When was the last time you shopped for health insurance? If you're like most Benefits Managers, it's been a few years since you sat down with your broker and tried to translate complex Uniform Discount and Data Specifications (UDS) into actual carrier rates.
At the end of the day, you just want to get your members the lowest rates for the services they use at the hospitals they prefer, but that’s been impossible with the lack of accurate, updated information available.
Thanks to new price transparency data, you can now directly compare negotiated rates at thousands of hospitals across carriers and plans for the first time, allowing you to reduce healthcare costs without compromising care quality. The savings are significant: our analysis finds an average savings opportunity of 27% across 500 common healthcare services. In this blog, we’ll walk you through exactly what’s in the new price transparency data and how self-insured employers can use it to capture these savings.
Price Transparency for Employers
Two price transparency regulations have changed the landscape of healthcare for employers: the Hospital Price Transparency Final Rule and the Transparency In Coverage (TIC) Final Rule. These rules require hospitals and health insurance companies to publish their previously private rates. Thanks to TIC specifically, detailed negotiated rates for all covered services are reported monthly for each carrier and plan, across all in-network healthcare providers (hospitals, labs, ambulatory surgery centers, medical groups, etc). This dataset is game-changing for self-insured employers—not only can you see exactly how much you pay for every service at each hospital with your current insurance plan, but you can also find out how your plan stacks up against other self-insured employer plans.
Of course, comparing plans hinges on having access to a comprehensive dataset. Fortunately, price transparency data contains rates for over 17,000 self-insured employers covering 31M participants. That amounts to 100%* (of course there’s an asterisk!) of self-insured employers identified by the Department of Labor. These employers include large Fortune 500 companies (think Amazon), powerful unions (think Service Employees International Union), as well as small companies like your local grocery store. Whether you’re at a big company or a small startup, you’ll find rates for your insurance plans, as well as those of other plans you may be considering. So what do you do now that healthcare rates are available? Go shopping, of course!
* We compare the number of active participants associated with self-insured employers in the price transparency data with the number of active participants on self-insured plans as identified by the Department of Labor in their Annual Report on Self-Insured Group Health Plans. You can find more information in the Methodology section.
Case Study: Shopping Spree in NYC
We know it’s easy to get overwhelmed by all this data, so let’s start simply by shopping for a single service at a single hospital. Today we head to shopper’s paradise: New York City. What are we shopping for? While each employer has unique healthcare utilization patterns, for many employers, maternity care is a top priority given their high spend on Obstetrics.
Within Obstetrics, there are notable high-risk, high-cost procedures that are particularly important. If you’re looking at your overall claims spend, births likely make up a significant portion of your utilization. A pregnant patient who also has other known health risks (called comorbidities) may encounter clinical complications during the process of a vaginal delivery. Within healthcare data, that complex vaginal delivery encounter is codified as MS-DRG 805. Let’s consider MS-DRG 805 at Hospital A, a large academic medical center located in Manhattan. At this hospital, negotiated rates range from $21,057 to $30,199, for the same procedure.
Why are some companies paying an extra $9.1k each time an employee gives birth? Well, odds are they don’t know that they can do better. Employers have traditionally deferred to carriers to negotiate rates on their behalf. Before price transparency data was available, the outcomes of those negotiations were a black box. That’s changed. Now, you can peer inside that box and see that UnitedHealthcare plans have the highest rate at Hospital A, while Aetna plans have the lowest rate. In this case, as an employer with a UnitedHealthcare plan, you can save 30% on complex vaginal delivery by switching to an Aetna plan. Importantly, you can realize these savings without compromising care quality—your members will still be going to the same hospital for the same procedure.
After seeing the graph above, you may be thinking: great, I’ll just sign up with Aetna and call it a day. Not so fast! Because each hospital independently negotiates rates with each carrier, carriers with the best rates at one hospital won’t necessarily have the best rates at a nearby hospital.
The graph below shows negotiated rates for complex vaginal delivery at Hospital B, a few miles away in Jersey City. Here, the tables have turned—employers contracted with Aetna are receiving the highest rate while those working with UnitedHealthcare are getting rates that are 53% lower. You already know that the complicated reality is that you must consider where your employees are receiving care when deciding on which carrier to select; it’s just that now, you have real, hard numbers to inform those decisions. If most of your members live in Manhattan and go to Hospital A, it makes sense to choose an Aetna plan. However, if your members primarily live in Jersey City and use Hospital B, a UnitedHealthcare plan gets you the lowest rates. With this data, you can definitively know where the highs and the lows are in every hospital that your members use.
Beyond differences in carriers, the graphs above show that employers also have the opportunity to reduce costs even when staying with the same carrier. At Hospital B, we see that some Aetna plans have a complex vaginal delivery rate of $27,223, while other plans** charge $11.2k (41%) less. Not only does choosing the right carrier matter, but choosing the right plan with that carrier can also have a huge impact. Price transparency data can help you find both the carriers and the plans with the most cost-effective negotiated rates.
** Price transparency data also includes rates for different networks, which can also lead to different rates for the same care.
More Hospitals, More Savings
So choosing carriers and plans with the lowest negotiated rates can result in significant savings… at two hospitals in the New York metro. But what about employees outside of the Big Apple? Zooming out, we see that 59% of hospitals across the country have more than one negotiated rate for complex vaginal delivery. In other words, employers can price shop between plans at most hospitals. Each of these hospitals represents an opportunity for you to reduce costs by choosing a lower-rate plan.
While the graph above tells us how often you can save, you may be wondering how much you can save. To measure this, we can perform the same single-hospital savings analysis we did for Hospitals A and B, except this time across all hospitals with multiple vaginal delivery rates. For each hospital, we found the plan with the highest rate and the plan with the lowest rate and calculated the savings opportunity as the percent change when moving from the highest rate to the lowest rate.
Across all hospitals with multiple vaginal delivery rates, employers (and in turn, employees) can save an average of 31% by moving from the highest-rate plan to the lowest-rate plan. Of course, this depends heavily on the hospital and region. We see a range of savings opportunities across the country's largest metros, with Atlanta topping the charts at 51%! Although these numbers can be eye-popping, keep in mind that not all employers are paying the highest rate at each hospital so your actual savings will depend on your current rates and which hospitals your members use, as well as the specific services they utilize.
Beyond Birth
We’ve seen that there are significant opportunities for self-insured employers to reduce vaginal delivery costs when using price transparency data to shop for insurance plans with the lowest rates. But the big-picture thinkers among you might be jumping ahead, wondering whether we can estimate savings for the entire range of different healthcare services your members use. We can!
Among the tens of thousands of services in the price transparency data, let’s focus on a subset of CMS’ 500 shoppable services, which are some of the most utilized and plannable services, like labs, procedures like knee replacements, and common drug therapies. Running the multi-hospital savings analysis across each of these services shows us very promising results: lots of opportunities to save, to the tune of 27%!
Savings vary quite a bit depending on the service, ranging from a modest 5% to a dramatic 54%. At 5% savings, you can start to have a real impact on your medical spend while gaining confidence that your members are getting cost-effective, quality care. At 54% savings, you’re significantly improving your company’s bottom line while maintaining quality care for your members. Because each employer has their own unique healthcare utilization patterns across these (and other) services, your actual savings will likely fall somewhere in between. The good news is that regardless of your utilization patterns, there are savings to be found.
The Path Forward: Strategies for Benefits Managers
What's a benefits manager to do with all this data? Laugh? Cry? It’s okay, data makes us emotional too.
First, recognize that you have an incredible opportunity to reduce healthcare costs for your company and employees. Different carriers often negotiate very different rates for the same service at the same hospital. With the availability of new price transparency data, you can now directly compare negotiated rates at thousands of hospitals across carriers and plans. As we said above, employers who use this data to shift from the highest-rate plans to the lowest-rate plans can reduce healthcare costs by an average of 27% across healthcare services.
To realize these savings, you’ll need to become a savvy, data-driven shopper. Start by understanding your company’s healthcare utilization patterns: which hospitals your members go to and which healthcare services they’re using. This helps you hone in on the key areas that drive your healthcare costs. Next, find the negotiated rates for these hospitals and services for your current plan and compare your rates with the rates of other carriers and other plans. Finally, work with your stakeholders and broker to select the carrier and plan with the lowest rates (that meets your other plan requirements). With these steps in mind, and price transparency data now at your disposal, go forth and confidently shop for the best health insurance for your members!
Methodology
Data and Preparation
This analysis is based on the Turquoise Payer Dataset (“Payer Data”), which is derived from extracting, aggregating, and cleaning price transparency data from machine-readable files (MRFs) published by 200+ major health insurance companies. Payer Data contains negotiated rates for all covered services and procedures for each insurance company and insurance plan, reported monthly for all in-network healthcare providers, including hospitals, imaging centers, labs, ambulatory surgery centers, and professional fees for medical groups. Data is as of December 2023.
Plan Selection
Self-insured employer plans are identified by matching Employer Identification Number (EIN) plan IDs in the Payer Data to Form 5500 EINs with a 4A type Welfare Benefit Plan code. Form 5500 data is obtained from the Department of Labor website, where it is released once per calendar year. We only included self-insured employer plans from the largest carriers: UnitedHealthcare, Aetna, Cigna, and Blue Cross/Anthem.
Rate Selection
Negotiated rates for vaginal delivery (MS-DRG 805) as well as CMS’ 500 shoppable services are included in this analysis. We include rates designated as ‘negotiated’ negotiated_type in the Payer Data, with no associated billing code modifiers.
Outlier Removal
Given that the intra-hospital price ranges used in this analysis can be sensitive to potential outlier rates, we take two measures to reduce the impact of potential outliers.
Statistical outlier removal: we calculate a modified z-score across all rates for each service and remove rates with a modified z-score greater than 5. A sensitivity analysis of multi-hospital savings and multi-service savings shows robust results across z-score thresholds of 2 and above. Modified z-score is calculated using the formula:
- Where Mi is the modified z-score of the ith data point
- xi is the ith data point
- x͂ is the median of the dataset x
- MAD is the Median Absolute Deviation of the dataset x, defined as MAD=Median(|xi − x͂|)
- 0.6745 is a scaling factor for using the MAD as a consistent estimator for the standard deviation
Medicare payment-based outlier removal: a minimum Medicare rate is calculated for each service by finding the lowest Medicare payment (based on IPPS and OPPS) for that service across all hospitals. Any rates lower than this minimum Medicare rate are excluded.
In addition to outlier removal, we also calculate median savings opportunities as a point of reference, which are less sensitive to outliers. Median savings are discussed in the Analysis section below.
Analysis
Self-Insured Employer Coverage
To understand the coverage of US self-insured employers in the Payer Data, we compare the number of active participants associated with self-insured employers in the Payer Data with the number of active participants on self-insured plans as identified by the Department of Labor in their Annual Report on Self-Insured Group Health Plans.
The number of active participants associated with self-insured employers in the Payer Data is calculated by pulling in Form 5500 data published by the Department of Labor for each self-insured employer identified in the Payer Data based on EINs (see “Plan Selection” above). Form 5500 data is released once per year, and data used in this analysis is for plan year 2022. Across 17,060 self-insured employers in the Payer Data, we observe 31M total active participants.
The most recent 2023 Annual Report on Self-Insured Group Health Plans (“Annual Report”) summarizes findings based on filings from statistical year 2020, the latest year for which complete data was available at the time of their analysis. The report finds 31M total active participants on self-insured plans, exactly matching what we observe in the Payer Data.
Please note that while the self-insured plan participant numbers in the Payer Data and in the Annual Report match nominally, these numbers are not directly comparable as the calculations are based on Form 5500 data in different years. Despite this clear difference, we can see based on historical annual reports that overall self-insured participant count has changed slowly since 2010, ranging from a low of 27M in 2010 to a high of 32M in 2019 with no annual change of greater than 1M active participants. Because the Department of Labor’s calculations are algorithmic and have changed over time, annual reports should not be compared directly, but the low variation of the Annual Report participant numbers can provide some assurance that the figures reported in the latest Annual Report will likely not change dramatically when updated with the 2022 data used in our Payer Data calculation. As such, we believe that the close match between the Payer Data numbers and the 2023 Annual Report numbers is a compelling indicator of high self-insured employer coverage in the Payer data.
Single-Hospital, Single-Service Savings Opportunity
The fundamental unit of analysis is the single-hospital, single-service savings opportunity calculation. This calculates the savings opportunity that can be obtained by shifting from the self-insured plan with the highest rate for a given service at a single hospital, to the self-insured plan with the lowest rate for the same service at that hospital, expressed as a percentage. The calculation is (highest rate - lowest rate) / highest rate for a single hospital and single service.
Multi-Hospital, Single-Service Savings Opportunity
The multi-hospital, single-service savings opportunity calculation builds upon the single-hospital, single-service savings opportunity calculation. We first calculate the single-hospital, single-service savings opportunity for each hospital with at least 2 distinct negotiated rates, then aggregate across hospitals. In our analysis, we aggregate using a trimmed mean approach after removing outliers (see “Outlier Removal” above). We test the consistency of findings using this approach vs aggregating using the median, and find that both approaches show reliable savings (national median-based aggregation results in 30% savings opportunity for complex vaginal delivery vs 31% savings opportunity using the mean).
Multi-Hospital, Multi-Service Savings Opportunity
The multi-hospital, multi-service savings opportunity calculation builds upon the multi-hospital, single-service savings opportunity calculation. We first calculate the multi-hospital, single-service savings opportunity for each of CMS’ 500 shoppable services, resulting in a percentage savings for each service. We aggregate across these services by taking the mean. We test the consistency of findings using the mean vs aggregating using the median, and find that both approaches show reliable savings (median results in 26% savings opportunity vs 27% savings opportunity using the mean).