title: A model for 'reverse innovation' in health care.
abstract: 'Reverse innovation,' a principle well established in the business world, describes the flow of ideas from emerging to more developed economies. There is strong and growing interest in applying this concept to health care, yet there is currently no framework for describing the stages of reverse innovation or identifying opportunities to accelerate the development process. This paper combines the business concept of reverse innovation with diffusion of innovation theory to propose a model for reverse innovation as a way to innovate in health care. Our model includes the following steps: (1) identifying a problem common to lower- and higher-income countries; (2) innovation and spread in the low-income country (LIC); (3) crossover to the higher-income country (HIC); and (4) innovation and spread in the HIC. The crucial populations in this pathway, drawing from diffusion of innovation theory, are LIC innovators, LIC early adopters, and HIC innovators. We illustrate the model with three examples of current reverse innovations. We then propose four sets of specific actions that forward-looking policymakers, entrepreneurs, health system leaders, and researchers may take to accelerate the movement of promising solutions through the reverse innovation pipeline: (1) identify high-priority problems shared by HICs and LICs; (2) create slack for change, especially for LIC innovators, LIC early adopters, and HIC innovators; (3) create spannable social distances between LIC early adopters and HIC innovators; and (4) measure reverse innovation activity globally.
authors.affiliation: Director, Global Primary Care Program, Massachusetts General Hospital, Boston, MA, USA. ptlee@partners.org.
authors.forename: Jacqueline W
authors.initials: JW
authors.lastname: Depasse
authors.forename: Patrick T
authors.initials: PT
authors.lastname: Lee
mesh_terms: D003695:Delivery of Health Care; D019049:Developed Countries; D003906:Developing Countries; D004059:Diffusion of Innovation; D014943:Global Health; D006801:Humans; D033181:Information Dissemination; D008962:Models, Theoretical