From negotiating at-risk contracts to improving quality measures, population health initiatives require a flexible, adaptable data analytics platform. Learn how the most successful organizations are tackling these quality-related problems.
To provide the highest quality, most appropriate, and most cost-effective care for patients, healthcare organizations must transform around value-based care. Making the associated clinical, operational, and financial changes will require a data- and analytics-powered strategic toolset. Organizations will adapt and thrive when they combine data and strategy to focus population health efforts on the most impactful initiatives, based on populations and contracts.
Within this vital shift to value-base contracts, good performance against quality measures is central to success. Yet, while governmental and commercial-payer measures aim to improve patient outcomes via emphasis on preventive and evidence-based care, these measure have also proved to be an administrative burden for many organizations. In response, systems must simultaneously raise their performance against specific measures while streamlining the effort required to calculate and report it.
From negotiating at-risk contracts to improving quality measures, population health initiatives require a flexible, adaptable data analytics platform. Here is how the most successful organizations are tackling these quality-related problems.
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