Data Science to Patient Value (D2V) is a multidisciplinary research initiative that focuses on Big Data methods, their applications to medicine and health care delivery, and ultimately, the achievement of high value, patient-centered health care. D2V accomplishes this by creating an environment of collaboration and innovation in which the top minds in data science, health care delivery and health services research work closely with patients and other stakeholders to tackle important problems. D2V places a priority on using big data in translation and dissemination work (i.e., implementation science), ensuring that D2V 'products' – be they analytic methods, care pathways or other tools – achieve maximal impact in the real world.
D2V’s approach has three transformational features:
Creation of a multidisciplinary, collaborative analytics and computational research environment that includes medical/health scientists, mathematicians/statiticians, computer/data scientists, informaticists, and implementation scientists.
Consideration of multiple stakeholder perspectives (patients, providers, health systems, payers and policymakers) when conducting research to inform clinical, health system, and policy decisions; and
Collaboration between researchers and clinical operations to design and conduct care delivery interventions, translate evidence into practice and policy, and work with the health system as a real-world innovations laboratory.