Evidence map›Paper›PMID 37246188›Full record

ReviewApplied health economics and health policy2023

myCOPD App for Managing Chronic Obstructive Pulmonary Disease: A NICE Medical Technology Guidance for a Digital Health Technology.

Heather Davies, Mary Chappell, Yingying Wang, Angaja Phalguni, Stephanie Wake, Mick Arber, Judith Shore

Abstract readReview
In one paragraph

Review in Applied health economics and health policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Delivery of Remote Pulmonary Rehabilitation: COVID-19 Service Evaluation in England.International journal of chronic obstructive pulmonary disease · 2025
    Article
  6. Review
  7. Article
  8. Use of Ecological Momentary Assessment to Measure Dyspnea in COPD.International journal of chronic obstructive pulmonary disease · 2024
    Article
  9. 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

7 authors.

Heather DaviesYork Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, YO10 5NQ, York, UK. Heather.r.davies@york.ac.uk.ORCID http://orcid.org/0000-0003-1943-3765
Mary ChappellYork Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, YO10 5NQ, York, UK.ORCID http://orcid.org/0000-0002-3789-0727
Yingying WangMedical Technologies Evaluation Programme, National Institute for Health and Care Excellence Level 1A, City Tower, Piccadilly Plaza, Manchester, M1 4BT, UK.
Angaja PhalguniYork Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, YO10 5NQ, York, UK.
Stephanie WakeYork Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, YO10 5NQ, York, UK.
Mick ArberYork Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, YO10 5NQ, York, UK.
Judith ShoreYork Health Economics Consortium, Enterprise House, Innovation Way, University of York, Heslington, YO10 5NQ, York, UK.ORCID http://orcid.org/0000-0002-5785-5937

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

myCOPD is a digital tool designed for people to manage their chronic obstructive pulmonary disease (COPD). It requires a device with an internet connection and incorporates tools for education, self-management, symptom tracking and pulmonary rehabilitation (PR). myCOPD was selected for medical technologies guidance by the UK National Institute for Health and Care Excellence (NICE) in 2020. The External Assessment Group (EAG) critiqued the company's submission. The evidence comprised four clinical studies (three randomised controlled trials [RCTs] and one observational study) and real-world evidence from 22 documents. The RCTs had small sample sizes, limiting the power to detect statistically significant differences and to match patient characteristics across arms. The company produced two de novo models for two subgroups of people with COPD; people discharged from hospital with acute exacerbation of COPD (AECOPD) and people referred for PR. After the EAG updated input parameters and adjusted the model structures, cost savings of £86,297 per clinical commissioning group (CCG) compared with standard care were estimated for the AECOPD population, with myCOPD predicted to be cost saving in 74% of iterations. Cost savings of £22,779 per CCG were estimated for the PR population (with the assumption that the CCG had an existing myCOPD licence), with myCOPD predicted to be cost saving in 86% of the iterations. The Medical Technologies Advisory Committee concluded that although myCOPD has the potential to help manage COPD in adults, further evidence is required to address uncertainties in the current evidence base. NICE published this as Medical Technology Guidance 68 (National Institute for Health and Care Excellence (NICE). myCOPD for managing chronic obstructive pulmonary disease. 2022. Available at: https://www.nice.org.uk/guidance/mtg68/ ).

Indexed as

Mobile ApplicationsPulmonary Disease, Chronic ObstructiveAdultCost-Benefit AnalysisHumansObservational Studies as TopicTechnologyTechnology Assessment, Biomedical

Identifiers

PMID37246188
PMCPMC10403412

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.