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This paper introduces and discusses key issues in the economic evaluation of digital health interventions. The purpose is to stimulate debate so that existing economic techniques may be refined or new methods developed. The paper does not seek to provide definitive guidance on appropriate methods of economic analysis for digital health interventions. This paper describes existing guides and analytic frameworks that have been suggested for the economic evaluation of healthcare interventions. Using selected examples of digital health interventions, it assesses how well existing guides and frameworks align to digital health interventions. It shows that digital health interventions may be best characterized as complex interventions in complex systems. Key features of complexity relate to intervention complexity, outcome complexity, and causal pathway complexity, with much of this driven by iterative intervention development over time and uncertainty regarding likely reach of the interventions among the relevant population. These characteristics imply that more-complex methods of economic evaluation are likely to be better able to capture fully the impact of the intervention on costs and benefits over the appropriate time horizon. This complexity includes wider measurement of costs and benefits, and a modeling framework that is able to capture dynamic interactions among the intervention, the population of interest, and the environment. The authors recommend that future research should develop and apply more-flexible modeling techniques to allow better prediction of the interdependency between interventions and important environmental influences. ; This paper is one of the outputs of two workshops, one supported by the Medical Research Council (MRC)/National Institute for Health Research (NIHR) Methodology Research Programme (PI Susan Michie) and the Robert Wood Johnson Foundation (PI Kevin Patrick), and the other by the National Science Foundation (PI Donna Spruitj-Metz, proposal # 1539846). The Health Economics Research Unit is funded in part by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. ; This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Elsevier.

This 2016 theme section of the American Journal of Preventive Medicine is supported by funding from the NIH Office of Behavioral and Social Sciences Research (OBSSR) to support the dissemination of research on digital health interventions, methods, and implications for preventive medicine. This paper is one of the outputs of two workshops, one supported by the Medical Research Council (MRC)/National Institute for Health Research (NIHR) Methodology Research Program (PI Susan Michie), the OBSSR (William Riley, Director) and the Robert Wood Johnson Foundation (PI Kevin Patrick); and the other by the National Science Foundation (PI Donna Spruitj-Metz, proposal # 1539846). The Health Economics Research Unit is funded in part by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Laura Bojke was supported in the preparation/submission of this paper by the HEOM Theme of the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care Yorkshire and Humber (NIHR CLAHRC YH, www.clarhrc-yh.nir.ac.uk). The views expressed in the paper are those of the authors alone and do not necessarily represent those of the funders. Elizabeth Murray is Managing Director of a not-for-profit Community Interest Company, HeLP-Digital, which aims to disseminate digital health interventions to the National Health Service. No other financial disclosures were reported by the author of this paper. ; Peer reviewed ; Postprint