Co-opetition to advance the science and practice of digital health behavior change
By Artur Direito, on 11 May 2018
By Dr. Melanie Hingle (1) with Dr. Heather Patrick (2), Dr. Paul Sacher (3), and Dr. Cynthia Castro Sweet (4)
(1) University of Arizona, (2) Carrot Inc., (3) Slimming World USA (3), (4) Omada Health
Leaders in the field of digital health have called for improved collaborative models of research and development that benefit both academia and industry science, creating new directions for behavioral research and producing measurable and clinically significant impacts on health. Recent industry shifts suggest that businesses increasing recognize the value of behavioral science research and are using this to build better products and differentiate themselves in the growing digital health marketplace. For instance, scientific advisory boards and executive leadership positions featuring “scientist” in the title are burgeoning; both of these general strategies concentrate scientific expertise in a manner that is directly applicable to product research/development and market strategy.
Despite some successful commercialization efforts in the field of digital health (e.g., diabetes, weight management, smoking), wide spread impact of digital health on health behavior change and related outcomes remains limited. This underperformance may in part be attributed to the parallel development efforts of academic and industry in the field of digital health, wherein both are interested in designing effective products, yet fail to converge around their unique and complementary strengths. There is an opportunity for a new model of collaboration that impacts the field of digital health, serves the end-user, and benefits both academic and industry interests, built around the neologism “co-opetition” (or cooperative competition) in which organizations sharing market space and interests work together to develop new knowledge and reach a higher value product.
Experts across the field of digital health have recommended inflection points for advancing the field of digital health, around which an academics and industry professionals might converge their respective expertise, including rapid and efficient development, understanding and promoting engagement, evaluating effectiveness, and ensuring ethical standards of digital health products and their delivery. For those wishing to engage in “co-opetition” with an academic or an industry partner in the digital health space, recognizing three key differences between these sectors may contribute to smoother advancement down this path:
1) Practical considerations and constraints of an academic appointment/industry position. Both parties should recognize their capacity to commit to an ongoing partnership and develop the arrangement accordingly. Consider prioritizing activities commensurate with limited availability; be realistic and transparent when committing to deadlines; initiate conversations regarding how academic and industry goals might serve one another (e.g., publications, student/post-doc training opportunities).
2) Mutually agreeable timelines and deliverables. Timelines are one of the most notable differences between industry and academia. For academics, studies unfold predictably over 2- to 5-years (aligned with grant funding periods). For industry, this is an impossibly long time, as market demand and competition create the need for rapid iteration and launching of product development, implementation, and evaluation. Academic and industry collaborators alike must be explicit about trade-offs, changes in scope, and other competing priorities that can get in the way of timely deliverables.
3) Outcome and evaluation metrics that stand up to academic scrutiny while responding to industry priorities. Flexibility in selecting metrics and outcome indicators is key. Academics must consider scientific rigor in designing experiments, thus frequently default to “gold standard” measurements when selecting study metrics. To be sure, these are important when establishing effectiveness of a product on health; however, there are additional opportunities for data collection in the product development and dissemination lifecycle, which may be equally important to industry partners, and also inform the end product. Engagement is a metric that is often considered to be an important primary outcome for industry, while academic researchers are more likely to consider this variable as a process outcome or mediating variable.
- Have you engaged in a successful academic-industry partnership? Tell us what you think were the “secrets” to your success.
- What do you think is the biggest barrier to engaging in a partnership at your institution? (What steps might you take to overcome this?)
Melanie Hingle, PhD, MPH, RDN (University of Arizona, firstname.lastname@example.org, @hinglem) works at the intersection of nutritional sciences research and public health practice, where she seeks to understand predictors and consequences of behavioral risk factors associated with obesity and type 2 diabetesand applythis knowledge to the design and conduct of lifestyle behavior modification interventions for children, adolescents, and their families. Mobile and wireless technologies are frequently featured in these programs.
Special thanks to Heather Patrick, PhD (@HPatrick_PhD, Carrot), Paul Sacher, PhD, RDN (@drpaulsacher, Slimming World), and Cynthia Castro Sweet, PhD (@cynmcsweet, Omada Health), talented behavioral scientists, co-workshop-conspirators, and co-authors of an upcoming commentary on the topic of academic-industry partnerships in digital health, whose excellent ideas and contributions are reflected in this blog post.