Population Health Management

Traditional to Advanced Analytics

Intelligent, actionable insights are delivered.

Traditional Population Health Management methods tend to prioritize high-risk individuals while ignoring areas with intermediate and low health concerns. This is due to the limits of clinical and claims data; clinical research often covers just acute treatment, whereas claims data is largely retrospective and only captures a moment in time rather than the complete care continuum.

PHM solutions, on the other hand, must be timely in order to support proactive, data-driven healthcare decision making. They must, at a minimum, perform ad-hoc data analysis across all regions and cohorts, integrate clinical, financial, and administrative data in near real time, and provide on-demand reporting. Such as

  1. Data analysis in real time and in the past
  2. Normalization and semantic interoperability.
  3. Scalable and robust IT infrastructure
  4. Integrations with APIs
  5. Governance and security of data
  6. Data analytics as a service

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Population Health Management

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