Arun Sundararaman
The functioning of Public Health Data Repositories is poised for major transformation, emerging from post-event data collection to pre-event insight generation and dissemination i.e. from post-epidemic cure to prediction and prevention of epidemics. Public Health domain is set to scale up data capabilities, analytics capabilities, technology capabilities, process capabilities and functional capabilities to be ready for such transformation. On one side, this transformation necessitates the need for shift to the NEW world such as “from traditional data repositories to future state Data & Analytics Platforms” that encompass not merely structured data, but, vast streams and variety of unstructured data (e.g. clinical notes, physician notes, patient notes, images, patient experience pulses through audio and video forms of data). And on the other side, data infrastructure for epidemics management requires extensive collaboration between Hospitals, Pharmacies, citizen services departments (not just healthcare), Health Data Exchanges and connected health eco-systems. These complexities necessitate next generation big data technologies led Healthcare Data Management practices to revolutionize Healthcare Information Management in addressing today’s key challenge that healthcare information is scattered in 4 different islands of data sets i.e. Health Administration, Clinical/Hospital in EHRs, individual data in PHRs and environmental data in Public domain. This paper covers specific recommendations around transformation to big data platforms for epidemic data sets, what to leverage from existing data sets to gaps and data opportunities to tap and proposes an innovative Public Health Epidemics Big Data Infrastructure Maturity Model to chart the course of this transformation.
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