healthanalytics

Analytics For Employers: A Tutorial (Part 2)

A succinct guide on how to save money on employer-sponsored healthcare

A succinct guide on how to save money on employer-sponsored healthcare

Over the past 3 years, the most common question we have heard from employers and brokers is this: health analytics is good, but what do we do with the dataWell, we are going to answer that question in this very post. That’s right, we’re sharing all the most actionable areas we look at for self-insured employers to help them to gain control over their spending. Some may say that we’re giving away our secrets, but we don’t see it that way. Our mission for employers is to make them savvy health care consumers, so making information transparent is what we do. Furthermore, it’s important to open up conversations on how organizations are using analytic data, because these conversations will help to advance insight and foresight so employers can use their data to create, track and refine a long-term strategy for the benefits they offer.

In Part 1 of this post we established that for employers, the best strategy for using health analytics moves beyond simply looking at spending to enter the realm of strategic benefit planning. This is the limitation of traditional healthcare analytics. Over the next decade, we will continue to see employers move away from watching spending go up and down and move towards looking at data in a way that provides both insight and foresight into population health. The next evolution of employer analytics informs a deeper understanding of who associates are, the benefits that will attract the best talent, and identifying the optimal strategy for funding these next-generation benefits packages.

To start, we pulled together a list of areas that any employer can explore if they want to ensure they’re using data to guide their spending decisions on health benefits. We've broken this into 3 sections: 1) Goals, 2) What's Actionable? and 3) Areas of Insight.

Beginning with the end in mind, here are the top goals that self-insured employers have when it comes to monitoring their health spending.

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Goals:

1.      To cut excess and wasteful healthcare spending and to accurately project future spending. Approximately 20% of an employer’s healthcare spending is wasted due to unnecessary and preventable costs. Open access to data helps to inform employers on exactly what areas are driving wasteful spending and how to better predict future spending.

2.      Identify strategies to support associates on their health journeys. While 5% of people drive 51% of health costs, 50% of plan members account for only 3% of health spending. Understanding how to support the unique, complex health needs of members affects a company’s bottom line in both healthcare costs and employee productivity.

3.      Track progress on the current healthcare and wellbeing strategy. An unbiased evaluation of a healthcare program is eye-opening. Not only does it guide the strategic evolution of an employer's healthcare strategy, it may reveal opportunities to recoup hefty vendor performance guarantees.

4.      Make sure members are getting the preventative medical attention they need. We consistently see that between 10%-20% of members never see a doctor. It’s within this group of people who are not driving costs today where an employer’s greatest future healthcare risks can lie.

In order to meet these goals, an organization needs to identify what exactly can be actionable. It's easy to spot the costs that stick out, but when is it too late to intervene on a cost-driver? Here are the most common areas where employers can focus to influence spending, care quality, preventative care, and effectiveness of condition management.

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What Is Actionable?

·        The plan’s pharmacy formulary (with some limitations based on the PBM partner).

·        The plan’s rules surrounding specialty medications.

·        The healthcare partners the employer selects (health plan, PBM, condition management services, smoking cessation, behavioral health services, direct primary care, centers of excellence).

·        Plan contributions, deductibles and coinsurance paid by employees for their healthcare benefit, emergency room surcharges, spousal surcharges, smoker surcharges, stop loss arrangements.

·        Cost variation among high cost and/or high volume services (MRIs, musculoskeletal surgeries, cancer care, etc).

·        Effectiveness of member education on health benefits.

·        Targeted wellbeing services offered to members.

Now that we’ve laid out the goals of using data and the areas that are actionable, here are some specific questions to answer when looking at the data.

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Areas of insight.

1.      Which conditions and medications represent the largest population health risks? How do these conditions vary by both dollars spent and number of people affected?

2.      Can amending prescription drug policies surrounding step therapy, specialty drugs, generics, place of service/purchase lead to savings for members?

3.      Does the member base have a problem with emergency room (ER) misuse and are certain locations or member categories driving ER costs?

4.      Do changes in member risk score, medication adherence and prevalent disease states such as diabetes show that your investments in condition management, smoking cessation and wellbeing interventions are working? Could performance guarantee fees be recovered from vendors?

5.      Are there trends noticeable related to members who are not engaging with physicians at all? Through looking at healthcare utilization among work location, salary bands, plan types—can we identify trends as to why certain people are not using necessary health services? These barriers to accessing care could be cost, lack of understanding of benefits, and even corporate culture, among others.

6.      What percentage of people are receiving preventative care and age-appropriate screenings among various member demographics?

7.      What are the largest cost variances that can be actionable? For example, could costs associated with procedures such as joint and hip replacement surgery or even MRIs be standardized via options that are available to your members? (Could centers of excellence be leveraged?)

8.      Could a direct primary care model have benefit for the member population?

9.      Are there actionable insights with respect to absence data and workers compensation claims?

10.  What is the size and scope (in dollars and members) of opioid use and dependency-related costs?

In the same way that reading an abstract is not the same as reading the book, please keep in mind that this is a very brief overview of a complex subject.* Every employer has unique challenges related to population health and health spending, so there's is no real "one size fits all" approach. The data drives the discussion in a unique direction for each employer.

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About BetaXAnalytics:

We combine data science with clinical, pharmacy and wellness expertise to guide employers and providers into a data deep-dive that is more comprehensive than any data platform on the market today. BetaXAnalytics uses the power of their health data "for good” to improve the cost and quality of health care. For more insights on using data to drive healthcare, pharmacy and wellbeing decisions, follow BetaXAnalytics on Twitter @betaxanalytics, Facebook @bxanalytics and LinkedIn at BetaXAnalytics.

* A Note on Data Privacy The purpose of using health analytics is to identify actionable areas to target costs and to improve effectiveness of care options on an aggregate level. This is done by looking at trends in data and under no circumstances should insights be presented to an employer in a way where data is individually identifiable. There are a number of data-related best practices that we recommend to remain adherent to privacy laws. Any employer, broker or consultant who is using health analytics should do so under strict adherence to HIPAA regulations and under the advisement of an experienced data privacy attorney.

5 Big Reasons Why Employers Should Use Health Analytics

Photo credit: iStockPhoto by Getty Images

Photo credit: iStockPhoto by Getty Images

We’re living in funny times when there’s a public outcry for open accessibility to affordable healthcare, yet employers still cover over half of the non-elderly population in the U.S.  So this leaves employers, very few of which have in-depth knowledge of how to keep people healthy, footing a large bill and assuming the health risk of their employees.  In fact, 82% of employers with over 500 employees are considered “self-insured,” meaning that they pay dollar for dollar the claims of their employees, spouses and dependents.  For most of these employers, healthcare is their second largest expense, second only to the cost of salaries. 

So this leaves any smart employer with a very reasonable expectation—they want to keep their employees healthy.  After all, they’re footing the bill for healthcare, so they have a vested interest in the health of their employees and their families.   But how do you keep people healthy?  Do you go home with them to make sure they don’t devour a package of oreos at night?  Or call them to remind people to take their blood pressure medication?  Or wake them up early to make sure they hit the gym before work?

Of course these interventions sound crazy.  People’s health habits are a product of personal choices that are decades in the making…and changing these habits is a tall task.  So employers are left to manage all sorts of 3rd parties to handle just this—to administer health services, to provide resources for health coaching, to inspire employees to be physically active, and to provide behavioral health and addiction services.  But the basic problem remains…employers are paying for these services, so how can they know they are getting what they pay for?  This is one of the reasons why health analytics is so important.

Here are the top reasons why employers need to use health analytics:

1.       To understand employee health needs.  Most employers, in addition to offering health insurance to employees, offer services to address employee health needs.  The goal of offering health services is to improve employee health and to lower health costs over time.  These services could be health coaching, health seminars, fitness challenges and weight loss programs.  And with the average employer spending $693 per employee on wellness incentives, they want to make sure they understand which services are needed most by their employees.  This helps them to spend wisely.  This moves them from the spaghetti method of health and wellness spending—throwing everything to the wall to see what “sticks,”—to a data-driven health and wellness strategy that can be justified and measured for their senior management. 

2.       To give high-risk employees the health resources they need.  What if you were able to know someone was going to have a heart attack before it happened?  The amount of data available today can be used for a very good purpose—to help to match people with proactive care before they end up in a hospital.  Let’s say you use an outside service to provide health condition management for your members.  The only way condition management can be valuable is if it is reaching the right employees.  Leveraging health analytics of your members can ensure that the right members are receiving proactive condition management outreach at the right time—before they end up in the hospital.

3.       To find wasteful spending.  Most employers today are under increased internal scrutiny to ensure that they are doing their due diligence in managing their vendors, and the total health and wellness services costs for employers significant.  Annual premiums for employer-sponsored family health coverage is $18,142, according to a 2016 employer survey from Kaiser Family Foundation.  One very common source of “waste” is the misuse of the emergency room (ER).  Understanding the magnitude of emergency room misuse and patterns in the reasons for costly ER visits helps to inform how to best communicate existing benefits to employees, communicate alternatives to the emergency room as well as to evaluate changes to ER co-pays to encourage employees to seek alternative forms of urgent care when it makes sense.

4.       To manage prescription costs.  A 2016 study by Castlight Health found that 1 out of every 3 opioid prescriptions covered by employers is abused, and that painkiller abusers cost employers nearly twice as much ($19,450) in medical expenses on average annually as non-abusers.  Rising opioid usage and skyrocketing specialty medication costs are at the top of mind for employers, but most employers get very little transparency into this information.  Examining prescription drug data helps employers to better understand medication usage, adherence and addiction among their members.  This provides valuable information that is crucial to help them to save money in the future, make needed changes to their pharmacy plans and to provide appropriate behavioral health and addiction resources to members.

5.       To manage health service vendors.  It is becoming more common for wellness service contracts to include performance guarantees, meaning your company could be getting money back, sometimes up to 30% in returned fees, if employee health is not improving as promised.  If your company has performance guarantees in your vendor contracts, you’ll want the ability to have your own source of truth on whether those guarantees are being met.  Have you ever had a question that was met with 3 different answers from 3 different vendors?  This is comparable to doing your taxes – you may take your tax documents to 3 different accountants and come up with 3 different numbers on your return. Every vendor is looking at data through a different lens, and some lenses are more accurate than others.  It’s ironic that employers foot the bill for employee health, yet they rarely have the ability to have their own data arsenal to inform their decisions and audit vendors.  Analytics helps employers to become more savvy “consumers” of health services. 

Bottom line – when you are spending a lot of money on something, you deserve to know if that money is being well-spent and you deserve to know how you might be able to save money in the future.  This is the value to employers of making data-driven decisions on their healthcare spending.  And if you have the opportunity to receive this data from an impartial 3rd party whose contract is not “on the line” based on the data they provide (i.e. not the health plan, not the wellness service provider), an employer is in a prime position to best manage these services.

 

About BetaXAnalytics:

BetaXAnalytics uses “data for good” to improve the cost and quality of health care for employers.  By combining PhD-level expertise with the latest technology, they help employers to become savvy health consumers, saving health dollars and better targeting health interventions to keep employees well.

Follow BetaXAnalytics on Twitter @betaxanalytics, Facebook @bxanalytics and LinkedIn at BetaXAnalytics.