Evidence map›Paper›PMID 36963909›Full record

Observational studyThe Lancet. Digital health2023

Factors associated with enrolment into a national COVID-19 pulse oximetry remote monitoring programme in England: a retrospective observational study.

Jonathan Clarke, Thomas Beaney, Ahmed Alboksmaty, Kelsey Flott, Hutan Ashrafian, Aidan Fowler, Jonathan R Benger, Paul Aylin, Sarah Elkin, Ana Luisa Neves and 1 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in The Lancet. Digital health, 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
0.7field-weighted citation impact, top 24% 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, 3 citations in OpenAlex.

  1. Pulse oximeter bench tests under different simulated skin tones.Medical & biological engineering & computing · 2025
    Article
  2. Review
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

11 authors at 4 institutions in 2 countries.

Jonathan ClarkePatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK; Centre for Mathematics of Precision Healthcare, Department of Mathematics, Imperial College London, London, UK. Electronic address: j.clarke@imperial.ac.uk.
Thomas BeaneyPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK; Department of Primary Care and Public Health, Imperial College London, London, UK.
Ahmed AlboksmatyPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK; Department of Primary Care and Public Health, Imperial College London, London, UK.
Kelsey FlottPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK.
Hutan AshrafianPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK.
Aidan FowlerNHS England and Improvement, London, UK.
Jonathan R BengerNHS Digital, Leeds, UK.
Paul AylinPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK; Department of Primary Care and Public Health, Imperial College London, London, UK.
Sarah ElkinNational Heart and Lung Institute, Imperial College London, London, UK.
Ana Luisa NevesPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK.
Ara DarziPatient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK.
NHS EnglandImperial College London · GBLung Institute · USNIHR Imperial Biomedical Research Centre · GB

Funding

Department of HealthWellcome TrustWellcome Trust 215938/Z/19/Z
6 · The paper itself

Abstract

backgroundHypoxaemia is an important predictor of severity in individuals with COVID-19 and can present without symptoms. The COVID Oximetry @home (CO@h) programme was implemented across England in November, 2020, providing pulse oximeters to higher-risk people with COVID-19 to enable early detection of deterioration and the need for escalation of care. We aimed to describe the clinical and demographic characteristics of individuals enrolled onto the programme and to assess whether there were any inequalities in enrolment.

methodsThis retrospective observational study was based on data from a cohort of people resident in England recorded as having a positive COVID-19 test between Oct 1, 2020, and May 3, 2021. The proportion of participants enrolled onto the CO@h programmes in the 7 days before and 28 days after a positive COVID-19 test was calculated for each clinical commissioning group (CCG) in England. Two-level hierarchical multivariable logistic regression with random intercepts for each CCG was run to identify factors predictive of being enrolled onto the CO@h programme.

findingsCO@h programme sites were reported by NHS England as becoming operational between Nov 21 and Dec 31, 2020. 1 227 405 people resident in 72 CCGs had a positive COVID-19 test between the date of programme implementation and May 3, 2021, of whom 19 932 (1·6%) were enrolled onto the CO@h programme. Of those enrolled, 14 441 (72·5%) were aged 50 years or older or were identified as clinically extremely vulnerable (ie, having a high-risk medical condition). Higher odds of enrolment onto the CO@h programme were found in older individuals (adjusted odds ratio 2·21 [95% CI 2·19-2·23], p<0·001, for those aged 50-64 years; 3·48 [3·33-3·63], p<0·001, for those aged 65-79 years; and 2·50 [2·34-2·68], p<0·001, for those aged ≥80 years), in individuals of non-White ethnicity (1·35 [1·28-1·43], p<0·001, for Asian individuals; 1·13 [1·04-1·22], p=0·005, for Black individuals; and 1·17 [1·03-1·32], p=0·015, for those of mixed ethnicity), in those who were overweight (1·31 [1·26-1·37], p<0·001) or obese (1·69 [1·63-1·77], p<0·001), or in those identified as clinically extremely vulnerable (1·58 [1·51-1·65], p<0·001), and lower odds were reported in those from the least socioeconomically deprived areas compared with those from the most socioeconomically deprived areas (0·75 [0·69-0·81]; p<0·001).

interpretationNationally, uptake of the CO@h programme was low, with clinical judgment used to determine eligibility. Preferential enrolment onto the pulse oximetry monitoring programme was observed in people known to be at the highest risk of developing severe COVID-19.

fundingNHS England, National Institute for Health Research, and The Wellcome Trust.

Indexed as

COVID-19AgedEnglandHumansObesityPhysical ExaminationRetrospective Studies

Identifiers

PMID36963909
PMCPMC10032661
OpenAlexW4353031168

What OpenQuestion holds

Textmetadata
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.