Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer

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Abstract

Background

Self-management support is one mechanism by which telehealth interventions have been proposed to facilitate management of long-term conditions.

Objective

The objectives of this metareview were to (1) assess the impact of telehealth interventions to support self-management on disease control and health care utilization, and (2) identify components of telehealth support and their impact on disease control and the process of self-management. Our goal was to synthesise evidence for telehealth-supported self-management of diabetes (types 1 and 2), heart failure, asthma, chronic obstructive pulmonary disease (COPD) and cancer to identify components of effective self-management support.

Methods

We performed a metareview (a systematic review of systematic reviews) of randomized controlled trials (RCTs) of telehealth interventions to support self-management in 6 exemplar long-term conditions. We searched 7 databases for reviews published from January 2000 to May 2016 and screened identified studies against eligibility criteria. We weighted reviews by quality (revised A Measurement Tool to Assess Systematic Reviews), size, and relevance. We then combined our results in a narrative synthesis and using harvest plots.

Results

We included 53 systematic reviews, comprising 232 unique RCTs. Reviews concerned diabetes (type 1: n=6; type 2, n=11; mixed, n=19), heart failure (n=9), asthma (n=8), COPD (n=8), and cancer (n=3). Findings varied between and within disease areas. The highest-weighted reviews showed that blood glucose telemonitoring with feedback and some educational and lifestyle interventions improved glycemic control in type 2, but not type 1, diabetes, and that telemonitoring and telephone interventions reduced mortality and hospital admissions in heart failure, but these findings were not consistent in all reviews. Results for the other conditions were mixed, although no reviews showed evidence of harm. Analysis of the mediating role of self-management, and of components of successful interventions, was limited and inconclusive. More intensive and multifaceted interventions were associated with greater improvements in diabetes, heart failure, and asthma.

Conclusions

While telehealth-mediated self-management was not consistently superior to usual care, none of the reviews reported any negative effects, suggesting that telehealth is a safe option for delivery of self-management support, particularly in conditions such as heart failure and type 2 diabetes, where the evidence base is more developed. Larger-scale trials of telehealth-supported self-management, based on explicit self-management theory, are needed before the extent to which telehealth technologies may be harnessed to support self-management can be established.

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Most cited references 57

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

Siobhan O’Connor, Peter Hanlon, Catherine A O'Donnell … (2016)

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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Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis.

X Liang, Q. Wang, X. YANG … (2011)

To assess the effect of mobile phone intervention on glycaemic control in diabetes self-management. We searched three electronic databases (PubMed, EMBASE and Cochrane Library) using the following terms: diabetes or diabetes mellitus and mobile phone or cellular phone, or text message. We also manually searched reference lists of relevant papers to identify additional studies. Clinical studies that used mobile phone intervention and reported changes in glycosylated haemoglobin (HbA(1c) ) values in patients with diabetes were reviewed. The study design, intervention methods, sample size and clinical outcomes were extracted from each trial. The results of the HbA(1c) change in the trials were pooled using meta-analysis methods. A total of 22 trials were selected for the review. Meta-analysis among 1657 participants showed that mobile phone interventions for diabetes self-management reduced HbA(1c) values by a mean of 0.5% [6 mmol/mol; 95% confidence interval, 0.3-0.7% (4-8 mmol/mol)] over a median of 6 months follow-up duration. In subgroup analysis, 11 studies among Type 2 diabetes patients reported significantly greater reduction in HbA(1c) than studies among Type 1 diabetes patients [0.8 (9 mmol/mol) vs. 0.3% (3 mmol/mol); P=0.02]. The effect of mobile phone intervention did not significantly differ by other participant characteristics or intervention strategies. Results pooled from the included trials provided strong evidence that mobile phone intervention led to statistically significant improvement in glycaemic control and self-management in diabetes care, especially for Type 2 diabetes patients. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

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The harvest plot: A method for synthesising evidence about the differential effects of interventions

David Ogilvie, Debra Fayter, Mark Petticrew … (2008)

Background One attraction of meta-analysis is the forest plot, a compact overview of the essential data included in a systematic review and the overall 'result'. However, meta-analysis is not always suitable for synthesising evidence about the effects of interventions which may influence the wider determinants of health. As part of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking, we designed a novel approach to synthesis intended to bring aspects of the graphical directness of a forest plot to bear on the problem of synthesising evidence from a complex and diverse group of studies. Methods We coded the included studies (n = 85) on two methodological dimensions (suitability of study design and quality of execution) and extracted data on effects stratified by up to six different dimensions of inequality (income, occupation, education, gender, race or ethnicity, and age), distinguishing between 'hard' (behavioural) and 'intermediate' (process or attitudinal) outcomes. Adopting a hypothesis-testing approach, we then assessed which of three competing hypotheses (positive social gradient, negative social gradient, or no gradient) was best supported by each study for each dimension of inequality. Results We plotted the results on a matrix ('harvest plot') for each category of intervention, weighting studies by the methodological criteria and distributing them between the competing hypotheses. These matrices formed part of the analytical process and helped to encapsulate the output, for example by drawing attention to the finding that increasing the price of tobacco products may be more effective in discouraging smoking among people with lower incomes and in lower occupational groups. Conclusion The harvest plot is a novel and useful method for synthesising evidence about the differential effects of population-level interventions. It contributes to the challenge of making best use of all available evidence by incorporating all relevant data. The visual display assists both the process of synthesis and the assimilation of the findings. The method is suitable for adaptation to a variety of questions in evidence synthesis and may be particularly useful for systematic reviews addressing the broader type of research question which may be most relevant to policymakers.

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Author and article information

Contributors

Hilary Pinnock:

Allergy and Respiratory Research GroupUsher Institute of Population Health Sciences and InformaticsUniversity of EdinburghMedical SchoolTeviot PlaceEdinburgh, EH8 9AGUnited Kingdom44 131 650 947444 131 650 9119hilary.pinnock@ed.ac.uk

ORCID: http://orcid.org/0000-0002-5976-8386

Journal

Journal ID (nlm-ta): J Med Internet Res

Journal ID (iso-abbrev): J. Med. Internet Res

Journal ID (publisher-id): JMIR

Title: Journal of Medical Internet Research

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Print): 1439-4456

ISSN (Electronic): 1438-8871

Publication date Collection: May 2017

Publication date (Electronic): 17 May 2017

Volume: 19

Issue: 5

Electronic Location Identifier: e172

Affiliations

[1] ¹Usher Institute of Population Health Sciences and Informatics University of Edinburgh EdinburghUnited Kingdom

[2] ²Allergy and Respiratory Research Group Usher Institute of Population Health Sciences and Informatics University of Edinburgh EdinburghUnited Kingdom

[3] ³E-Health Group Usher Institute of Population Health Sciences and Informatics University of Edinburgh EdinburghUnited Kingdom

Author notes

Corresponding Author: Hilary Pinnock hilary.pinnock@ 123456ed.ac.uk

Author information

Peter Hanlon http://orcid.org/0000-0002-5828-3934

Luke Daines http://orcid.org/0000-0003-0564-4000

Christine Campbell http://orcid.org/0000-0003-4868-0554

Brian McKinstry http://orcid.org/0000-0001-9581-0468

David Weller http://orcid.org/0000-0002-8112-718X

Hilary Pinnock http://orcid.org/0000-0002-5976-8386

Article

Publisher ID: v19i5e172

DOI: 10.2196/jmir.6688

PMC ID: 5451641

PubMed ID: 28526671

SO-VID: 8e36cc2e-d2b7-4923-a983-97cda5742eed

Copyright © ©Peter Hanlon, Luke Daines, Christine Campbell, Brian McKinstry, David Weller, Hilary Pinnock. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.05.2017.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 26 September 2016

Date revision requested : 7 January 2017

Date revision received : 22 February 2017

Date accepted : 9 March 2017

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