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Predictive Analytics: Drive Affordability and Better Health

Predictive models are an amazingly powerful use of data. And we have so many new reasons to use these advanced approaches to offset rising costs of care and challenging health conditions: deferred care, the increased need for mental health care, and virtual care adoption are disrupting historical patterns. How do predictive models work? Where is it best to consider using predictive analytics? What should you be doing with the results?

Watch this webinar to learn about how predictive analytics can fit into an overall analytic strategy. Invest in capabilities that allow you to act upon results, instead of sitting in reports in your inbox. Predictive analytics, when put to purpose, can be an instrumental part of a broader strategy to drive down costs and improve health. Make sure you have the big picture so you get the most from these investments.

We’ll share:

  • A framework to use to help discern where and how predictive capabilities are highly useful
  • Insights into how you can couple predictive capabilities and leading indicators
  • Approaches other health insurance providers are taking to act upon what their data is telling them

Webinar hosted by AHIP.


Rani Aravamudhan, MBBS
Senior Clinical Consultant
Health Data & Management Solutions (HDMS)

Rani Aravamudhan joined HDMS as a Senior Clinical Consultant. She is a physician, specializing in General Medicine with extensive experience in the EMR/EHR and population-health industries with a focus on clinical transformation, workflow design and development, value-based care, risk management and clinical quality and performance reporting. Her strong background in clinical medicine and experience in the HIT industry make her successful in navigating payer, provider, and technology vendor landscapes.

Prior to joining HDMS, Rani worked for Philips Wellcentive as a Services Leader, where she led teams of program managers, clinical specialists and training staff along with heading their Data Governance committee. Before that, Rani was leading EMR/EHR implementations, workflow and process optimization consulting at McKesson Corporation and was their resident subject matter expert for all CMS quality reporting programs. Rani earned her medical degree at Grant Medical College in Mumbai University, India.

Keith Wilton
Vice President of Product Management
Health Data & Management Solutions (HDMS)

Keith Wilton is the Vice President of Product Management, with more than 15 years’ experience in Product Management and an emphasis on creating and deploying complex software applications. Keith joined HDMS in March 2016 after serving as Vice President of Product Management at Backstop Solutions, a leading player in the Alternative Investment space. Prior to Backstop, Keith ran product management for an arm of Morgan Stanley, and for other organizations. Keith received his B.S. degree from the University of Illinois Urbana-Champaign.


Powerful predictive analytics, easy to implement and use.

Learn more about the power of HDMS Predictive Capabilities.

HDMS provides predicitive models, pre-defined segments, model scores, historical predictions and more. Bring member-level scores and cohorts into a cross-prediction analytic view.

There’s power and sophistication wrapped up in an intuitive user experience – so you can do more than look back on historical trends.

Use data to look ahead. Then take action.

HDMS clients – have your team walk you through the latest models. What do you do next? We’ll make sure your data supports your next steps and actions.


Predictive Analytics: Harnessing the Power of Data

Predictive models are an amazingly powerful use of data. They can inform benefit design and help deliver personalized, meaningful user experiences.

In this presentation, attendees will gain insight into predictive analytics and learn how to leverage health data sets, such as clinical, wellbeing, and social determinants of health information to transform their employee’s health journey, identify cost savings opportunities, and assess year-over-year population-based outcomes.

In addition, the speakers will examine the use of these advanced approach analytics to navigate vaccine prioritization, deferred care risks and virtual care adoption. Although trend disruptions of 2020 have forced many to tune and adapt their current models, there are many opportunities to use existing data to create leading indicators employers can use now to set the stage for long-term change and growth with short-term benefits along the way.


What every Executive should know about predictive analytics

This 20 minute tutorial is great for HR executives and Health Plan product managers who want to have more informed discussions about how and where predictive analytics can complement efforts at their organization.


Predictive Analytics – Do more with data. Use it to look ahead

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.

Read about Predictive Capabilities from HDMS


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. 

Holistic Strategy

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.

Cohesive platform
  • 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.

Watch this 10 minute video

See an example of how predictive analytics layer into trends in mental health.

Predictive Analytics Resources

Predict and Disrupt (60 minute webinar) | Watch

What every Executive should know about predictive analytics | Watch

HDMS Enlight Predictive Capabilities | Download

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