Cost and cost-effectiveness of mHealth interventions for the prevention and control of type 2 diabetes mellitus: A systematic review

Highlights

• A pre specified protocol was registered on the Prospective Register of Systematic Reviews.

• To the best of our knowledge this is the first systematic review on this topic.

• The quality of evidence was assessed using the CHEERS checklist.

• The majority of studies identified were partial economic evaluations.

• There was difficulty in comparing results due to study heterogeneity.

Abstract

The prevalence of type 2 diabetes mellitus continues to rise and simultaneously technology has contributed to the growth of MHealth interventions for its prevention, monitoring and management. This systematic review aimed to summarize and evaluate the quality of the published evidence on cost and cost-effectiveness of mHealth interventions for T2DM. A systematic literature search of PubMed, EMBASE, and Web of Science was conducted for papers up to end of April 2019. We included all partial or full economic evaluations providing cost or cost-effectiveness results for mHealth interventions targeting individuals diagnosed with, or at risk of, type 2 diabetes mellitus. Twenty-three studies met the inclusion criteria. Intervention cost varied substantially based on the type and numbers or combination of technologies used, ranging from 1.8 INT $ to 10101.1 INT $ per patient per year. The studies which presented cost effectiveness results demonstrated highly cost-effective interventions, with cost per QALY gained ranging from 0.4 to 62.5 percent of GDP per capita of the country. The quality of partial economic evaluations was on average lower than that of full economic evaluations. Cost of mHealth interventions varied substantially based on type and combination of technology used, however, where cost-effectiveness results were reported, the intervention was cost-effective.

PROSPERO registration number: CRD42019123476; Registered: 27/01/2019.

Introduction

In 2017, diabetes was ranked as the fourth leading cause of disability globally [1]. The health consequences of diabetes cause a marked loss of productivity and economic burden to patients, healthcare providers and country’s economies, mounting to 1.8% of the global gross domestic product (GDP) and 12% of the global health expenditure in 2018 [2], [3]. Over 80% of yearly deaths due to diabetes occur in developing countries causing drastic economic consequences compared to their developed counterparts [4]. Diabetes is notoriously difficult to control with only about 50% of patients reaching their treatment targets [5]. There are multifactorial explanations for this, including the challenges T2DM poses on patients’ habits surrounding diet and exercise. Many patients demonstrate low willingness to change their perceptions and actions to alter their undesirable lifestyle habits [6], [7]. Moreover, treatment plans often consist of multiple daily pharmacological interventions which contribute to poor medication adherence [8].

Mobile health (mHealth) uses technology to encourage patients’ lifestyle modification and medication adherence by providing portable, every-day interventions to empower patients and encourage them to adhere to their management plans [9]. The rise of mHealth has heavily correlated with the exponential growth in internet access which has allowed for the creation of wireless healthcare opportunities combining patient empowerment with the convenience of mobile devices [10], [11]. MHealth interventions are becoming prominent amongst several medical specialties encompassing preventative, curative and chronic management goals. Additionally, mHealth reduces geographic related disparities in health care by removing physical barriers to accessing medical information and providing individuals a “virtual” platform. Successful MHealth interventions have shown to significantly reduce hospital inpatient admissions and prompt a 63% reduction in number of admission days [12].

MHealth interventions targeting diabetes have shown clinical effectiveness in both the prevention and management of T2DM [13], [14], [15]. Management based interventions have proven to be particularly successful at reducing haemoglobin A_1c (HbA_1c) levels amongst people with T2DM [14]. A meta-analysis investigating mobile phone interventions for glycaemic control demonstrated that among 22 trials there was a statistically significant improvement in glycaemic control amongst users of the online intervention [16]. Similarly, another review found that glycaemic control results were significant amongst T2DM when mobile text messaging interventions were combined with an internet based intervention [17]. MHealth interventions have proven to be low cost and cost-effective across various medical specialties [18], [19]. Economic evidence is crucial to guide policy makers and funders towards implementing mHealth interventions. Nevertheless, there is a large gap in the literature analysing the costs and cost-effectiveness of mHealth interventions addressing T2DM [20]. To the best of our knowledge, there is currently no published literature summarising the cost or cost-effectiveness of mHealth interventions targeting the prevention and control of T2DM. This study aims to systematically review, analyse and summarise the published evidence on the cost and cost-effectiveness of mHealth interventions for T2DM, as well as, to assess the quality of the published evidence.