Advances in Data Driven Responses to Preventing Spread of Antibiotic Resistance across Healthcare Settings.

Abstract

Among the most urgent and serious antibiotic resistant threats to public health, seven are bacteria predominately acquired during health care delivery. There is an emerging field of healthcare epidemiology focused on preventing healthcare-associated infections with antibiotic resistant bacteria incorporating data from patient transfers or patient movements both within and between facilities; this analytic field is being used to help public health professionals identify best opportunities for prevention. Different analytic approaches drawing on uses of big data is being explored to help target the use of limited public health resources, leverage expertise, and enact effective policy to maximize an impact on a population-level health. This paper will summarize recent advances in data driven responses to preventing spread of antibiotic resistance across healthcare settings: leveraging big data for machine learning, integration or advances in tracking patient movement, and highlighting the value of coordinating response across institutions within a region.