Evidence map›Paper›PMID 28219430›Full record

Trial reportBMC medical informatics and decision making2017

Digital health system for personalised COPD long-term management.

Carmelo Velardo, Syed Ahmar Shah, Oliver Gibson, Gari Clifford, Carl Heneghan, Heather Rutter, Andrew Farmer, Lionel Tarassenko, EDGE COPD Team

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 8 pooled it
–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

62 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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2 more citing papers are in PubMed but not listed here.

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

9 authors.

Carmelo VelardoDepartment of Engineering Science, University of Oxford, IBME, Oxford, UK. carmelo.velardo@eng.ox.ac.uk.ORCID 0000-0003-4836-3743
Syed Ahmar ShahDepartment of Engineering Science, University of Oxford, IBME, Oxford, UK.
Oliver GibsonDepartment of Engineering Science, University of Oxford, IBME, Oxford, UK.
Gari CliffordDepartment of Engineering Science, University of Oxford, IBME, Oxford, UK.
Carl HeneghanNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Heather RutterNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Andrew FarmerNuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.
Lionel TarassenkoDepartment of Engineering Science, University of Oxford, IBME, Oxford, UK.
EDGE COPD Team

Funding

Department of Health [UK]Wellcome Trust
6 · The paper itself

Abstract

backgroundRecent telehealth studies have demonstrated minor impact on patients affected by long-term conditions. The use of technology does not guarantee the compliance required for sustained collection of high-quality symptom and physiological data. Remote monitoring alone is not sufficient for successful disease management. A patient-centred design approach is needed in order to allow the personalisation of interventions and encourage the completion of daily self-management tasks.

methodsA digital health system was designed to support patients suffering from chronic obstructive pulmonary disease in self-managing their condition. The system includes a mobile application running on a consumer tablet personal computer and a secure backend server accessible to the health professionals in charge of patient management. The patient daily routine included the completion of an adaptive, electronic symptom diary on the tablet, and the measurement of oxygen saturation via a wireless pulse oximeter.

resultsThe design of the system was based on a patient-centred design approach, informed by patient workshops. One hundred and ten patients in the intervention arm of a randomised controlled trial were subsequently given the tablet computer and pulse oximeter for a 12-month period. Patients were encouraged, but not mandated, to use the digital health system daily. The average used was 6.0 times a week by all those who participated in the full trial. Three months after enrolment, patients were able to complete their symptom diary and oxygen saturation measurement in less than 1 m 40s (96% of symptom diaries). Custom algorithms, based on the self-monitoring data collected during the first 50 days of use, were developed to personalise alert thresholds.

conclusionsStrategies and tools aimed at refining a digital health intervention require iterative use to enable convergence on an optimal, usable design. 'Continuous improvement' allowed feedback from users to have an immediate impact on the design of the system (e.g., collection of quality data), resulting in high compliance with self-monitoring over a prolonged period of time (12-month). Health professionals were prompted by prioritisation algorithms to review patient data, which led to their regular use of the remote monitoring website throughout the trial.

trial registrationTrial registration: ISRCTN40367841 . Registered 17/10/2012.

Indexed as

Medical Informatics ApplicationsComputers, HandheldHumansMonitoring, AmbulatoryOximetryPulmonary Disease, Chronic ObstructiveSelf CareTelemedicineAdaptive thresholdsAutomatic alertsCOPDDigital healthSelf-management

Identifiers

PMID28219430
PMCPMC5319140

What OpenQuestion holds

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LicenceCC BY
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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.