Healthcare
Astronomical Clock
The 2nd century BC Antikythera mechanism of ancient Greece was used to calculate the positions of the sun, moon, and stars at any given point by use of complex mechanical gears. (courtesy Wikipedia)

Comparative Effectiveness Research

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The growing ascendance of “structured healthcare” in developed & developing nations has brought about a renewed focus on the entire healthcare value chain. By definition, the structured healthcare market is an expansive view of the provider(hospitals, clinics), payer(insurance and claims) and pharmaceutical and medical products sectors.

A growing (but slow) reformation of the healthcare system within the OECD (Organization for Economic Co-operation & Development) countries is aimed to reduce the rate at which costs have been increasing while sustaining its current strengths. These reforms are not only critical to these nations as an economic indicator but also has a far more deepening impact on society at large.

In majority of the OECD countries, healthcare accounts for a significant portion of their national GDP and employ a substantial workforce. Even a sliver of cost reduction has a far reaching impact on the overall cost efficiencies that can be achieved across the value chain.

Healthcare in general has lagged behind other industries in improving operational performance and adopting technology-enabled process improvements. Spending on healthcare per person is on the rise albeit without any obvious evidence of better outcomes.

More than ever at any point in time, the use and leverage of data along with the potential of predictive analytics, is an area that sees growing eminence amongst the measures deployed to yield better outcomes of spending.

Most data in the healthcare domain is fragmented and lies in silos across hospitals (mainly clinical and patient data), claims data(insurance companies), pharmaceutical (including R & D data) and patient behavior (sentiment) data entities.

Although the bigger opportunity lies in the integration of these data pools that could lead to huge benefits in overall process and cost efficiencies, at iQG, the macro level opportunities lie in dissecting the data that lies virgin and untapped within the current silo structures of data.

By unleashing the full potential of predictive analytics and how it can be applied to these various pools of data, we at iQG believe, that the use of statistical algorithms on these data that can be transformed into actionable intelligence and can pave the way to non-holistic cost efficiencies across these data silos.