June 25, 2018

Why data matters to today’s employers: A Q&A with Healthgram’s data expert

We're sitting down with Healthgram's data expert for a Q&A session on why big data matters to HR professionals. Join us to learn more.

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A recent study showed that 97% of employers want more healthcare data. But what does that really mean? And how many actually have a plan for what to do with that data they find?

We sat down with Healthgram team member Cindy Rutherford for answers to our questions about data. She’s an expert in translating numbers into savings, and helps us get to the bottom of what employers should know about healthcare data and most importantly, what they should do with it.

Let’s start with the basics:

 

Can you help us understand what healthcare data is?

Healthcare data refers to the information about a population that helps employers make decisions about their health plans and benefits offerings. It can include anything from findings that quantify the prevalence and severity of health conditions to utilization of the healthcare system.

Although data is collected at the individual level, it’s helpful to look at the big picture. Basically, the trends beyond a member’s isolated events that show correlations for the population as a whole. It helps employers become proactive in identifying and addressing risk instead of being reactive.

 

Why should employers care about this data?

It’s important to say that data isn’t just about number crunching. We never want to simply say “okay, let’s just give people data.” The end goal is to help the employee, not to have more numbers to look through in a meeting. For example, if your data shows a high prevalence of unmanaged diabetes, it does no good unless you’re ready to act on the opportunity to influence change.

It’s here where the individual level data (claims and pharmacy data showing diagnoses and medication non-compliance) can work with the population-level data (a trend of unmanaged diabetes) to become actionable. The only way to change data on a population level is to change it on the individual level, so a good example of an actionable solution would be implementing a one-on-one diabetes management program for those members identified.

There are countless population health management or employee wellness programs that can be created to address a company’s specific need. But without implementing a solution, all you have is proof of the problem.

 

Can you give us some examples of some data points employers should be paying attention to?

The most valuable data typically lies in identifying costly chronic conditions and healthcare utilization. Examples of data points that may indicate intervention is needed for members with chronic conditions:

  • Medication adherence
  • Biometric lab values
    • Can not only help identify who is diagnosed with a condition, but also subsets who have borderline labs or don’t know they have a condition
  • Claims indicating presence of a disease

The frequency and types of healthcare utilization by members is also telling. Data points that can help identify misuse or underutilization:

  • Emergency utilization for non-life threatening care
  • Use of providers or facilities who overcharge for procedures
  • Employees without a primary care physician
  • Non-compliance with recommended preventive screenings

 

How should this data be collected?

Many employers are already well-versed in data collection methods, and perhaps even have them implemented. We like to recommend online health risk assessments, biometric screenings, on-site clinic encounter information and real-time claims and pharmacy analyses.

Unfortunately, integration of this data can be an issue. We’ve seen this gap with companies we start working with; they may have claims data and pharmacy data, but no way to tie the biometric data with it, and that’s the key piece.

If you’re trying to draw conclusions, which is the whole purpose of analyzing data, you can’t do that without all of the information in one place. It can’t be piecemeal. Without it, you risk making the wrong conclusion, be scared to make one at all, or go down an avenue that doesn’t address the real cause of the issue.

 

What should employers do with data once they have it?

In order to turn integrated data into action, a process must be in place to continuously audit data and come up with a plan to address trends.

Data should highlight opportunities for a health coaching or intervention initiative. Examples of programs we’ve seen implemented with successful outcomes include plan design changes that encourage proper healthcare utilization, concierge advocacy services for employees, on-site or near-site clinics, pharmacy programs and condition-specific outreach. The possibilities are endless and the more data you are able to collect, the bigger impact you can have.

But having something actionable is just the beginning. Data doesn’t do any good when it’s only available once per year. The more real-time information you can put in front of those providing the outreach, the more they are able to influence the whole person and ensure all the different pieces of a person’s health and wellness get advanced in the right direction. This can be anything from helping them make more informed decisions about healthcare utilization or stay compliant with their employer’s wellness program requirements.

Another important reason why data should be dynamic and available in real-time is so that you can see progress and make changes to your programs.

 

What about employee privacy?

Employee privacy should always be considered and all security protocols should constantly be in place. Data at the individual level should only be available to those providing outreach to employees. Aggregate reporting should be stripped of all identifiers in order to protect employees. Trust is an important factor when implementing a program that relies on individual health data, so employers should be wary of reports that give too much detail.