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Intelligent Population Health: Better Insights for Better Results

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March 1, 2018

Highlights on this story:
  • Four new developments in analytics solutions strengthen the tools available to support providers in effectively managing the health of their patients.
  • The development of visualization tools empowers healthcare organizations to use business and clinical intelligence in more consumable and compelling ways.

As healthcare organizations take on more accountability through value-based contracting, they are making business and clinical intelligence solutions an integral part of their population health strategy.

These solutions have significantly advanced in recent years and healthcare organizations are using them to better inform decisions and drive actions for success in managing patient populations.

Four new developments in analytics solutions strengthen the tools available to support providers in effectively managing the health of their patients.

Advancements in Predictive Analytics

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The evolution of algorithms and models that analyze healthcare indicators and system-specific patterns enables organizations to more precisely identify at-risk and rising-risk patients within their population. This helps organizations optimize care interventions with patients that have been identified with the potential to encounter elevated healthcare needs.

Inclusion of Social Determinants of Health

SDOH conditions account for 40 to 50 percent of overall patient health and include education, job status, social support, income and community safety. Patients that are negatively afflicted in these areas are less likely to have the ability to cope when physical health issues arise. Therefore, having insight into the SDOH factors impacting a patient population can help healthcare organizations better identify patients at-risk and assist in dealing with these issues that, if not addressed, can have an extraordinary impact on cost, quality and adherence to the plan of care.

Integration of Artificial Intelligence and Deep Learning

Integrating AI enables solutions to “learn” over time without human intervention, continually improving the algorithms and predictions of the solution specific to the actual experience of a healthcare organization. These tools provide deep insight and real-time, actionable recommendations based on the actual experience and behaviors of a specific population. Healthcare organizations can use this insight to identify issues that typically may not be detected, otherwise, and initiate programs to drive improvement across their patient populations.

Empowerment through Visualization

The development of visualization tools empowers healthcare organizations to use business and clinical intelligence in more consumable and compelling ways. The integration of natural language querying allows a user to search for specific data points and then present this data through dashboards, charts and graphs. Viewing data in this manner makes it easier to identify issues, build consensus, make informed decisions and take appropriate actions to improve patient outcomes.

These advancements in business and clinical intelligence solutions offer great promise by giving organizations the ability to predict, analyze and visualize population and patient-specific data in real-time, arming them with better insights to drive better results.

It is very important to remember that simply having insight and analytics about the health of a population is only half of the solution analytics solutions must integrate with a care management system whereby patients can be seamlessly transitioned for evaluation, care planning and intervention.

Date: Feb 16, 2018

Source: HealthcareITNews

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