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.
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.