Evidence map›Paper›PMID 36690927›Full record

ArticleBMC infectious diseases2023

The use and impact of digital COVID-19 tracking in adult social care: a prospective cohort study of care homes in Greater Manchester.

Akbar Ullah, William Whittaker, Fay Bradley, Pauline A Nelson, Dawn Dowding, Marcello Morciano, Nicky Cullum

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 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
2.0field-weighted citation impact, top 15% 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

7 authors at 3 institutions in 2 countries.

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. akbar.ullah@manchester.ac.uk.
William WhittakerManchester Centre for Health Economics, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Fay BradleyDivision of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Pauline A NelsonDivision of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Dawn DowdingDivision of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
Marcello MorcianoDepartment of Economics, University of Modena and Reggio Emilia, Via Università, 4, 41121, Modena, MO, Italy.
Nicky CullumDivision of Nursing, Midwifery and Social Work, School of Health Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK.
University of Manchester · GBManchester Academic Health Science Centre · GBUniversity of Modena and Reggio Emilia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo support proactive care during the coronavirus pandemic, a digital COVID-19 symptom tracker was deployed in Greater Manchester (UK) care homes. This study aimed to understand what factors were associated with the post-uptake use of the tracker and whether the tracker had any effects in controlling the spread of COVID-19.

methodsDaily data on COVID-19, tracker uptake and use, and other key indicators such as staffing levels, the number of staff self-isolating, availability of personal protective equipment, bed occupancy levels, and any problems in accepting new residents were analysed for 547 care homes across Greater Manchester for the period April 2020 to April 2021. Differences in tracker use across local authorities, types of care homes, and over time were assessed using correlated effects logistic regressions. Differences in numbers of COVID-19 cases in homes adopting versus not adopting the tracker were compared via event design difference-in-difference estimations.

resultsHomes adopting the tracker used it on 44% of days post-adoption. Use decreased by 88% after one year of uptake (odds ratio 0.12; 95% confidence interval 0.06-0.28). Use was highest in the locality initiating the project (odds ratio 31.73; 95% CI 3.76-268.05). Care homes owned by a chain had lower use (odds ratio 0.30; 95% CI 0.14-0.63 versus single ownership care homes), and use was not associated with COVID-19 or staffing levels. Tracker uptake had no impact on controlling COVID-19 spread. Staff self-isolating and local area COVID-19 cases were positively associated with lagged COVID-19 spread in care homes (relative risks 1.29; 1.2-1.4 and 1.05; 1.0-1.1, respectively).

conclusionsThe use of the COVID-19 symptom tracker in care homes was not maintained except in Locality 1 and did not appear to reduce the COVID-19 spread. COVID-19 cases in care homes were mainly driven by care home local-area COVID-19 cases and infections among the staff members. Digital deterioration trackers should be co-produced with care home staff, and local authorities should provide long-term support in their adoption and use.

Indexed as

COVID-19AdultHumansNursing HomesPandemicsPersonal Protective EquipmentProspective StudiesCare homesCOVID-19Digital tracker useGreater ManchesterImpact evaluationPanel data

Identifiers

PMID36690927
PMCPMC9869837
OpenAlexW4317752005

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.