When price transparency legislation went into effect in January 2021, the goal was to empower patients to make informed healthcare decisions. With cost information about healthcare procedures and services at their fingertips, consumers could compare prices across different providers and make the most cost-effective decision for themselves. But this rapid introduction of historically unavailable pricing information also gave health plans an advantage. By accessing this publically-available data, health plan leaders gain the ability to see where they stand in a highly competitive market. That kind of intelligence has wide-ranging impacts from negotiating better provider contracts to advancing top priorities like offering affordable and accessible care. The catch? The enormous machine readable files in which this data is delivered is anything but transparent. Working with our health plan customers, we’ve seen firsthand the challenges that come with this influx of complex, new data but also the opportunities that arise once health plans leverage data analytics to transform these files into actionable intelligence. Keep reading to learn the three biggest challenges and opportunities of price transparency data for health plans. Challenges with Price Transparency Data 1. Information Accuracy Carriers are responsible for providing their pricing information, but who’s checking to make sure it is accurate? Verifying the accuracy of pricing data for just one carrier can be like finding a needle-in-a-haystack, not to mention multiplying this task hundreds and hundreds of times. A comparative analysis of a given price requires enriching the price transparency data with supplemental provider data and COB data if available. Once providers are unified across datasets, it is possible to link group practices and health systems and validate provider fees. This task is a necessary step to build an accurate, data-backed picture of a health plan’s competitive landscape, but it’s also resource-intensive. It’s why many health plans are turning to a trusted data management and analytics partner to give them confidence that they are working with the best possible figures. 2. Complex Data Even if health plan teams know they are working with accurate numbers, they still face a trifecta of data hurdles with these machine-readable files. First, there’s simply the files’ massive size. Because of the complex contracting that payers are involved in, payer data is much more complex and bigger than hospital systems. To put it in perspective, the number of rates presented in these files are 1000x larger than the total number of pages on Wikipedia. Second, there’s no standardization, requiring health plans to aggregate and normalize all of these massive files into a consistent dataset. For example, information on one plan could be spread across multiple files or one file could contain multiple rate In addition, generic naming conventions create difficulty in understanding which product and network relates to which file. In order to even begin analysis, health plans would need to standardize each competitor’s data. Then they would have to categorize that data and enrich it with other available provider data. Handling the size and translating this kind of data requires data processing and analytics expertise, along with technology that is often beyond a health plan’s resources. 3. Incomplete Information We’ve already talked about how carriers could provide inaccurate information, but there’s also potential for them to leave gaps. Health plan teams could discover incomplete information in the price transparency files. In the example below, the internal provider group ID came with no corresponding lookup information and nests of thousands of NPI’s. We are therefore presented with very little information about this provider group along with every rate for the provider group ID mapped to all of these providers, regardless of the fact that many of the individual providers do not fulfill the type of service in question. Filling in these gaps again requires standardizing, normalizing, and linking the price transparency data with other provider data. From this, health plan teams can work from a complete picture of competitor fees across inpatient, outpatient, and professional service categories. Opportunities with Price Transparency Data Despite its obstacles, the machine-readable files present health plans with unprecedented visibility into a highly competitive market. Making sense of these figures affords health plans three competitive advantages: 1. Access to Benchmarks and Reporting Data Not Currently Being Utilized by Competitors Detangling the data gives health plan analytic teams the ability to compare their plan’s pricing, networks, and rate file completeness with other plans. Imagine drilling down into price variance across different services, price bundles, and locations. With this intelligence, health plan teams gain insight into where their offerings are competitive, plus where adjustments may need to be made. 2. Strengthened Negotiating Power in Provider Contracting Efforts When it comes to providers, the price transparency data allows health plan analytics teams to see the prices providers are offering competitors, specifically which providers are offering competitors lower prices. This kind of insight gives health plans the upper hand when it comes to securing a desired contract. 3. Develop Strategies to Win and Retain Business with Employer Clients Price transparency insights can also give health plans an advantage in acquiring and retaining employer clients. Price comparison allows health plans to understand which of their employer clients may be at risk based on pricing, and adjust offerings to retain that business. They also gain visibility into new employers who would be better served by their health plan offerings. From this insight, a health plan can build business strategies to better retain and attain new business.   Do you want to learn more about using price transparency data to gain a competitive edge? Check out Certilytics’ approach that is helping leading health plans succeed.

Transparency was the goal of the government’s 2021 requirement for healthcare carriers to publicly supply the costs of their services and procedures. But many health plan teams who’ve accessed this pricing data quickly feel overwhelmed when trying to make sense of these enormous and tangled machine-readable files. It’s why many health plans have turned to trusted data partners like Certilytics to get the actionable insights they need – from rate comparisons to provider reimbursement analysis. Through our experience working with these health plan partners, we’ve put together a recipe health plans should use to transform these dense files into actionable competitive intelligence. Step One: Wrangle the Price Transparency Data Files The massive size of the machine-readable files are the first hurdle health plans must face with price transparency data. While hospital files tend to be easier to digest and consume, they are sparse. Payer data, on the other hand, takes up a larger portion of the price transparency files and they come with much greater complexity due to the amount of contracting payers are involved in. Put together, the files are enormous, with rates in the trillions. For example, the number of rates presented in these files are 1000x larger than the total number of pages on Wikipedia. Simply ingesting the pricing information necessary to gain competitive insights is a major lift for health plans, and requires a data analytics platform capable of consuming terabytes of data. Health plans should identify a trusted data and analytics partners who has the capacity to aggregate massive volumes of data. The partner will eliminate this obstacle by not only wrangling the data together, but cleansing it to get actionable insights. Step Two: Normalize and Enrich the Data In addition to the massive size of the data, inaccuracies, incomplete information, and incongruities within the files make simply collecting price transparency data insufficient. Why? Even with the data aggregated, health plan partners struggle to easily compare rates because providers are buried beneath an inconsistent tangle of misaligned labels, naming conventions, and different organizational structures across carriers. For example, information on one plan could be spread across multiple files, or one file could contain multiple rates. Multiple providers could be associated with one national plan that has filed their information nationally, making a rate comparison in a local market time consuming. On top of that, fees must be verified for accuracy before any rate comparison occurs because carriers are supplying information about their prices themselves. In order to have a complete picture of the data, a health plan should enlist a data partner to validate the prices, and fill in these gaps. First, a data partner can normalize all the files into a consistent data layer and categorize them. This processing of standardizing the price transparency language is the first step a health plan needs to take in order to understand its competitive landscape. Once all the files are consistent, linking the MRF files to supplemental provider data will unify providers across data sets. This begins to bring the competitor picture into focus because it links group practices and health systems together, helping isolate and fill any gaps as well as verify that carriers have supplied accurate information about their files. For example, Certilytics’ extensive provider database of approximately 7 million providers helped pinpoint a price discrepancy from one provider. Professional Rates An efficient data partner will also link the price transparency data with supplemental provider datasets including COB data. This not only further verifies prices and fills in some holes, but allows for a robust rate and utilization comparison across competitors. Step Three: Generate Reports and Analysis to Gain a Competitive Edge Once the data is cleansed and ready for analysis, a data partner can also save a health plan time and resources by supplying insights through intuitive reports and dashboards. With access to a powerful and flexible data platform, health plan teams can find answers and explore the massive data efficiently and quickly through comprehensive, curated views of competitor fee schedules and provider reimbursement fees. For example, Certilytics supplied our health plan customers with both a summary competitor network fee schedules across inpatient, outpatient, and professional service categories as well as access to the source MRF datasets. The Certilytics’ reports include the client’s reimbursement benchmarked against Medicare fees where possible. Outpatient Rates With these insights, health plans can gain clear, unprecedented visibility into where they stand in a highly competitive market. Then, they can use that intelligence to support provider contracting efforts, improve the overall value of their plan, and accelerate customer growth and retention.   How can a health plan use price transparency data and insights to advance their goals? Check out our next blog to see three ways health plans have turned competitive intelligence into a competitive advantage.

The new price transparency regulations promise unprecedented competitive intelligence for health plans, but the machine-readable files in which they are packaged come with some major data obstacles. With the help of an experienced analytics partner, health plans can access actionable data insights from these files that give their teams an edge in a highly competitive market. What are some of the most effective ways health plans can use this intelligence? Here are three ways our health plan partners leveraged price transparency data insights from Certilytics’ data analytics platform and turned their competitive intelligence into a competitive advantage. Use Case #1: Access to Competitive Pricing Analysis One of our health plan customers wanted to use the price transparency data to compare their rates with a competitor. This Midwest-based health plan  wanted to identify trends and spot price variations so they could make impactful rate adjustments. But once they gained accessed to the files, they quickly realized that drilling down into price variance across different services, price bundles, and locations was going to require data expertise. Why? The files are massive, requiring a technological platform capable of ingesting terabytes of data. In addition, there’s no standardization in the files. For example, information on one plan could be spread across multiple files or one file could contain multiple rates.   In order to even begin a pricing comparison, the health plan analytic teams needed to overcome the technological hurdle of consuming massive amounts of data and de-tangle the data enough to understand which product and network related to which file. Certilytics’ data analytics platform not only aggregated the enormous amount of data, but normalized it into one consistent layer and enriched it with supplemental provider and COB data. This linked group practices and health systems together in order to compare the fees the carriers supplied in the price transparency files to Certilytics’ and COB’s reference database of millions of providers. This extra step validated the accuracy of the figures supplied by the carriers so that the health plan could be sure they were working from precise numbers. Once the data was validated, cleansed, and ready for analysis, our platform also saved the health plan time and resources by supplying insights through intuitive reports and dashboards. With quick, reliable insights at their fingertips, the health plan teams explored a summary of competitor network fee schedules across inpatient, outpatient, and professional service categories as well as accessed the source MRF datasets. Plus, the reports include Medicare and the client’s reimbursement levels for straightforward bench-marking.   In the end, Certilytics’ data insights helped the health plan analytic teams compare their plan’s pricing, networks, and rate file completeness with multiple other plans, broadening the scope of their initial analysis and informing their pricing strategies. Use Case #2: Strengthen Negotiating Power in Provider Contracting Efforts. For another Midwest-based health plan partner, the price transparency files gave them the unprecedented opportunity to compare provider reimbursement rates, specifically which providers were offering their competitors lower prices. In this case, the health plan team wanted to analyze the fees from a provider in a rural hospital. But again, the enormity of the files and their lack of standardization made drilling down to this one provider much like finding a needle in a haystack. Within the files, multiple providers could be associated with one national plan that has filed their information nationally, making a rate comparison in a local market time consuming. Incomplete information also existed in the price transparency files. In the example below, the internal provider group ID came with no corresponding lookup information and with thousands of nested NPI’s. In this instance, they were therefore presented with very little information about this provider group and must grapple with the fact that every rate for the provider group ID is mapped to multiple providers, regardless of the fact that many of the individual providers don’t fulfill the type of service in question. On top of a lack of consistency in the provided rates, there was no comparison to Medicare, making any basis for a reasonable assessment of one reimbursement fee impossible from the raw data. Certilytics’ aggregated, standardized, cleansed and linked the files to reference databases to create the most holistic cost analysis possible. By supplementing the data with Certilytics’ provider database and COB’s database, Certilytics’ platform caught a price discrepancy that would’ve thrown off the health plan’s analysis. The result? The health plan now had the ability to drill down to one provider in a rural hospital and analyze the reimbursement fees. Professional Rates Using this insight, health plan leaders acquired the ability to secure a more desired contract with an in-demand provider. Use Case #3: Develop Strategies to Win and Retain Business with Employer Clients. For our third use case, a Southwest-based health plan partner sought a competitive advantage from the price transparency files when it came to acquiring and retaining employer clients in a specific market. They were looking for different answers from the data, but they ran into the same obstacles as our other health plan partners. Without the help of Certilytics’ data platform, a pricing analysis of rate structures and provider reimbursement fees wasn’t possible. Provider lookup information was incomplete or scattered across multiple files. The same was true for competitor rates, with information on one plan spread across multiple files or one file containing multiple rates. National plans that filed nationally were difficult to analyze on a local level. And on top of the sheer volume of the data, the accuracy of the numbers remained a concern without a reference database like Certilytics’ provider database, which contains the fee schedules of millions of providers, to validate the figures. Certilytics’ platform performed the heavy lifting of aggregating, standardizing, cleansing, and validating the data to make a price comparative analysis possible. The health plan could then explore a summary of competitor network fee schedules across inpatient, outpatient, and professional service categories, access the source MRF datasets, and benchmark their reimbursement levels against Medicare. In the end, this health plan understood which of their employer clients may be at risk based on pricing, and could adjust offerings to retain that business. They also gained insight into new employers in that local market who would be better served by their health plan offerings.   Ready to see how you could turn competitive intelligence into your next competitive edge? Meet with our team to see how you can leverage your price transparency insights.