Employers are always looking for ways to reduce one of their biggest expenditures–the cost of providing health insurance to employees. Many employers have explored solutions such as adding wellness plans, reducing usage, and providing different provider access mechanisms, all with modest success.
Stemming the rising costs of health insurance requires management to understand and improve healthcare outcomes for their employee and dependent populations. Changing the future of employer health insurance will require a multi-faceted approach:
1. Driving additional value by reducing utilization of healthcare services within these employer populations.
2. Utilizing a wider lens through which to view performance of various providers, then making decisions based on those who are consistently providing low cost, high quality care.
3. Employer will need to combine their data with other companies across a geographic region to get a better picture of the provider landscape than has ever been possible before.
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Employers in the United States are constantly looking for ways to reduce what has historically been their number two or three largest expense item on their profit and loss statements—healthcare costs. Some surprising headlines have made waves in the business world: “Starbucks spends more on healthcare than coffee beans,” and “General Motors is a health and benefits company with an auto company attached.” While both statements are historically true, U.S. employers–including both GM and Starbucks–understand the challenge represented in keeping their workforce and their loved ones healthy. It’s both expensive and complex.
Over the past 20 years, employers have looked to a wide variety of solutions to address this problem. These solutions include wellness plans, different provider access mechanisms, and attempts to introduce interventions aimed at reducing usage. The success of these efforts was modest at best.
In the same timeframe, the number of large firms (defined as 1,000 employees or greater) that moved from a fully-insured to a self-funded plan grew from 62 to 90 percent. The reason is simple: large companies (with a greater sample size), utilize the greater predictability of larger populations. Because of this, insurance providers were able to sell the financial benefits of self-funding a covered lives population to employers at a lower price point than what was historically possible. This has largely been a function of improved efficiency in the financial structure, allowing providers to squeeze more and more value out of the self-insured concept, enabling lower pricing for large firms over time.
However, it’s becoming increasingly difficult to squeeze incremental value out of simply increasing the efficiency of these tried-and-true financial instruments. Combatting the rising cost of healthcare expenses will require management teams to engage more directly in understanding, managing, and improving healthcare outcomes for their employee and dependent populations.
What will this look like? Employers are even now waking up to the realization that they really don’t understand the healthcare expense line item as well as they do other major lines of expense that drive their business. The first step in this journey will be better access and understanding of the healthcare data that, to date, most employers have done very little to understand. Self-funded employer plans have every incentive to understand this cost structure, despite the complexity that exists, but to date most do not have effective ways to measure, predict, and manage this cost structure.
The future of employer health insurance will be in driving additional value by reducing utilization of healthcare services within these employer populations. It will also include utilizing a wider lens through which to view performance of various providers, then making decisions based on those who are consistently providing low cost, high quality care. To truly make a difference, employers will need to join their data with other companies across a geographic region to get a better picture of the provider landscape than has ever been possible before. Doing so will require a very different set of tools and infrastructure than what has historically generated cost reductions. Some examples of these tools and infrastructure include some old stand-bys, as well as new, innovative structures and methods to really generate the kinds of data and analysis for corporations to do right by their employees and their bottom lines.
Historically, the only source of data available to an HR team was retrospective, months-old claims file data that typically only tells a part of the story. Claims data is great to specifically detail what procedures and treatments were approved and paid for by insurers, the company, and ultimately the employee, but this data is point-in-time, event-specific, and usually driven by some incident or ongoing problem. It is only recently that more constant, wellness-driven data, like heart rate, caloric and fluid intake, daily exercise, and steps taken can be combined in a solution to make a difference in how individuals see and evaluate their personal health.
Trackers, such as Fitbits and the like, are making significant inroads into this market. In fact, in 2018 Fitbit announced a new initiative to more tightly couple the data they glean from their devices into a program designed to help employers better understand the wellness and financial status of their employee and dependent populations. This is a trend that will continue to grow, as technology further converges to bring devices and infrastructure together, allowing for sharper resolution into what drives health and wellness, and what interventions most effectively improve outcomes and lower cost.
In addition to improvements in how employers track and collect health and wellness data from individuals, strides forward have recently been made in the ability for infrastructure to integrate this data together in ways not possible in the recent past. These infrastructure improvements fall along two pathways. The first is the ability to see a more complete picture for an individual. Placing exercise, calorie, fluid, biometric, and sleep data in one place, and in context with each other, allows individuals to make better decisions. Correspondingly, taking that same data and combining it with claims data and clinical data across an entire employee population allows management to make much better decisions across the entire population around quality of care and cost. In the future, it will also be possible to combine these employer data across geographies, thus using larger sample sizes to drive quality and cost recommendations with more precision.
Finally, once employers have the data sources and infrastructure, there is still a missing piece. Who can best utilize this data on behalf of employees? One could argue that frontline healthcare professionals, not the HR department, can best make use of the data to inform best practices. While true that the data is invaluable in the hands of the Chief People Officer to create the best benefits program for employees, the day-to-day should be left to clinicians and primary care providers by empowering them to drive clinical effectiveness and reduce costs.
One example of this new paradigm can be found in the increase over the last ten years in primary care clinic providers aimed at the employer health insurance space. There are several examples in the market who are doing well in this space: Crossover Health, One Medical, and VillageMD are a few names that come to mind in the United States. Singapore-based Fullerton Health, with more than 500 clinics across eight regions in Southeast Asia is an international provider also doing innovative things in this space.
Each of these providers understand this fundamental reality: while employers–and, to a lesser extent, employees–are the ultimate payers in most healthcare systems, employees get a little queasy when the boss knows too much about their own personal health situation. This is one downside of the data revolution we are living in—so much data heightens privacy issues, and calls into stark contrast the fears that, through data, our own health could be used against us. While safeguards are in place, and this fear is largely misplaced, the entire system works much better when placed squarely in the hands of the person and group who can use it to greatest effect – primary care providers.
Forward-thinking primary care providers understand this shift and are working hard to incorporate all sources of data into a provider model that retains the best while minimizing the risks. Allowing healthcare professionals to have this data at their fingertips minimizes privacy risks while allowing these professionals to prescribe treatments and recommendations based on the totality of data. This hopefully prevents issues that would have historically worsened, costing more money and decreasing productivity.
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