data

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.

Forget Flashy Technology: Here Are 3 Data and Analytics Best Practices Any Company Can Use Right Now

Image credit: iStockPhoto, Ryan J. Lane

Image credit: iStockPhoto, Ryan J. Lane

The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades.
— Dr. Hal R. Varian, Chief Economist at Google

Practically everyone is talking about using data and analytics to succeed today in business, but surprisingly companies are only deriving a fraction of the value that’s available to them in their data when they’re making decisions. The reasons for this vary across organizations, but often times it comes down to budget constraints, talent constraints, or lack of recognition from leadership that analytics will help their business to run better. During an interview in 2009, Google’s Chief Economist Dr. Hal R.Varian predicted, "The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill in the next decades." 

Let’s take a look at some of the highest-performing companies out there today.  Over the past 5 years, there have been 13 companies that have managed to outperform the S&P 500 each year.  And when you take a look at this elite group—which includes companies such as Facebook, Amazon, and Google—you find that the majority of these businesses are algorithmically-driven.  These companies take in data constantly, and use this data in real time to update the user-experience.  In their 2012 feature on big data, Andrew McAfee and Erik Brynjolfsson shared findings from their research that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.”  It is hard to deny that success in our respective businesses is not a function of how well we make use of the data available to us. 

So how does Human Resources (HR) fit in to this picture?  HR may not be the first group that you think of when considering who should have a strategy around using data.  However, HR has the weighty responsibility of managing the top expenses of a company—salaries, healthcare, and benefits.  The 2018 Milliman Medical Index estimates that the cost of healthcare for a family of 4 this year will be upwards of $28,166. Yet approximately 20% of employer-sponsored health care spending is wasted each year due to unnecessary or preventable costs across the continuum of care.  The rise of high deductible health plans mean that decisions made within HR on health plans and benefits are decisions that weigh heavily on their employees pocketbooks as well.   When we look at HR through the expense-management lens, we see that HR carries the company’s fiduciary responsibility to manage these expenses not just for the bottom line of the employer, but also for the sake of their employees’ wallets.

We often see companies who make the decision to start using data and analytics immediately start shopping for a tool to make use of their data.  While this step may be right for some companies, there are a few foundational analytics best-practices that we recommend companies have in place before making any analytic technology investments.

1.       Understand the quality of your data.  One of the biggest mistakes we see companies make is that they assume that just because a report comes from I.T. or from a vendor, that the data is correct.  However, very rarely is the data captured by a company in “ready-to-use” form.  IBM estimates that poor data quality cost American companies $3.1 trillion  in 2016 alone.  A recent study of 75 executives who assessed their own organizations data quality found that only 3% of their companies’ data met basic quality standards.  Furthermore, understanding data quality is a fundamental issue within organizations, executives are more informed to understand how data quality affects their vendor partners as well.  Every bit of data that we review is a piece of a much larger picture, and understanding the limitations of the quality of your company’s data helps to make a more accurate assessment of its insights.

2.       Develop your data strategy.  Take a step back from day to day operations to decide how to data can help to inform your decisions.  This affects what metrics you’re looking at, and how often you’re receiving it.  Many companies are surprised to find that the process of developing a data strategy often means reducing the amount of reports people are looking at.  A common assumption is that the more data we’re looking at, the better off we are.  In reality, when decision-makers are inundated with extraneous reports, they may miss valuable messages that they need to see.  What goals is your division working towards?  Which pieces of data most closely track progress to these goals?  The best way to guide a strategic process for looking at data aligns your business goals with a limited number of key metrics to indicate when changes are needed to reset course. 

3.       Identify a data “expert” on your team.  Given the issues that exist in every organization with data quality, it is valuable to identify someone who is intimately aware of the source and limitations of the data your company assesses.  This person can answer questions on why particular data might be wrong, if duplicate records are skewing the data, or how outliers are affecting results.  Your data expert can help to tell the story of your organization’s data to better frame what actions are needed to meet your operating goals.

Using data to make better business decisions does not need to be cost-prohibitive for your company.  Before investing in any data and analytics tools, implementing these foundational best practices lays the groundwork for a sound approach to using data.  They can be used by any company, regardless of size or budget.  And the best part is, you can start to use these best practices today.

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Bob Selle has led culture change and organizational design for America’s most recognized retailers.  He is currently the Chief Human Resource Officer for the northeast's premier close-out store Ocean State Job Lot, leading a transformation that has named them a Forbes Best Midsize Employer two years in a row.

Shannon Shallcross is a data expert who believes that data interpretation holds the key to solving healthcare’s toughest challenges. As the co-founder and CEO of BetaXAnalytics, her company uses the power of data “for good” to improve the cost, transparency and quality of healthcare for employers.

See Bob and Shannon at the Strategic HR Mt. Washington Conference on October 29th, 2018 during their plenary session, Metrics That Matter: Let Numbers Tell a Story.

How To Make Data-Driven Decisions When You Don't Have Data

Image Credit: Pixabay; _Marion

Image Credit: Pixabay; _Marion

In 1934, T.S. Eliot famously lamented the empty soul of modern work life. Though he wrote “Choruses from the Rock” over 80 years ago, he hits a nerve in our present-day struggles by asking, "Where is the wisdom we have lost in knowledge? Where is the knowledge we lost in information?" In current times, we have so much data at our fingertips, but does that mean we are making better decisions? Today, the core of data analytics is simply using information to make well-informed decisions. The only difference today from 80 years ago is that we simply have more information available to make decisions and more sophisticated methods to use this information. 

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A question that I get time and time again from managers is “How do I make data-driven decisions when I don’t have any data?” As a decision maker, it’s incredibly frustrating to feel hampered by a lack of data.  Despite wide availability of information, companies might not put data into the hands of decision makers for a couple reasons. Maybe the organization does not have an effective way of capturing data—this happens in companies that have older technology in key areas of the business. Or maybe the data they have is too messy—for instance, perhaps they can track customer quotes online, but they have no way of cleaning up the 30 different customer quotes that actually were generated by the same person. In other cases, data is kept sectioned off in certain parts of a company, but it is not shared widely with people whose decisions depend on the information. For whatever the reason that managers feel like they do not have access to information to make an informed decisions, there are a few guidelines you can follow to ensure that you are making the right decisions.

The key is not to get more data – it’s to get the right data.

It’s important to keep in mind you can have all the data in the world and still not have the information you need. The key is not to get more data – it’s to get the right data. In research from the book Stop Spending, Start Managingexecutives reported wasting an average of $7,731 per day—or $2.8 million per year—on wasteful “analytics.” The first step to making sound decisions is to recognize what that “right” data is for your business. Once you identify this, you can cut your time looking at reports significantly because now you have a strategy. You know exactly what you need to see to make a decision, and you can see through the noise of mountains of data that don’t add value to your decisions. 

Executives reported wasting an average of $7,731 per day—or $2.8 million per year—on wasteful “analytics.”

If you don’t have access to the data you need at work, here are some steps you can take:

1.      Identify your business goals.  Here’s your opportunity to start at square one and holistically rethink how your decisions are made. This entails taking a 50,000 foot view of your business to make sure that you’re asking the right questions. We often get in the habit of process, and we repeat process patterns of looking at old reports that don’t tell us what we really need to know. If your business unit always looked at a set group of metrics, it’s easy to get tunnel vision and to see it as a bad decision to stop looking at a certain report. But I recommend taking a step back to ensure you’re asking the following questions before even looking at any data:

·        What are the business objectives for which we are responsible? (In other words, what are our goals?)

·        What are the crucial areas of the business that we need to be tracking?

2.      Identify which data you need to track progress on your goals. What data do you need to see to be able to track progress on these goals and to make sound decisions? In most cases, every business goal you cite has one or multiple metrics that will help you to gauge progress against that goal.

3.      Examine your data access. Identify which of these must-have pieces of data you have access to. For the data you don’t currently have access to, identify how you can get access. This can be as easy as requesting access from another department, or as hard as implementing a way to capture new data.

4.      If needed in the short term, identify proxy data for the information to which you don’t have access. When you can’t access crucial data, is there a proxy measure that would tell you the same thing? For instance, if you have no way today of tracking the number of customers who are calling with a particular complaint, can you poll your front line customer service representatives to identify trends in complaint themes? Finding a short-term proxy for needed data will provide you with some useful information. The proxy is not a perfect solution, but in the short term it’s better than using no information at all.

5.      Start the process of gaining access to the data that you need. As simple as this sounds, if you’re in a situation where you don’t have access to crucial data, the goal is to exit this reality as soon as possible. Whether this means insourcing or outsourcing to gain access to data you need, there’s simply no business case for continuing to manage without the right information.

The guiding principle of how to manage your data is to identify what data aligns with your goals—if you don’t have access to this data today, the best place to be is somewhere on the track to gaining access to this data. Identifying proxy data is a bridge to dealing with an undesirable situation, and moving towards one that puts you on the right path. But it is important to not accept a lack of data within your company simply because it’s “the way it’s always been done.” If you find yourself clamoring for meaningful metrics, creating a process to get this data involves some work--but there are huge rewards for your business in the end.

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BetaXAnalytics is a healthcare data consulting firm that helps payers and providers to maximize their CMS reimbursements and helps employers to reduce their healthcare spending through proven strategies to contain costs. For more insights on using data to drive healthcare, pharmacy and wellbeing decisions, follow BetaXAnalytics on Twitter @betaxanalytics, Facebook @bxanalytics and LinkedIn at BetaXAnalytics.

If you want to learn more about solving healthcare’s challenges, you may also like:

Dear Employer: High Deductible Health Plans Are Making People Sick

The Future of Healthcare is 3 Letters: CVS

My Talk for TEDxProvidence

2 Reasons Why Your Data is Lying

5 Questions with HR Leader Bob Selle on Why Decisions and Data Go Hand-in-Hand

Photo: Getty Images

Photo: Getty Images

Wellbeing goes far beyond what many think of when they hear the word “wellness.”  And employers realize that employee wellbeing is a key building block to creating an engaged and productive workforce. 

Bob Selle, Chief Human Resource Officer of Ocean State Job Lot (OSJL) talks with our team at BetaXAnalytics (BXA) about the challenges employers face with respect to maintaining a “well” workplace, and how data allows them to achieve this. 

BXA: What challenges make it difficult to have a healthy workplace?

Selle: Keeping a heathy workplace is hard, and retail poses some unique challenges. Associates are so spread out geographically and being able to communicate and get the right message can be difficult. Helping the associates understand the "why" to living a healthy lifestyle is also a challenge. We strive to translate what it means to their quality of life when they make healthy lifestyle changes.  Lastly and most importantly, we need to tie pieces together so they understand all the individual links that fit in a wellbeing chain.  Wellbeing goes beyond physical activity and nutrition; mental health, sleep, finance, and stress are all individual parts that tie the chain together.

BXA: How does Ocean State Job Lot support a healthy workplace?

Selle: OSJL supports a healthy workplace through a number of activities.  First, we have best in class benefits offerings at a very low premium to our associates. We are all one family and we believe in sharing our profits and low cost, and offering quality healthcare is one way to do this. We also listen to our associates.  For example, our associates want to be active and also give back to their communities. So we will pay for their entry fee in local walks/runs. We work with partners who share our values and find ways to have fun challenges between the locations we serve. Eating right is a big deal so we partner with Chop Chop, a non-profit who helped us create recipe cards and menus we share on our communications portal. Understanding that caring for associates and their families means caring for their pets, we now offer pet insurance.  In addition to this, we provide life insurance for every associate who works 20 hours or more.  Supporting a healthy workplace means so much more to us than the obvious.  We want to prioritize providing the education and resources that can ensure our associates have the tools they need to be healthy.

BXA: Why is data-driven decision making important at Ocean State Job Lot?

Selle: Data is valuable because it takes the emotion out of the equation. I like to ask my team, “What is the story?”  Data can provide this in many ways. The story can be told in pictures or graphs, but the bottom line is that it's factual and actionable.  The traditional barriers to using data to drive decisions are access (people do not know how to obtain the data they need) and understanding (people do not understand how using data can help them to form better decisions.) Every company has limited resources, so it is important to be targeted in your approach to wellbeing in order for your efforts to succeed.  At OSJL, we want to be smart stewards of our finances to be able to provide the best benefits possible for our associates, while providing low prices for our customers; making data-driven decisions helps that to happen.

BXA: How does OSJL use data to support their spending decisions?

Selle: We use the data to ensure that we work with the right providers for our associates. For example, if we did not know that not having life insurance coverage was a stress for our people, we would never have invested in this. Data showed that our associates are more at ease if their pets had insurance, so we made a business case to offer this benefit. Lastly, we have learned from our data that those who work part time for a number of businesses may not have the resources if an emergency came up.  So OSJL provides a full service employee assistance program to ease the burden.

BXA: What does the future of wellbeing look like at Ocean State Job Lot?

Selle: The future of wellbeing for OSJL is two-fold. First, we are becoming “surgical” in our approach to using data.  We want to make sure the resources we are providing to keep employees healthy are aligned with our true cost drivers and needs.  Second, wellbeing is at OSJL will continue to be fun and rewarding. Seeing and hearing the stories of associates who have transformed themselves using the tools we provide is priceless. This is why I do what I do.

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Founded in 1977, Ocean State Job Lot is the Northeast's largest, privately held, closeout retail chain with 126 stores in New England, New York, and New Jersey; approximately 4,800 employees; and annual sales exceeding $650 million. Our company mission is to provide exceptional value to our customers through opportunistic buying and selling of quality brand name merchandise, and to share the resulting profits with stockholders, associates, and the communities in which we live and work. The Ocean State Job Lot Charitable Foundation has a long history of philanthropic leadership, placing emphasis on local food banks in communities where we operate stores. Ocean State Job Lot is headquartered in North Kingstown, RI. oceanstatejoblot.com

BetaXAnalytics partners with employers like Ocean State Job Lot to use “data for good” to improve the cost and quality of health care.  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.  For more insights on using data to drive healthcare, pharmacy and wellbeing decisions, follow Follow BetaXAnalytics on Twitter @betaxanalytics, Facebook @bxanalytics and LinkedIn at BetaXAnalytics.