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      Digital health system for personalised COPD long-term management

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          Abstract

          Background

          Recent 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.

          Methods

          A 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.

          Results

          The 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.

          Conclusions

          Strategies 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 registration

          Trial registration: ISRCTN40367841. Registered 17/10/2012.

          Related collections

          Most cited references14

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          Understanding factors affecting patient and public engagement and recruitment to digital health interventions: a systematic review of qualitative studies

          Background Numerous types of digital health interventions (DHIs) are available to patients and the public but many factors affect their ability to engage and enrol in them. This systematic review aims to identify and synthesise the qualitative literature on barriers and facilitators to engagement and recruitment to DHIs to inform future implementation efforts. Methods PubMed, MEDLINE, CINAHL, Embase, Scopus and the ACM Digital Library were searched for English language qualitative studies from 2000 – 2015 that discussed factors affecting engagement and enrolment in a range of DHIs (e.g. ‘telemedicine’, ‘mobile applications’, ‘personal health record’, ‘social networking’). Text mining and additional search strategies were used to identify 1,448 records. Two reviewers independently carried out paper screening, quality assessment, data extraction and analysis. Data was analysed using framework synthesis, informed by Normalization Process Theory, and Burden of Treatment Theory helped conceptualise the interpretation of results. Results Nineteen publications were included in the review. Four overarching themes that affect patient and public engagement and enrolment in DHIs emerged; 1) personal agency and motivation; 2) personal life and values; 3) the engagement and recruitment approach; and 4) the quality of the DHI. The review also summarises engagement and recruitment strategies used. A preliminary DIgital Health EnGagement MOdel (DIEGO) was developed to highlight the key processes involved. Existing knowledge gaps are identified and a number of recommendations made for future research. Study limitations include English language publications and exclusion of grey literature. Conclusion This review summarises and highlights the complexity of digital health engagement and recruitment processes and outlines issues that need to be addressed before patients and the public commit to digital health and it can be implemented effectively. More work is needed to create successful engagement strategies and better quality digital solutions that are personalised where possible and to gain clinical accreditation and endorsement when appropriate. More investment is also needed to improve computer literacy and ensure technologies are accessible and affordable for those who wish to sign up to them. Systematic review registration International Prospective Register of Systematic Reviews CRD42015029846 Electronic supplementary material The online version of this article (doi:10.1186/s12911-016-0359-3) contains supplementary material, which is available to authorized users.
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            Telehealthcare for chronic obstructive pulmonary disease: Cochrane Review and meta-analysis.

            Chronic obstructive pulmonary disease (COPD) is common. Telehealthcare, involving personalised health care over a distance, is seen as having the potential to improve care for people with COPD. To systematically review the effectiveness of telehealthcare interventions in COPD to improve clinical and process outcomes. Cochrane Systematic Review of randomised controlled trials. The study involved searching the Cochrane Airways Group Register of Trials, which is derived from the Cochrane Central Register of Controlled Trials, MEDLINE, embase, and CINAHL, as well as searching registers of ongoing and unpublished trials. Randomised controlled trials comparing a telehealthcare intervention with a control intervention in people with a clinical diagnosis of COPD were identified. The main outcomes of interest were quality of life and risk of emergency department visit, hospitalisation, and death. Two authors independently selected trials for inclusion and extracted data. Study quality was assessed using the Cochrane Collaboration's risk of bias method. Meta-analysis was undertaken using fixed effect and/or random effects modelling. Ten randomised controlled trials were included. Telehealthcare did not improve COPD quality of life: mean difference -6.57 (95% confidence interval [CI] = -13.62 to 0.48). However, there was a significant reduction in the odds ratios (ORs) of emergency department attendance (OR = 0.27; 95% CI = 0.11 to 0.66) and hospitalisation (OR = 0.46; 95% CI = 0.33 to 0.65). There was a non-significant change in the OR of death (OR = 1.05; 95% CI = 0.63 to 1.75). In COPD, telehealthcare interventions can significantly reduce the risk of emergency department attendance and hospitalisation, but has little effect on the risk of death.
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              Using a mobile health application to support self-management in COPD: a qualitative study.

              Telehealth shows promise for supporting patients in managing their long-term health conditions, such as chronic obstructive pulmonary disease (COPD). However, it is currently unclear how patients, and particularly older people, may benefit from these technological interventions.
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                Author and article information

                Contributors
                carmelo.velardo@eng.ox.ac.uk
                syed.shah@ndcn.ox.ac.uk
                oliver.gibson@oxehealth.com
                gari@alum.mit.edu
                carl.heneghan@phc.ox.ac.uk
                heather.rutter@phc.ox.ac.uk
                andrew.farmer@phc.ox.ac.uk
                lionel.tarassenko@eng.ox.ac.uk
                Journal
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central (London )
                1472-6947
                20 February 2017
                20 February 2017
                2017
                : 17
                : 19
                Affiliations
                [1 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Engineering Science, , University of Oxford, ; IBME, Oxford, UK
                [2 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Nuffield Department of Primary Care Health Sciences, , University of Oxford, ; Oxford, UK
                Author information
                http://orcid.org/0000-0003-4836-3743
                Article
                414
                10.1186/s12911-017-0414-8
                5319140
                28219430
                0c4fc18b-4605-432c-bdb8-2ea2b5f65e59
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 August 2016
                : 8 February 2017
                Funding
                Funded by: Health Innovation Challenge Fund - Department of Health and Wellcome Trust
                Award ID: HICF-1010-032
                Award ID: HICF-1010-032
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Bioinformatics & Computational biology
                copd,self-management,digital health,adaptive thresholds,automatic alerts

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