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One more field can make a difference: Diversity, Equity, and Inclusion.

We’re used to looking at a lot of healthcare metrics – utilization, costs, outcomes.  Even just a little more data can tell us a lot more about what’s really happening.

 

Check out how a few Plan Sponsors were able to surface measurable differences within their populations, by adding just a little more data into their analytics.

 

Measuring these differences allows us to take what we anecdotally see or suspect, and support it with facts.

Collegaues focused on Diversity, Equity, and Inclusion (DEI) agendas are wonderful partners. Share these insights with them.  The numbers give your organization a brilliant set of facts to help drive decisions aligned to company goals.

We’d love to help you surface these insights at your organization.  Just ask and we can share more about the possibilities.

 


 

Join the movement.  We’ll help you get started on measuring how healthcare needs and patterns change across different subpopulations at your organization.


 

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Prepare for your health analytics implementation before you buy a thing!

Avoid buyer’s remorse.

Did you ever have a home improvement project that finished late and cost more than you expected? How about a technology implementation that finished late and cost more?

You are more likely to be on-time and on-budget if your plan is thoughtful and reflects your reality. Don’t you want to have confidence knowing what you’re really getting into?

So, here are three tips to set you up for implementation success when it comes to health analytics:

  1. One-size does not fit all. It’s unlikely your implementation is the same as other organizations.  Why?  Because the culture of your organization is a huge factor.  Dig in.  What are the details behind YOUR implementation plan?

Tip!



Discuss what will be problematic or painful based on your experience and what you are moving away from. Are those complexities appropriately addressed, cared for, or resourced? Think about metric definitions and consensus, data quality, data reconciliation, matching and integration across sources, and slowly changing history.
  1. Identify what is- and is-not in your control. If something is beyond your direct control, is there a named resource and escalation path?  What risk does that pose to the project timeline based its nature.  For instance, your health analytics implementation is reliant on data from others.  How are your relationships and service level agreements with those partners and vendors?  How does that affect your plan and what’s the back-up plan?
Tip!

Before your implementation starts, refresh your knowledge of the day-to-day contacts, authorities, and any contractual SLA’s you have in place. If there will be costs associated with establishing new feeds or data interfaces, identify those early.
  1. Top down, bottom up, or an interesting mix? Think about the approach that will work better for your organization.  What process works for you – here’s my data – what can I do with it?  Or here are my objectives – what data do I need?  There are pros and cons to each but thinking about this as you prioritize is invaluable for setting internal expectations and getting the right resources lined up.
Tip!

Use phase 1 for quick wins. Standard sources generally seamlessly populate the most common views. Users feel like they get a lot out of the gate and that helps tremendously with adoption.

Remember, you’re better off with an implementation plan that’s realistic rather than one that sounds like a dream but doesn’t work well for you in the end.

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Beyond Transparency in Coverage - Embrace plan sponsors with strategic analytics

What makes you trust someone?

Maybe they act upon facts and share these openly with you?
Even when it’s not great news?

While everyone works to meet Transparency in Coverage regulations, we see the chance for you to leap ahead. Anticipate where the market is going and offer more than traditional plan sponsor reporting – bring your plan sponsors business transparency, strategic plan performance transparency. You’ll earn their trust; you’ll be rewarded with retention.

With major industry changes, new care options, and changes in care needs, people have lots of new questions. Be the health plan that easily gives plan sponsors answers, even to hard questions.

Employers benefit because health benefit satsifaction is a contributing factor to employee retention. With the right analytics, it can be easy to find opportunities to improve, maybe by introducing additional plan options. Yes, that’s right. Design analytics that introduce the potential value of your buy-ups. With better plan performance everyone wins as health care costs lower overall.

In an industry built upon trust,

Embrace it, lead with trust


Increase plan sponsor trust with an analytic strategy that delivers better plan transparency, too.

You’ll deepen relationships, earn loyalty, and retain your customers.


Powerful plan sponsor analytics. Go beyond reporting.

What could controlled plan sponsor plan performance transparency look like?

Self-service analytic front-ends are what people want, to explore data. But the secret is the data itself. If you want to focus on using data for plan performance improvements, your analytic views will naturally be very specific to your business.

Take a peek at HDMS Enlight™. Imagine plan sponsors with access to data and analytics you choose or design. See teams working side by side with accounts, helping them to optimize and get the most out of your thoughtfully designed plans and networks.

Customers will love you for it.

Trust us.

(yet verify – it’s ok, we would too.)

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Social Determinants of Health – Analytics

How are organizations approaching SDoH in their analytics? What are they doing given the insights and measurements they find?

Here’s some specific examples of work going on within HDMS clients. You can use these projects to understand the analytic possibilities available with our SDoH capabilities. And even more importantly, see how organizations are taking action upon insights and driving innovation.

Click here to see some examples


Score big for communities

HDMS clients – have your team walk you through available possibilities. There’s so many new options. Where will you take this next?

We’ll help tailor new analytic views to any specific needs you have.



Read more about SDoH here

Seven SDoH Indices, ready for you.

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Integrated Mental Health Strategies: A Right-Sized Approach

Published in HealthPayerIntelligence
Authored by Rani Aravamudhan, Senior Clinical Consultant, HDMS


Member programs encouraging mental health Data Analytics for Mental Healthand wellness have increased in popularity lately among health plans and sponsors. There is a growing consensus that a happy, healthy workforce can lead to better business results. Consequently, promoting mental health strategies is considered a “win-win” proposition.

The question is, how do we quantify the wins?

Read how.

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Improving Plan Performance by Measuring Diversity, Equity, and Inclusion.

Numbers talk. They are a powerful language in business.

 

These numbers let us think differently and specifically – design strategies and plans that improve health engagement and drive down costs.

With digital transformation improving health experiences, we now have even more Big Data in healthcare to use for deeper insights in population health.

When it comes to health analytics and DEI efforts, what data do you need? How do you get it? How can you get started? What happens next?

 

We’re so glad you asked – hear from our experts.

 

 

Watch this webinar to learn about ways you can actively measure health outcomes, costs, and utilization through the lens of diversity equity, and inclusion.  Most importantly, then what?  Come listen to what some plan sponsor companies are doing and dig into the perspectives of a health plan…

 

Download the slides

Webinar hosted by AHIP.

 

 

 

The Speakers

Rani Aravamudhan

Rani Aravamudhan, MBBS

Head of Clinical Advisory Services
Health Data & Management Solutions (HDMS)

Dr. Rani Aravamudhan leads HDMS Clinical Advisory services. She is a general medicine physician who cares for individuals yet connects experiences to population health perspectives using her deep data expertise. Rani is known for her work in data-driven transformation, workflow design and development, value-based care, risk management and clinical quality and performance reporting.   Her work and team guides clients to understand what is possible with data, find answers and insights within projects and analyses, and gather context and scale across the HDMS client base.

Jason Elliott

Vice President of Employer Customer Experiences
Health Data & Management Solutions (HDMS)

Jason Elliott is Vice President of Customer Experience for Employer clients at HDMS.  A true public health enthusiast with a Masters in Epidemiology, he spent over a decade delivering dedicated clinical analytics and leadership at BCBS.  Since then, Jason has managed the managed the Employer practice area.  He brings very structured thinking into the types of problems his clients are trying to solve, and what can be done with the insights discovered.

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Use Cases for Predictive Analytics in Healthcare

Predict, then act!

Companies are using predictive analytics to get the right people to the care they need.

Think about it - predictions aren't truely valueable unless we act upon them to either avoid a negative prediction, or accelerate a positive prediction.

Read these 3 use case examples to help inspire new ideas about how your organization can be using predictive analytics.

 

What could you do differently to help members be on a path to better health?

 

Download use cases and ideas for intervention strategies

Want help finding rising risks?

Use Predictive Analytics to look ahead