title: What We Can Learn from Amazon for Clinical Decision Support Systems.
abstract: Health care continue to lag behind other industries, such as retail and financial services, in the use of decision-support-like tools. Amazon is particularly prolific in the use of advanced predictive and prescriptive analytics to assist its customers to purchase more, while increasing satisfaction, retention, repeat-purchases and loyalty. How can we do the same in health care? In this paper, we explore various elements of the Amazon website and Amazon's data science and big data practices to gather inspiration for re-designing clinical decision support in the health care sector. For each Amazon element we identified, we present one or more clinical applications to help us better understand where Amazon's.
authors.affiliation: InfoClin Inc, Toronto, ON.
authors.forename: Sidra
authors.initials: S
authors.lastname: Abid
authors.affiliation: InfoClin Inc, Toronto, ON.
authors.forename: Karim
authors.initials: K
authors.lastname: Keshavjee
authors.affiliation: InfoClin Inc, Toronto, ON.
authors.forename: Arsalan
authors.initials: A
authors.lastname: Karim
authors.affiliation: Ryerson University, Toronto, ON.
authors.forename: Aziz
authors.initials: A
authors.lastname: Guergachi
mesh_terms: D003625:Data Collection; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D057286:Electronic Health Records; D006801:Humans; D000069550:Machine Learning
keywords: A/B testing; Amazon®; algorithm; clinical decision support system; predictive analytics; prescriptive analytics