Digital health transformation has fundamentally altered the way organizations use data to unify disparate medical functions and deliver optimal outcomes for individual patients and the health enterprise.
For an organization to achieve this goal, each interconnected component of its healthcare ecosystem (governance and workforce, interoperability, predictive analytics, and person-enabled health) must align with and enable every other component.
Ensuring that each component achieves its potential requires that outcomes for each are measured in a standardized, repeatable way. In the third of a four-part series, we look at measures of effectiveness for predictive analytics.
By using data to extrapolate outcomes, predictive analytics equips healthcare organizations with knowledge and real-world insights that can help make informed decisions about individuals, health teams and health system leaders.
It also leverages health system data, digital tools and population data to inform care delivery and operations—creating personalized healthcare, risk prediction to optimize outcomes and the proactive tracking of population health to support health and wellness.
This advanced form of analytics is measured within the following parameters:
Predictive analytics represent the point at which data management progresses from reporting on past and current conditions to assessing future outcomes, forecasting their probability and identifying factors that could change them. Documentation is important in any clinical or business setting to maintain health standards and learn from past events, but the real power of digital health transformation lies in its ability to shape next steps that will optimize the health of the individual, the population and the organization that serves them.
When an organization sets out to forecast the future with a high level of accuracy, standards for measurement are essential. Consistent precision behind analytics helps ensure consistent accuracy of the events they predict.
Along with the other three components of the ecosystem, this information provides healthcare organizations a framework to judge how effective they have been in achieving frictionless, system-wide support for the needs of the people in their care.
The next post in our series on measuring digital health transformation will explore person-enabled health.
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