Just a few years ago, health systems were generally operated as revenue centers—the more patients seen, the more money made. But, in today’s reality of outcomes-based reimbursement, hospitals must be run as cost centers—ensuring their margins by eliminating the process inefficiencies and waste that contribute to hospital readmissions, reduced reimbursement and costly penalties.
To improve quality of care while reducing unnecessary costs (e.g., duplicate tests, avoidable readmissions), providers need to be able to access and make sense of many untraditional types of patient data, including demographic and social information found in unstructured free text physician notes, diagnostic images and other sources.
However, according to JAMA, advances in analytics techniques are in contrast to traditional statistical methods which are “largely not useful for analysis of unstructured data such as text-based documents that do not fit into relational tables.”*
The remedy lies in building a flexible data strategy.
Ultimately, striking an ideal balance of improving patient outcomes and reducing process inefficiencies and unnecessary costs will require a robust and flexible data strategy that enables a 360-view across all data sources to enhance clinical interventions specific to each patient. The problem is that trying to create this agile strategy on rigid, outdated technology is, in and of itself—costly and inefficient.
There is a better way …
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Three Questions for Your Healthcare Data Strategy: With healthcare data projected to grow to a staggering 25,000 petabytes by 2020—for context, just one petabyte can hold 500 billion pages of standard printed text—developing a flexible data strategy is critical to a sustainable and competitive enterprise.
Webinar: Is Your Data Strategy Ready for Quality & Payment Reform? As healthcare transitions to a world of risk-based reimbursement, healthcare data strategy must also evolve. Dr. David Nace co-hosts a discussion that outlines strategies for payers, providers and other organizations to leverage high volumes of variable data to improve care coordination and health outcomes.
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