Getting people like Takki to the right care is critical.
But how do you find people who most need care when they don’t go to the doctors?
Predictive analytics help us spot Takki.
Takki has a heart condition. Her health history shows a number of ER visits, diagnoses without follow ups, and no PCP utilization. We can’t always see health risks walking around the office or warehouse. Takki looks like lots of other hard working 27-year-olds. She’s always helping her family and enjoys time with friends. But family and friends need her complicated condition managed so she will be there for them in years to come.
Predictive analytics – not your major in college? Know the basics to contribute meaningfully in meetings.
Watch this 20-minute video for executives and be confident. You’ll understand the basics of how these technologies work. Now you can have a point of view on where and how your organization can make investments in this emerging hot spot.
Predict: Use the data you have, differently. Use data about the past to look ahead, with predictive analytics. Send population health data through predictive models to anticipate what is likely to happen. See statistical results specific to your population. And even more amazingly – imprint actionable member-level predictions when running HDMS predictive models.
How? In addition to understanding the big picture, initiate care actions towards members who meet each segment criteria.
Disrupt: Put your predictive efforts in places where you can make a difference. Once you have data-driven predictions, what can you do to move in the direction you want? Who is likely to have an emergency room visit? Who is likely to become an inpatient admission? Once you know this, what can you do to avoid these circumstances? How can you engage a member before the prediction becomes a past event?
Marry data-driven predictions with proactive actions. You’ll drive more positive outcomes, reduce unnecessary costs, or improve the affordability and convenience of health care. Find the rising risk in your population and take action to embrace people to encourage a path to better health.
Approach predictive analytics as part of a cohesive analytic strategy
Artificial intelligence and predictive analytics are cool, but they need you. You are the critical resource that can help your organization invest energy and effort around predictive analytics in the right places.
Great! Um, where’s that?
It helps to think big picture. Approach predictive analytics as an extension of a holistic strategy and cohesive platform.
Where can you make a difference? What resources, recommendations, offers or alternatives can you offer a person? How can you improve the predicted state (if the prediction is negative) or increase the likelihood (if the prediction is positive)? Think about what your organization can immediately take action on.
- Use your historical and trend analytics to orient and quantify where you have improvement opportunities. Uncover drivers and root causes, and determine if you can impact change effectively.
- Build leading indicators to provide a near term view of how market trends are manifesting within your specific population, in places where you plan to implement predictive models.
- Measure and monitor the effectiveness of disruptive actions that aim to positively influence predicted outcomes.
- Evolve predictive models so predictions are trustworthy and reflective of the rapidly changing face of health care.
Predictive Analytics Resources
Predict and Disrupt (60 minute webinar) | Watch
What every Executive should know about predictive analytics | Watch
Key ingredients to build or buy predictive models | Coming soon
A Cohesive Strategy for Predictive Analytics – Example with Mental Health | Watch
3 Use Cases for Predictive Analytics (and ideas for intervention strategies) | Check it out