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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?
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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. Understand 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’ the back-up plan?
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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.
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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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Enlight

Enlight is a flexible analytic platform that unlocks the power of data. It brings data to life and reveals
connections and insights so you can make being healthy more affordable, convenient, engaging, and equitable.

Read more.

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How to measure your wellness program’s ROI

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


While many employers are willing to invest in wellness programs, they aren’t always clear on the goals for these benefits.

Rather than jumping on the wellness bandwagon or adding a program just to expand the suite of benefits, employers would be better served to evaluate and make decisions based on data.

Read how HDMS recommends employers approach this.

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Keep Essential Workers Safe: Data Analytics Strategies to Guide Effective Benefits Design

Published in HR Executive
Authored by Rani Aravamudhan, Senior Clinical Consultant, HDMS


HR executives have followed the time-tested adage of past behavior being the best predictor of future behavior – evaluating utilization patterns over time to make educated projections for the upcoming year. However, given the skewed healthcare consumption caused by COVID-19, these traditional means of assessing year over year trends fall predictably short.

Read the five strategies suggested to guide effective benefit design.

Download PDF reprint

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Diversity, Equity, and Inclusion. Start with understanding where you really are...

Use Analytics to dig into specific parts of your population and better understand unique health concerns, emerging needs, and guide decisions for a more thoughtful benefits strategy.

HDMS clients have access to Transgender Health dashboards.
Look at some of the insights that clients may find.

Click here for just one example…


HDMS clients – have your team walk you through your dashboards. Where can you take this next? We’ll help tailor and expand this for you!

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How Data is Driving 2021 Benefits Strategies

Published in Fierce Healthcare
Authored by Rani Aravamudhan, Senior Clinical Consultant, HDMS


Health plans typically design benefit offerings by assessing patterns of utilization and cost data in previous years. Thanks to disruptor-in-chief, COVID-19, this traditional approach was rendered inadequate to say the least.

With the pandemic demanding agility, many health plans turned to flexible data analytics and infrastructures capable of generating original, actionable intelligence at a moment’s notice. Having the ability to respond rapidly to their clients’ immediate data needs, despite ongoing uncertainties, is much like having a fire truck ready to put out fires whenever and wherever they arise.

Health plans needed to quickly pivot business processes to align with evolving customer needs. For healthcare benefits administrator Meritain Health, the large-scale shift in the consumption of care that followed the onset of the pandemic required swift adjustments to accommodate changes in multiple areas: fluctuating sites of service and code sets and payment structures, to name a few. Hence Meritain implemented several strategic variations to their business processes.

Read more.

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Integrated Mental Health Strategies: A Right-Sized Approach to 2021

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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Five essential strategies for healthy essential employees

This year, you’ve adjusted the physical working environments in your offices, manufacturing plants, and retail floors. You’ve adopted the state, local, and CDC guidance with your own new policies for COVID-19. You’re even offering free flu shots on-site for your employees.

Wondering what else you can do to support your essential workers? By analyzing a few key metrics, you can make decisions that support employee health and productivity—now, and into the future.

Get the guide.

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Countering COVID-19: Using phased data analytics to shape benefits plans

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Five Tips on how to Optimize your Cost Model during COVID-19

The COVID-19 Cost Model built by HDMS is used and adapted to meet our client’s needs and interests. We invite you to download this model and use as-is – or customize it to suit your specific needs. Here are a few tips to get the most out of your COVID-19 cost model:

Use a cross-functional approach: Obtain representation and contribution from across the organization, with inputs from Finance, Data, and Clinical/ Healthcare Specialist resources, at a minimum. Clinical/Healthcare Specialists ensure your model is answering key questions, contains accurate assumptions, and reflects current thinking. Your data team, working in collaboration will create efficiencies in balancing what you want to know and what data is available to support this investigation. They can help build for a refreshable model and possibly introduce new ideas to the team based on data possibilities. The finance team will guide calculation accuracy and are usually great partners to help with organizational buy-in and create confidence in the model.

Build for ranges: Create a model framework that invites ranges both as inputs and outputs. The template provided contains both range estimates and is constructed for three case scenarios to help accommodate different organizational approaches. This increases the usability of the model, as ranges communicate a realistic spectrum. By understanding how large the range can be, you innately create context for anyone using the model outputs.

Create in parallel: Again, collaboration is key. Let data analysis help inform increasing specificity for your cost model. As you develop your model, assess the data available to support increased granularity and actionability. Bring in member demographics like age, gender, geography and use historical health insights along with HR data to consider health risks, role type and job type considerations. Health plans might also wish to analyze by industry, geography, plan type, or other business attributes for additional aggregated insights.

Build assumptions as variables: What we know is rapidly changing and evolving. By building assumptions in as variables, rather than use within formulas, you can update your assumptions more easily and completely. Showing the values as variables on the model itself also creates transparency so it is clear what is used in calculations.

Make the model self-documenting: Document within the model itself. Cite and link to sources, show assumptions as variables as shared above, and create a high level of transparency to help answer as many questions as possible. Make it easy to check sources to see if recommendations or assumptions merit updating based on evolving information.

Download the HDMS COVID-19 Cost Model to see and play with a working model. If you are an HDMS client, reach out to your customer experience team for a more detailed and customizable model that works cohesively with your HDMS implementation.