Using Data Transparency to Control Hospital Costs

Using Data Transparency to Control Hospital Costs

Sep 21, 2022
On this episode of On the Evidence, guests Evelyn Li of Mathematica, Maureen Hensley-Quinn of the National Academy for State Health Policy, Gloria Sachdev of the Employers' Forum of Indiana, and Guru Rasukonda of Mathematica discuss the potential of data transparency tools for curbing rising hospital costs.

On this episode of On the Evidence, guests Evelyn Li of Mathematica, Maureen Hensley-Quinn of the National Academy for State Health Policy, Gloria Sachdev of the Employers' Forum of Indiana, and Guru Rasukonda of Mathematica discuss the potential of data transparency tools for curbing rising hospital costs.

Increasing hospital prices are the biggest driver of rising health care spending for Americans. Historically, one reason hospital costs have kept rising was minimal price and quality transparency, which made it difficult for health care purchasers, such as employers and state programs, to negotiate lower prices. Opaque pricing has also prevented health care consumers from shopping for care that is both high quality and affordable. In compliance with recent federal regulations, hospitals and insurance plans are now sharing more of their pricing data than ever before, but employers, state regulators, journalists, health care consumers, and others still need help translating thousands of data files into useful, understandable insights. To make sense of the pricing data, stakeholders also need to know the underlying costs for hospitals to provide services. However, it hasn’t been possible to know those underlying costs due to the lack of access to data.

This year, Mathematica partnered with the National Academy for State Health Policy (NASHP) and the Employers’ Forum of Indiana (EFI) to create two free online tools (the Hospital Cost Tool and Sage Transparency, respectively) to address the problem of rising hospital costs by helping people integrate, analyze, and interpret the data.

Our guests for this episode of On the Evidence are Gloria Sachdev, president and CEO of EFI; Maureen Hensley-Quinn, a senior program director at NASHP; Evelyn Li, a senior researcher at Mathematica; and Guru Rasukonda, a senior project manager at Mathematica. In the episode, they discuss the following topics:

  • The problem with rising hospital costs
  • The role that data transparency could play in helping employers, consumers, and others choose high-value care
  • The impact of recent federal regulations on making hospital cost data available to the public
  • The need for accessible online and interactive tools to make large sets of hospital cost data useful
  • How tools such as Sage Transparency and the Hospital Cost Tool are already being used and how planned updates could enhance their utility

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On the Evidence · Using Data Transparency to Control Hospital Costs

A version of the full episode with closed captioning is also available on Mathematica’s YouTube channel here.

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There's a lot of different ways that they're slicing and dicing this. It speaks to different policymakers in different ways, but there are strategies that mesh with each of these. You look at what are different hospitals' costs and expenses to make sure those are being covered, while also trying to provide some predictable pricing for purchasers of care over time.


I'm J.B. Wogan from Mathematica. Welcome back to On the Evidence, a show that examines what we know about today's most urgent challenges and how we can make progress in addressing them.

On today's episode, we're going to talk about the promise of data transparency in controlling for the biggest driver of rising health care spending for Americans, which is hospital costs. Historically, one reason hospital costs have kept rising is minimal transparency when it comes to both the price and the quality of care. That lack of transparency has made it difficult for payers of health care services to negotiate lower prices. Such payers include Medicare, Medicaid, private insurance companies, and employers.

The opaque pricing, by the way, has also prevented health care consumers like you and me from being able to shop around for care that is both high-quality and affordable. But change is afoot. In January of 2021, a federal rule went into effect that requires hospitals to disclose their negotiated prices for all items and services. This summer, another federal rule went into effect that requires health plans to make similar disclosures.

Hospitals are now sharing more of their cost and pricing data than ever before, but health care payers and consumers still need help translating thousands of data files into digestible and useful insights. Fortunately, there's a free Web tool for that; actually, there are two. This year, Mathematica partnered with the National Academy for State Health Policy and the Employers Forum of Indiana to create two free online tools to address the problem of rising hospital costs by helping people analyze and interpret the data.

The tool Mathematica developed in partnership with the National Academy for State Health Policy is called the Hospital Cost Tool. The tool Mathematica developed in partnership with the Employers' Forum of Indiana is called Sage Transparency. During the episode, we'll go into more detail about the tools, which serve slightly different purposes but are complementary.

My guests for this episode are Gloria Sachdev, the President and CEO of the Employers' Forum of Indiana; Maureen Hensley-Quinn, a Senior Program Director at the National Academy for State Health Policy; Evelyn Lee, a Senior Researcher at Mathematica; and Guru Rasukonda, a Senior Project Manager at Mathematica.

On this episode, we talk about the problem with rising hospital costs; the role that data transparency could play in addressing those rising hospital costs; the impact of recent federal regulations on making hospital cost data available to the public; the need for accessible online and interactive tools to make hospital cost data useful; and how two such tools, Sage Transparency and the Hospital Cost Tool, are already being used and how planned updates may enhance their usefulness in the future.

On the Mathematica blog associated with this episode, I'll include links to Sage Transparency and the Hospital Cost Tool. You can also find a full transcript of this episode on the blog. I hope you find this conversation useful.

So I do want to talk today about the two websites that our organizations have created to help with the problem of hospital price transparency. Let's start by providing listeners with some context.

Gloria, what is the current problem with hospital costs and their transparency or lack thereof? And if you could, from your vantage point at the Employers' Forum of Indiana, what are some of the concerns that are specific to the employer perspective?


Thank you for having me on.

You know, health care is just really complex; and health care pricing is particularly complex. Traditionally, there's been no line of sight to seeing hospital prices. So as a person, as an employer, you would purchase health care and then just get billed, maybe weeks later. When that happens, you have no choice. You're not able to sit there and say, "Here's the best price or the best quality, and that's where I'm going to go." So that's really the struggle that's been going on for decades.

Sage Transparency provides some information on price and quality and costs from five different data sources, all reputable data sources, to just allow everyone to have some information to make more informed decisions.

Indiana, unfortunately, looking at the RAND Hospital Price Transparency studies and other studies – we see that Indiana's hospital prices are fourth highest in the country. There's a lot of variability in those prices. Some of them might be 150% of Medicare, so we're paying 1.5 times what Medicare pays for the exact same services; and then some prices are 450% of Medicare. There's no correlation to quality. So now it allows employers to just make more thoughtful choices on behalf of their employees when they're considering benefit design.


Maureen, I wanted you to weigh in here as well. The National Academy for State Health Policy has a slightly different constituency and mission from the Employers' Forum of Indiana. Where do you see overlap in your concerns about hospital price transparency? And name some of the concerns that are specific to state health policymakers.


I think there's a lot of overlap between what employers care about and what state officials care about. When I think about this, I consider state officials are a diverse group. They are purchasers of care. They are regulators of their health market, and they are champions or watchdogs for consumers in their states. So different offices are going to use hospital transparency data differently; but all who want affordable, comprehensive coverage really need to start looking at the underlying costs that are driving some of the premiums, out-of-pocket costs for services that consumers are experiencing.

Employers especially are at the front lines of wanting to retain employees, providing robust benefits, and how to do that in an environment where health care costs just keep rising. So as we look at transparency, one of the first issues is access; and there is a lack of access even though more and more transparency is coming out. But then the next issue after you have data is understanding what you're looking at and then how to use it.

So I like to use the example, NASHP's Hospital Cost Tool uses Medicare Cost Report data. That data is available publicly for each individual hospital, but those reports are complicated. They are hard to use. You get a lot of data, a lot of information; but you're not sure what's meaningful and what isn't, how to pull that out to be able to understand the comprehensive price and cost story of the hospital you're most interested in. Then without a doubt, after you start looking at one hospital as a state, you want to this normal? What's the benchmark? How should I be considering this?

So you need to look at neighboring hospitals. Then, you need to understand is this an urban versus rural problem? Is this a problem because this health system is driving up costs? So then you want more hospital data.

So NASHP's tool strives to answer those questions. We strive to provide analysis of this data across as many hospitals as we can offer, but doing so in a digestible way so that people can actually use the data.


I believe you said the data is becoming more transparent, that we're going in the right direction. I believe that's partially a reference to some recent federal rule changes. So I was hoping you could speak to how recent federal rule changes have increased the likelihood of transparency.


The recent federal rules, for the first time, have set a national expectation that hospital prices and health plan payments for services should be transparent; and that is critically important. We know that hospital compliance has been slow, and further improvement is needed. While the expectation has been set, which is notable, the implementation of that has not been achieved yet.

We also know that having access, as we noted before, to data is a necessary first step; but the federal rules specifically note that this data should be presented in a machine-readable format, and that is not user-friendly. Consumers absolutely can't use that information. We have been talking with state officials from state employee health plans who are accessing their third-party administrator plan information right now, and even they are struggling with the machine-readable format to understand what is actually within that dataset.

So we know that policy across states and federal governments is iterative. So the federal rule is an important first step, and setting the expectation is critical; but there needs to be continued work to make sure that this information is as usable as possible. I'll just say that, rather selfishly, NASHP's tool and Sage Transparency are helping to fill a gap as we work out these details. I'm optimistic. I'm very optimistic about the level of transparency that's coming forth.


What is machine-readable format? What does that look like? I'm imagining like a printout of binary code. Is it quite that bad, or what makes it so difficult to use?


We're told it's symbols and some letters, some numbers. So I personally haven't dove into some of these. We expected a big datasheet of numbers, but they're having trouble even finding the numbers in there.


Oh my gosh.

Well, Gloria, I wanted to get your take as well what has been the impact so far of these federal rule changes around hospital price transparency.


Well, the hospital price transparency – the federal rule went into effect January 1st of 2021. So it's been around now for over a year-and-a-half. Similar to what Maureen was talking about, there are requirements that all the prices have to be in a machine-readable file; but also, 300 shoppable services can be posted on their website and more easily accessible.

The issue is, again, some hospitals – a few – have chosen to put up a spreadsheet of the 300 shoppable services by plan, by procedure. But most hospitals, by and large near all hospitals in Indiana at least, aren't doing that. They have a patient inquiry portal, but then you have to put your insurance information and your Group ID information. Certainly as an employer if you only have, let's say, a BlueCross BlueShield plan or a UnitedHealthcare plan, you can't shop across plans because that's what you're trying to do.

You're like, hm, I wonder who has the best deal. I'm contracting with BlueCross BlueShield right now, but I might be interested to see if UnitedHealthcare or other insurance companies got a better rate at that hospital since that's the hospital or hospital system that the majority of my employees go to. So that's still missing. That's in the machine-readable files. They are, as Maureen alluded to, generally terrible; and I have seen the files. I've seen several of the files; and you really have to be a machine to read them, not a human.

So tools like Sage Transparency and the Hospital Cost Tool, the goal is just to make it simple – make it simple to look at so that it is ultimately usable to align payment with the value of services provided. I'm hopeful that as we have more and more price transparency, I do think there's an opportunity for States and for the Federal Government to put some rules around the machine-readable files. That's certainly an opportunity so that they're in a standardized format. That makes it easier to ingest for partnerships with Mathematica and other IT folks if everything's standardized.

One difficulty that Guru might be able to talk a little bit about is that when data comes in and it's not all standardized, it's just a big lift to get it all synchronized and standardized. So for example, if there's not a health system ID number associated with all of the hospitals, then you don't know, well, are these independent hospitals? Are these hospitals associated with a particular health system?

So we've been, and Mathematica's been, doing a lot of heavy lifting and just trying to, again, make the data more understandable and usable.


Well, Gloria, you teed up, I think, Guru and Evelyn nicely there. I'm sort of imagining these like long printouts of hieroglyphics, the machine-readable formats.

Guru and Evelyn, I'm not sure who wants to go first; but what are the limitations or challenges with using the data that has become available so far?


The reason transparency and coverage rule I think reflects a giant step towards the health care price transparency. Since July 1st this year, we've seen that health insurance companies by way of compliance have posted hundreds of thousands of files. The volume of data that has become available recently has the potential to transform the entire industry. But the big challenge, as Gloria and Maureen addressed here, is that most consumers and health care purchasers are not data savvy. The machine-readable files even makes a data-savvy data scientist a headache, let alone the general public.

So the burden is on companies and data solution innovators to come up with ways to ingest and integrate the many data files. If you think that integrating two data sources is challenging, we are talking about integrating hundreds and thousands of files to get meaningful insights behind the data. If consumers want to know -- for example, orthopedic surgeries – how much do I have to pay at this large system hospital compared to an independent hospital in the nearby community?

Well, without data science solution, the answer is not readily available even though the data is just sitting out there. So there's a long distance between the myriad of data available to us and digestible, actionable information that the general public needs.


If this is giving data scientists headaches, then what hope is there for the rest of us?

Guru, is there anything you would add in terms of some of the limitations with the data that's been made available so far?


From the Sage Transparency perspective, as Gloria already mentioned earlier, we are consuming data from five different data sources – mainly the CMS Hospital Compare, RAND, Quantros, NASHP, and Turquoise Health. There are a few challenges when trying to combine such disparate datasets. So what we understand is that they're already in formats and data structures and, most importantly, the frequency of release of new versions – these frequencies or the release dates are not the same across these five data sources

So that requires a need for a robust data model that can be updated by new datasets from one source and still work with the older versions and the data source which have been integrated earlier. So that is one part of the integration aspect of these datasets.

Mulching and stitching these datasets together to achieve a single meaningful dataset that can be used for reporting is a very complex design and development activity. Apart from requiring good sequel and database skills, there's also a need for some (inaudible) experts that understand these datasets and are able to link them together. Designing and integrating the data model requires an in-depth study of what is required from these datasets – the workflows, the multilevel search capabilities, and the information access controls.

Apart from these now, we also have had scenarios of bad data or data quality issues. We have had situations where we were not able to consume some parts of these source datasets because of not being able to link them together. We had situations or requires from some of the users who came back and asked us, "Where is this hospital, where is that hospital system?" The reason for that is we were not able to combine them together because of data quality.

But then when we had such situations, we did some deep dives into those particular datasets or specific data line items in the database to link them together as we learned more about them. I'm assuming, or maybe I'm expecting, that the time from Mathematica sharing these data quality issues with the source systems, we will be able to, over time, start getting better data as we go; and we'll avoid such issues in the future.


Maureen and Gloria, is there anything else that you wanted to touch on in terms of the current limitations of the data that's been made available so far?


I'd like to comment on what Guru mentioned regarding data quality. The quality of the data that's coming in is great. So I don't want there to be a misunderstanding that the data is not of high quality. The data from the five data sources that comes in is of high quality. The data quality in developing Sage Transparency as a tool is the issue that he's referencing in that we're trying to link, for example, in the RAND hospital price transparency studies, we have 4,100 hospitals. But in the CMS datasets, we have over 5,000 hospitals. Then in the Turquoise datasets, it varies because they get daily feeds; but we get a quarterly report from them to upload. And the number of hospitals, it's in the thousands again, is going to vary.

So linking those and saying, "Do I have five data points from these five different sources for every hospital," no, I don't. I might only have two data points, maybe one quality data point and one price data point to display. Should we display only two, or should we display only one? Those are the quality issues that we've been working through.

Again, also like linking -- we'll have the hospital system information, but some of the hospitals in the datasets don't have the hospital ID linked to it. So they will be in the hospital dataset, but they may not be in the health system dataset even though they are part of the health system. So the data we have is awesome; it's solid. It's just the linking them all together, five different datasets, is really where we have spent, I would say, a good eight months trying to pull it all together to make it useful.


So, Gloria and Maureen, I'd like to hone in now on the Web tools that our respective organizations have partnered to create – your respective organizations partnering with Mathematica, I should say. We've already talked about it a little bit, but I want to make sure we're explicit and specific about these two tools. So tell me, what do they do; and how are they intended to spur action by consumers, employers, or government actors?

Maybe, Gloria, you can start us off by talking about Sage Transparency.


I'd be happy to.

So what does Sage Transparency do? What problem are we trying to solve?

When we got through the RAND Hospital Price Transparency studies, the first one came out in 2017; and that was just Indiana. Then we had RAND Hospital Price Transparency Study – we call it RAND 2.0 – in 2019 that had 25 states; and then 3.0 and 4.0 had 49 states plus D.C. But these are big, hairy Excel spreadsheets that are kind of complicated to use. Once we would educate people on how to use them, we'd say, well, now they want to go to the best employers and people. They want to go to the best quality at the best price. That's where we want to go.

So I'd say, "Well, you could go to the CMS Hospital Star website. It's freely and publicly available," and link it up. I'd make graphs for them kind of in presentations. Then I realized no one was doing it (laughing). So we developed Sage Transparency just to make it easier for folks to say, "Here's the publicly-available price data. Here's the publicly-available quality data." Then when cost information became available, we were so excited because there are so many great measures on the NASHP tool; but particularly there's this commercial breakeven price.

So we now had the opportunity to say, "What are employers paying as a percent of Medicare, and what would they need to pay for that hospital to break even?" So that takes into consideration all of their costs. If they were losing money on Medicare payments, Medicaid payments – and Maureen can dive into that more. But to keep that hospital financially whole, what would they need to be paid as a percent of Medicare?

The difference in many of the hospitals is just unbelievable. It's over 100%. Then in some hospitals, their costs are high. So maybe what we're paying them is quite reasonable. In some of them, there's not a lot of difference. So the whole idea is how do we get to a fair price? That's the goal of Sage Transparency, is helping people identify what's a fair price, number one; and, two, where is the best quality at the best price?

So right now, people can customize. There are four tabs on Sage Transparency. So you can look at a hospital and kind of get a face sheet, if you will, everything we have about a hospital. You can look at hospital systems and compare them. You can look at states and compare states or compare within a state. You can compare clinical categories; so you can search by orthopedics, or GI, or cardiovascular and see what the price and quality – what it looks like.

We don't have it at the procedure level. So we might say, "orthopedics," but we don't say, "knee replacement," "hip replacement." The reason for that is employers don't shop by procedure. People do; but this was really designed for employers, academics, policymakers, and researchers. To get it really at the procedure level, I would say states that have all payer claims databases should show everything now at the procedure level.

In Indiana, we aim to stand up an APCD; and about half the states in the U.S. have one. But most of them don't have it at the procedure level. So we might put it in Sage Transparency if there's interest from the public to include it. We would have it from the insurance company data files that have recently been made available. We could put procedure-level information in it if there's interest. But then we would like to be able to say, "What insurance plan do you have?"

"Oh, I have Anthem BlueCross BlueShield. I'm in this state. I'm looking for this procedure, and what's the price?"

Or maybe you want to be able to compare across plans. So what's really exciting to me about the future of both of our tools, or specifically Sage Transparency, is that in addition to just having hospital prices and hospital quality, we are going to get into the space of independents because the independents, by and large, are a lot less expensive and provide oftentimes equal or better quality. But we don't have them in the tool yet. So while it's fine and dandy to compare across hospitals and among hospitals, what about the independent oncology service; or what are the prices and the quality of the oncology or the independent orthopedic service if I need a knee replacement? How do they compare to the hospital?

Then in the RAND study, we looked at ambulatory surgical centers. We haven't loaded that into Sage yet, but we're going to by year's end. So the ambulatory surgical center prices for 4,100 ASCs is, by and large, a lot less expensive than the hospital. So I think we will be able to provide just – I don't know – more transparency over time and in graphs. So when you go to Sage Transparency, you see pie charts and bar graphs; and it's customizable, and you can pick certain regions within your state. So the goal of it was just to make it as user-friendly as possible.


Maureen, if you could just walk us through the Hospital Cost Tool now. They are similar. They have a similar purpose. They have a similar originating motivation – but exactly what it does, what the motivation was behind it.


NASHP does work with state officials across agencies and offices. We have state officials advising our hospital and health system work, and I will share why hospitals – why is that our focus. Hospitals have been for a very – I can't tell you how long – as we've looked back at U.S. expenditure data, they are consistently where the United States spends the largest proportion of our health care dollar. There's lots of reasons why that may never change, and that's fine. But as states are looking at how to get a sort of handle on rising health care costs, they did ask NASHP to focus in on hospital and health systems so they can understand this more, understand what levers are available.

So as we started diving into this work, one of the first things we set out to do – this was before the federal transparency rules – states asked for data. So we started developing a model legislation and template so that states could request or compel hospitals to provide financial data. As we were developing that, our advisor said, "Okay, but what about costs? What we need to understand is cost at the hospital level."

My colleague, Marilyn Bartlett, said, "I can do that with the Medicare Cost Report." She said, "I've already been doing that." She worked in Montana at the State Employee Health Plan. She did change how Montana State Employee Plan pays for hospital services as a multiple of Medicare and saved that health plan millions of dollars and the state overall.

So she took what she used there and created a calculator for us to share with states. That calculator was honed over time, and we were able to create the Hospital Cost Tool with the assistance of Rice University, who pulls down a ton of data for us from a federal database. Then, Mathematica created this amazing tool that provides these graphics; and it's customizable and explains different pieces of information.

The break-even metric, as Gloria described – and she did a great job of that – it is a multiple of Medicare that the hospital needs in order to cover all of its expenses. It's losses we take into consideration, it's profits, its investments. So it's like at a bare minimum, commercial payers will need to pay X percentage of Medicare to that hospital to cover their costs. We are not suggesting that that's what hospitals should be paid It's a data metric that is useful to understand essentially what their costs are. As we develop tools/strategies to try to get sort of a handle on rising costs, we don't want to do so at the expense of access. So maintaining quality access is a driving goal of this work.

But other metrics that are used, cost-to-charge ratios. As that percentage changes, what is driving that change? Is it an increase in costs, or is it an increase in charges? Is it an increase in both? What can we do? When did that start? How do we handle that? What policies could be used to help a hospital, or encourage a hospital, to get a grip on some of those things?

Payer mix – it's essential to understand a hospital's payer mix. Then importantly, states very much care about trends over time. So different interventions that they take, different coverage models that they put forward. The expansion of Medicaid through the ACA is an area that states are always asking about. At what point in the cost trajectory do we see that change take place, and did it have any influence or effect on hospital costs, break-even, their profit margin? So we can see that in looking at this data over time.


Maureen did a super job explaining that because that tool also provides ten years' worth of historical data, which is very valuable because then you can trend information – you know, trend hospital profit margin, compare hospital profit margin, a particular health system to a state average or to a national average. That's been really, really helpful – not so much the employer discussion but really the policy discussion.


That leads me to my next question, which is how these tools are being used. Maureen, so far, who is using the Hospital Cost Tool and how?


We know that a variety of different policymakers at the state level are using it. We know that researchers are using it. We know that employer groups are using it. I think the goals of all of those groups are the same, but how they take in the information and what they do with it I think is different.

So as I've noted before, state policymakers are a diverse group. You have individuals in departments of insurance that are regulating and providing consumer protection. You have Medicaid officials that have serious budget constraints and are trying to make sure that they're paying the best for the quality that they're getting. Then you even have offices that have responsibilities, literally, for cost containment. All of those different groups are using our information, and they're using it different ways.

People are looking at payer mix and hospital profit or loss according to different payers. They are taking a look at what consolidation means for their states. If they know some of the dates when independent hospitals are purchased by larger systems, they can track over time whether that has affected a hospital's cost and price.

And again, cost-to-charge ratio – taking a look at the trends for that. Like we know that prices increased, but what was the driver of that? Sometimes there isn't an obvious driver in the data, which prompts different questions. But with that, we've been talking with state officials. They are interested in trying to better navigate consolidated systems. So we have model laws/model policies that they can pursue.

Anti-competitive contracting, things of that nature – when there are states that look at the tools, look at the RAND – or we're adding RAND 4.0 data. We use 3.0 right now. But as they look at the RAND versus the break-even – so where a hospital needs to cover its expenses versus what they get paid, which can be dramatically different -- states are asking why, and maybe we ought to seriously look at some cost containment measures that might even be referencing Medicare to limit payments by different purchasers of care. But doing so in a thoughtful manner, where you don't just take up blunt instruments; but you look at what are different hospitals' costs and expenses to make sure those are being covered, while also trying to provide some predictable pricing for purchasers of care over time.

So there's a lot of different ways that they're slicing and dicing this. It speaks to different policymakers in different ways. But there are strategies that mesh with each of these, and NASHP gets the opportunity to work on this. We're delighted.


Gloria, with regard to Sage Transparency, what do we know about engagement there? Who's using it and how?


We've had about 11,000 – over 11,000 people, or sessions I should say, on the Sage Transparency tool since we launched in on May 5th. So we're really excited about that, and we hope that continues to grow. You know, it's freely and publicly available. We don't have data because we don't make people put their credentials to access it because it's just open to the public. Going forward, we are considering doing that just if they want to create custom private reports, so that we know what level of access to give them to the data. Because we have much more data than we're displaying on Sage Transparency, and some of that data may be helpful to folks. So that's a future use.

But to get back to who's using it and how they're using it, employers are using it for direct contracting – is where I'm seeing them primarily use it. They're also using it to ask tough questions of the insurance companies – like, "How did you negotiate such high prices? How is this possible that you negotiated three times what Medicare pays for the exact same rate," or two times or four times. So that's how employers are using it, to become more sophisticated shoppers of care.

They're also using it to design their benefits differently. They want to find the best quality at the best price, and think about how are they going to incentivize their employees to go there versus going to a place that's the highest price and worst quality.

SEP employers – employers, you know, they're the biggest purchaser of health care in the United States. So they can apply pressure on the entire supply chain – which is their insurance companies, the benefit consultants, the hospitals, the physician groups, really, really everyone. But they didn't have readily-accessible, usable data to have those conversations; so really, the tail was wagging the dog for decades. Now that's changing because they have this information.

We also see academics using it. We'd love to have more academics just writing papers and doing all these comparisons. Journalists have certainly used it. We've had policymakers using it, as Maureen mentioned. Benefit consultants have been a really big user of this information because employers oftentimes hire benefit consultants to help them and advise them as their trusted advisor on who to contract with in PBM, their pharmacy benefit manager; their providers; their on-site clinic; the disease management; wellness services.

So they have consultants to help them out with a lot of different types of services. These benefit consultants have been operating also in the dark, and it becomes a sales and marketing game that's going away. So we see the best benefit consultants in the country using Sage Transparency and making recommendations that are evidence-based.

Also, we're seeing hospitals use this. A lot of hospitals want to know how they stack up against their peers. This information wasn't readily-available to them. They didn't know how they stacked up on any of these measures – price, quality, and cost – before. So that's been really interesting. We've seen a hospital system go into a market that was really high-priced because they didn't have a lot of competition to create competition. They're like, "Hey, we can do better than that. We're building here."

We have seen independent providers go, "Oh my gosh, you're paying the hospital this much? Pay me! Our prices are a lot better. Our quality is good." And nobody really knew because the largest hospital systems in most states are the drivers of high health costs, and we can see that now. You can just pick state, put every hospital in the state on a graph and see who's the highest-priced – even within a health system. Some health systems are national. You can put Ascension Health or HCA or any of these really big health systems and say, "How come your prices vary so much across states? What's happening here?"

You can look at even a contained health system within one state. They may have 16-20 hospitals; and you're like, "Why are your prices so variable within the same state, within the same health system?" Then you go to the insurance companies and go, "Why did you negotiate such variable hospital prices?" And that's because the purchasers have no line of sight. These organizations had signed contracts with each other and included gag clauses in these contracts that said neither party is allowed to share what the negotiated price was. So employers and people are just paying for it, and then the tail wagging the dog here was standard of care.

But as Maureen mentioned, we need policy to address that – that anti-competitive contract language, the Federal Government and the State of Indiana have banned gag clauses. That's great, but there are other clauses that need to be banned as well so that we can develop tiered networks and steer people to best quality at best price. So I do think that there are a lot of opportunities here.


Okay, great. Where I wanted to wrap up was by talking about what comes next. This question might be best for Guru and Evelyn – at least start with Guru and Evelyn. Do you have plans to update these two Web tools? Might new data improve their usefulness?


Speaking for the Hospital Cost Tool, we are working with NASHP to update the underlying data to include more recent years of hospital cost reports; specifically, the 2020 and 2021 data. We're also making charts to include additional cost metrics that will be helpful for the state officials to better understand cost drivers.

We are planning to launch the version 2.0 of Hospital Cost Tool in the fall. So we certainly invite you, the listeners, to let us know how you are using the current tool; what's working well; and what can be improved.


I can speak to the upcoming developments for Sage Transparency. At this point in time, we have the Phase 2 or the Version 2 of Sage Transparency that is live; and we have a plan for the Version 3, which the first enhanced version of this space is planned to go live in December. It includes data and measures on this data for ambulatory care and incentivized prices. I think Gloria can add more data after me on that.

There will be some new measures and new dashboards included with this current version, and also there may be upgrades to existing dashboards. We are talking at this point in time about the private insurance data and how we could use that data for presenting some measures which would be useful. Gloria already mentioned about some of those things in earlier discussions.

Apart from all of this, we have a continued upgrade that happens. This is because of the new datasets that keep coming in from these sources. So we currently have a plan for updating with the new datasets until the end of 2024. So there is a road map, and there's sort of work that we have planned so far.


Gloria and Maureen, I want to hear if there's anything else you want to add in terms of ways to improve these tools or updates to these tools that we can expect. But then I'm also curious how you plan on using the data to spur policy change. I just wanted to make sure there wasn't anything we've left on the table in terms of how the data might spur action.


So just to follow up on what Guru mentioned regarding upcoming updates, we plan to add from the RAND 4.0 data ambulatory surgical center information – so 4,100 ambulatory surgical centers. That will be a whole new dataset – have to figure out how to integrate all that.

RAND 4.0 also has standardized prices. So in addition to showing hospital prices as a percent of Medicare, there are other columns that are shown as standardized prices. So you'll be able to toggle. Like do I want to see the prices as Medicare prices, or do I want to see them as standardized prices. This is a criticism of some hospitals – that, hey, that hospital is showing a much lower percent of Medicare and that's because they're an academic medical center. They're receiving a lot of what we call "dish payments" or medical education payments. So this way, you can kind of compare prices apples to apples without all those Medicare adjustments.

The insurance data is really exciting. We're anxiously awaiting to hear from the data scientists, such as Evelyn, when and if it's going to be usable and how much of it's going to be usable.

We aim to update Sage Transparency quarterly, as Guru mentioned, for the next two years and have the funding to do so. That's important because we want -- when Maureen updates the Hospital Cost Tool in October, then we'll capture that in our December rollout. CMS is doing quarterly updates; they're on their own schedule. Turquoise Health, as I mentioned, has daily updates; but we only update it quarterly. Quantros has the Hospital Quality Tool. They do updates quarterly, so we pick up theirs as well. RAND, while they're not doing updates, RAND 5.0 is already in the works. So the foundation is being laid for garnering claims data for RAND 5.0; and when that does release, we'll add it in.


Maureen, anything else that you'd like to flag in terms of what's next for the Hospital Cost Tool?


Evelyn did an excellent job of sort of sharing some of the updates that we're going to be doing to the actual tool. Our hope is that there will be different users ahead of the next legislative session. The 2022-2023 legislative session is going to be big for all states. The last legislative session was smaller; but this is a budget year for if not all, most states. So we've already been engaged by a number of different state officials who want to understand more about our model policies and, in so doing, are asking about data to help them make the case. Is this something that our states should be pursing? Is this something that is where we should be spending political capital, or should we be focused on some other issue?

Those are really good questions to ask, and we really believe that the Hospital Cost Tool can help guide some of that. So that's already started, and we expect that to continue to happen in the next four to six-eight months as the legislative sessions kick off. There's the preparation period, there's the kickoff period, and then there's the duration. So we believe that the Hospital Cost Tool can help throughout that experience.


Thank you.

Thank you so much for giving your time. I've really enjoyed the conversation, and I've learned a lot.


Thank you for the opportunity.


Thank you.


Thank you.


Thank you.


Thanks again to my guests...Gloria Sachdev, Maureen Hensley-Quinn, Evelyn Lee, and Guru Rasukonda. A full transcript of our conversation is available on the blog post associated with this episode, which you can find at Links to both of the tools we discussed in the episode, Sage Transparency and the Hospital Cost Tool, are included on that blog post and in the show notes for this episode.

As always, thank you for listening to another episode of On the Evidence, the Mathematica podcast. There are a few ways you can stay up-to-date on future episodes. You can subscribe at Goodpods, Apple Podcasts, Spotify, YouTube, or wherever else you listen to podcasts. You can also follow us on Twitter. I'm at JBWogan. Mathematica is at MathematicaNow.

Show notes

Explore Sage Transparency, a free online tool developed by the Employers’ Forum of Indiana and Mathematica. The tool draws on data from the RAND 4.0 Hospital Price Transparency Study, Centers for Medicare & Medicaid Services, and other health databases to show the real prices that employers pay for health care across the country.

Explore the Hospital Cost Tool, a dashboard designed by the National Academy for State Health Policy and Mathematica, which helps bridge the information gaps on costs and pricing.

About the Author

J.B. Wogan

J.B. Wogan

Senior Strategic Communications Specialist
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