, (2) implementation readiness, (3) clarity of purpose/perceived value and (4) relative priority in the context of wider system pressures.

conclusionsOur study findings resonate with the digital solutions evidence base prior to the COVID-19 pandemic, suggesting three key factors that can inform future development and implementation of rapid digital responses in care home settings even in times of crisis: an incremental approach to implementation with testing of organisational readiness and attention to implementation climate, particularly the innovation's fit with local contexts (i.e. systems, infrastructure, work processes and practices); involvement of end-users in innovation design and development; and enabling users' easy access to sustained, high-quality, appropriate training and support to enable staff to adapt to digital solutions.

Indexed as

Care homesDigital interventionsImplementationMixed-methodsSocial care

Identifiers

PMID36650559
PMCPMC9843982
OpenAlexW4316813561

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.