Designing and Undertaking a Health Economics Study of Digital Health Interventions

McNamee, Paul; Murray, Elizabeth; Kelly, Michael P.; Bojke, Laura; Chilcott, Jim; Fischer, Asja; West, Robert; Yardley, Lucy

doi:10.1016/j.amepre.2016.05.007

Cited by 71 publications

(88 citation statements)

References 43 publications

(49 reference statements)

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“…A central motivation for DBCIs is that they may be cost effective—and certainly cheaper than their face-to-face counterparts—because they can rapidly increase scale at minimal cost. Generating accurate evidence of cost effectiveness will be essential in gaining support from health system payers, but it requires additional consideration beyond conventional analysis (see [7]).…”

Section: Resultsmentioning

confidence: 99%

“…Scribes were appointed from the writing groups to take and circulate notes of relevant points for each paper and the proceedings were audio-recorded. The writing groups developed five articles after the workshop, now published in the American Journal of Preventive Medicine (AJPM) [1,3-7]. …”

Section: Methodsmentioning

confidence: 99%

“…The workshop led to a series of publications [3-7]. This paper discusses key recommendations arising from the workshop and subsequent discussion.…”

Section: Introductionmentioning

confidence: 99%

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Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop

Michie¹,

Yardley²,

West³

et al. 2017

J Med Internet Res

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690

572

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Devices and programs using digital technology to foster or support behavior change (digital interventions) are increasingly ubiquitous, being adopted for use in patient diagnosis and treatment, self-management of chronic diseases, and in primary prevention. They have been heralded as potentially revolutionizing the ways in which individuals can monitor and improve their health behaviors and health care by improving outcomes, reducing costs, and improving the patient experience. However, we are still mainly in the age of promise rather than delivery. Developing and evaluating these digital interventions presents new challenges and new versions of old challenges that require use of improved and perhaps entirely new methods for research and evaluation. This article discusses these challenges and provides recommendations aimed at accelerating the rate of progress in digital behavior intervention research and practice. Areas addressed include intervention development in a rapidly changing technological landscape, promoting user engagement, advancing the underpinning science and theory, evaluating effectiveness and cost-effectiveness, and addressing issues of regulatory, ethical, and information governance. This article is the result of a two-day international workshop on how to create, evaluate, and implement effective digital interventions in relation to health behaviors. It was held in London in September 2015 and was supported by the United Kingdom’s Medical Research Council (MRC), the National Institute for Health Research (NIHR), the Methodology Research Programme (PI Susan Michie), and the Robert Wood Johnson Foundation of the United States (PI Kevin Patrick). Important recommendations to manage the rapid pace of change include considering using emerging techniques from data science, machine learning, and Bayesian approaches and learning from other disciplines including computer science and engineering. With regard to assessing and promoting engagement, a key conclusion was that sustained engagement is not always required and that for each intervention it is useful to establish what constitutes “effective engagement,” that is, sufficient engagement to achieve the intended outcomes. The potential of digital interventions for testing and advancing theories of behavior change by generating ecologically valid, real-time objective data was recognized. Evaluations should include all phases of the development cycle, designed for generalizability, and consider new experimental designs to make the best use of rich data streams. Future health economics analyses need to recognize and model the complex and potentially far-reaching costs and benefits of digital interventions. In terms of governance, developers of digital behavior interventions should comply with existing regulatory frameworks, but with consideration for emerging standards around information governance, ethics, and interoperability.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop

Michie¹,

Yardley²,

West³

et al. 2017

J Med Internet Res

Self Cite

690

572

View full text Add to dashboard Cite

show abstract

“…Furthermore, digital technology including mobile health applications and wearable technologies may be useful when combined with patient education and behavioral theory as a way increase levels of physical activity and exercise . However, there is a lack of evidence regarding the cost‐effectiveness of digital health interventions, and economic evaluations are required to inform decision makers with regard to the allocation of resources in this area . Novel interventions are also required to support adherence to IDE programs.…”

Section: Discussionmentioning

confidence: 99%

Barriers and facilitators for engagement and implementation of exercise in end‐stage kidney disease: Future theory‐based interventions using the Behavior Change Wheel

Clarke

Jhamb

Bennett

2019

Seminars in Dialysis

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Theory‐driven interventions are required to increase the adoption and implementation of physical activity and exercise programs among patients with ESKD. The Behavior Change Wheel (BCW) represents a synthesis of behavior change theories and can be used to aid the systematic development of theory‐driven interventions designed to change exercise behavior. The goal of this review was to synthesize barriers and facilitators to engagement and implementation of exercise and develop theory‐based recommendations for exercise behavior change interventions in patients with ESKD. We applied the BCW in the current context of exercise for ESKD patients and conducted an analysis of patients’ and health care professionals’ (HCPs) capabilities, opportunities, and motivations to engage or promote exercise, respectively. Our analysis identified a number of salient barriers that could be targeted via intervention to increase levels of physical activity and exercise. Intervention functions identified as most likely to change patient behavior included training, enablement, education, restructuring environment, persuasion, modeling, incentivizing, and coercion. Similarly, intervention functions most likely to change HCPs behavior for exercise promotion included training, modeling, education, environmental restructuring, persuasion, and incentivizing. We also considered potential over‐arching policy changes required to support these interventions. Our findings provide theory‐based recommendations that can help inform future clinical and research decision‐making for implementing exercise interventions in these patients. However, high‐quality research in this area is desperately needed to ensure that interventions not only be theory‐driven, but evidence‐based.

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“…The success of digital health interventions for reaching and supporting individuals with mental illness will be largely determined by whether we can uncover specific behavioral mechanisms responsible for effectively managing mental health symptoms, preventing relapse, or reinforcing the adoption and maintenance of healthy behaviors. Future sustainability of digital technology interventions will also depend on carefully planned economic evaluation (McNamee et al, 2016), where the development, maintenance, and running costs of these interventions combined with the costs needed to adapt to rapidly changing technological platforms are balanced against potentially meaningful mental or physical health outcomes experienced by individuals living with mental illness. Mental disorders represent the leading cause of disability worldwide, and therefore identifying ways to effectively reach these individuals represents a major public health priority.…”

Section: Conclusion and Implications For Practicementioning

confidence: 99%

Health behavior models for informing digital technology interventions for individuals with mental illness.

Naslund

Aschbrenner

Kim

et al. 2017

Psychiatric Rehabilitation Journal

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Objective Theoretical models offer valuable insights for designing effective and sustainable behavioral health interventions, yet the application of theory for informing digital technology interventions for people with mental illness has received limited attention. We offer a perspective on the importance of applying behavior theories and models to developing digital technology interventions for addressing mental and physical health concerns among people with mental illness. Methods In this commentary, we summarize prominent theories of human behavior, highlight key theoretical constructs, and identify opportunities to inform digital health interventions for people with mental illness. We consider limitations with existing theories and models, and examine recent theoretical advances that can specifically guide development of digital technology interventions Results Established behavioral frameworks including Health Belief Model, Theory of Planned Behavior, Transtheoretical Model, and Social Cognitive Theory consist of important and overlapping constructs that can inform digital health interventions for people with mental illness. As digital technologies continue to evolve and enable longitudinal data collection, real-time behavior monitoring, and adaptive features tailored to users’ changing needs over time, there are new opportunities to broaden our understanding of health behaviors and mechanisms of behavior change. Recent advances include dynamic models of behavior, Persuasive System Design, the Behavioral Intervention Technology model, and behavioral models for Just-In-Time Adaptive Interventions. Conclusions and Implications for Practice Behavior theories offer advantages for guiding use of digital technologies. Future research must explore how theoretical models can effectively advance efforts to develop, evaluate, and disseminate digital health interventions targeting individuals with mental illness.

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Designing and Undertaking a Health Economics Study of Digital Health Interventions

Cited by 71 publications

References 43 publications

Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop

Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop

Barriers and facilitators for engagement and implementation of exercise in end‐stage kidney disease: Future theory‐based interventions using the Behavior Change Wheel

Health behavior models for informing digital technology interventions for individuals with mental illness.

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