Using standardized Transparency in Coverage data across 16 states, we analyze how Aetna’s negotiated Exchange rates, network expansion, and premium growth compared to peers like UnitedHealthcare and Cigna. The data show Aetna paying materially higher rates—particularly for inpatient services—placing it at a structural disadvantage in the price-sensitive ACA marketplace and helping explain its 2026 exit.

CMS was explicit about the goals of TiC 2.0: reduce duplication, normalize file structure, and make machine-readable files more usable at scale. One month in, we’re seeing meaningful progress—and some familiar patterns of “compliance in name only.” But as always with TiC, the details matter. In this edition of MRF Processing Notes, I’ll break down the adoption of 2.0 and where it’s helping (or hurting) the cause of usable transparency data. 

Turning messy payer and plan names into standardized, trustworthy data for healthcare price transparency.

Commercial healthcare prices often appear chaotic in dollar terms, but a clearer pattern emerges when rates are benchmarked to Medicare. This post explains why Medicare remains the most reliable reference point for interpreting price transparency data, how benchmarking helps normalize variation across service lines and markets, and where differences in commercial rates reflect meaningful signals rather than noise.

The Trump administration’s most recent announcements on healthcare affordability are full of transparency actions—mandating that all providers and health insurers meaningfully post their pricing.

In this analysis, we test whether aggregating Florida Blue’s machine-readable files across 18 months meaningfully closes known data gaps.

CMS’s latest proposed update to Transparency in Coverage signals a meaningful shift—from publishing more data to making price transparency data actually usable.

How we scaled MCP from a local prototype to two production-grade servers, tackling key challenges in authentication, architecture, and schema design to enable secure LLM access to price transparency data.

Learn why percent-of-charges contracts can’t be benchmarked with payer files alone—and how combining payer TiC, hospital MRFs, and claims reveals true market cost.

Serif Health successfully completed its SOC 2 Type II audit with Advantage Partners, supported by Vanta’s automated compliance platform—reinforcing its commitment to secure, reliable healthcare data infrastructure.

Access complete hospital and clinic fee schedules instantly with Serif Health’s new Fee Schedule Lookup in Signal. Explore provider contracts, codes, and rate benchmarks in one click.

Learn how Serif Health uses AI and the Model Context Protocol (MCP) to make healthcare price transparency data more accessible, actionable, and secure—unlocking new ways to explore cost and network insights.

Custom (CSTM) and Local (LOCAL) codes often contain critical negotiated rate data that many vendors ignore. Learn how Serif Health normalizes these payer-specific codes to ensure your price transparency analytics are complete and accurate.

The new Transparency in Coverage (TiC) Schema 2.0 introduces key updates to provider identification, DRG pricing, plan sponsor fields, and out-of-network thresholds—while raising new questions about enforcement, validator tools, and custom code use.

See Serif Health’s live network quality scoring across 200+ payers, with monthly updates on transparency data completeness and reliability.

Discounts aren’t enough. This blog breaks down how employers can move beyond percent-of-billed charge arrangements and use cost intelligence to evaluate networks, steer care, and design smarter benefit strategies.

How Serif Health Standardizes Anesthesia Reimbursement Across Payers

Employers and their advisors are redefining benefits strategy with a new benchmark: Total Cost of Care. See how real-time data helps forecast benefits spend and guide smarter healthcare decisions.

What can we learn from price transparency data for physician-administered drugs? New data on Keytruda highlights wide variation in commercial reimbursement: across states, by payer, and based on provider characteristics like place of service. A single treatment for this high-cost infusion can range from under $12,000 to over $30,000, depending on where it’s given, which payer is involved, and how it’s billed.

Serif Health recently submitted both an independent and joint coalition response to the federal government’s Request for Information on prescription drug price transparency. Drawing on our national TiC data from June 2025, we demonstrate that infrastructure already exists and offer clear recommendations to ensure that negotiated drug prices become fully visible, comparable, and actionable.

Healthcare markets fail because prices are hidden, but Serif Health is building transparency tools to make pricing visible and actionable. By creating the most comprehensive database of negotiated rates, we're helping stakeholders understand value and improve patient access across the US healthcare system

The behavioral health market is experiencing unprecedented growth and transformation. In this article, we analyze behavioral health trends and reimbursement rates using 2025 machine-readable files, with examples from real payer-MSO relationships.

Price transparency files are incredibly valuable for finding up-to-date pricing on hospital reimbursement, but you need a partner who knows what they are doing.

Following February’s Executive Order, CMS, the Labor Department, and the Treasury Department recently dropped new guidance that pushes us further toward standardization, enforcement, and real usability of price transparency data. At Serif Health, we’ve always believed transparency data only matters if it can be trusted, compared, and acted upon. Recent updates show the federal government is continuing to lean in toward these goals.

Uncovering key contracting terms from machine readable files by joining to CMS datasets.

This blog post answers a big what-if question: what if the Transparency In Coverage laws were actually enforced and penalties were administered to the entities that are either not posting machine readable files, or are posting files which are obviously incomplete? How financially impacted would those entities be? Read on to see the high level math, as well as our quarterly lay-of-MRF-land with this installment of “MRF Processing Notes”.‍

Example insights you can draw from comparing machine readable file data over time.

In a prior post, we covered the Serif Health approaches for zombie rate filtering, and the volume of data impacted by different filtering approaches. Our question for this blog post is: what impact does all this data in the raw file have on the resulting distributions, and where do distributions land when the data is removed?

Designed for third-party administrators (TPAs) and health plans, this API can transform how you deliver provider and facility search experiences to your members.

Your personal analyst for working through price transparency data

The Hospital Price Transparency “v2” Schema rolled out in July of 2024 had the potential to greatly increase data accessibility and standardization. We’ve been implementing automated data collection pipelines on the v2 schema, and are excited to report that we do indeed see significant improvements in data quality and availability. But as with any rule, there’s plenty of rule breakers out there. Read on to see how HPT v2 changes the landscape for hospital data gathering, what’s working, and where the hard parts still are.

Some learnings from spending years inside payers’ machine readable files with our customers.

Payer machine-readable files (MRFs) are filled with irrelevant "zombie rates"—like a mental health provider billing for a knee replacement. Learn how we use claims data and taxonomy mapping to filter out these misleading records, streamlining data for faster, more accurate search results.

We are excited to share some of the latest price transparency use cases. Learn more about how our customers - from health systems and provider groups to employers and TPAs - are utilizing Serif Health's archived price transparency data to develop powerful historical analysis and insights.

The latest addition to Serif Health’s platform, Signal, allows users to compare contracts across providers for easy, flexible benchmarking

It’s been 25 days since the ‘V2 Schema’ for Hospital Price Transparency took effect in the market. So, is the data better? Is the workflow simpler? We’ve been looking into the new text and MRF files posted by many different hospitals, and we like what we’re seeing. So much so that we’re on a quest to gather all the hospital data…again. Read on for an early look at our experience with Hospital Price Transparency V2 MRF Processing and why we're excited to be gathering this data to complement our industry-leading portfolio of TiC files.

Our June MRF Processing Notes blog focuses on a new behavior we are seeing with increasing consistency from UHC, Anthem, and various other BCBS Entities - rate limiting and/or blocking access to machine readable files. Read on for details.

In our previous post on our monthly data ingestion process, we discussed what it takes to keep all of the Table of Contents (ToC) up to date across the varying Payors. But now that we have them, what exactly do we do with them? How do we go from a ToC file to defining what constitutes a PPO network and locating its associated files.

Signal’s latest report enables your practice to easily discover and compare contracted rates across a customized set of provider organizations.

A set of examples for non-standard arrangements like service bundles, capitation agreements, and case rates present in the payer price transparency data.

The Serif Health data team is constantly investigating the technical nuances of the price transparency data. In this post, we explore the utility of the negotiated type field across payers and implications for Serif Health customers and users of the transparency data.

Serif Health’s platform, Signal, makes it easy to factor in actual contracted reimbursement data into your expansion roadmap.

As self-funded employers increasingly grapple with their role as fiduciaries for their employees’ healthcare, there is a unique opportunity to use price transparency data to drive substantial cost savings and improve employee healthcare. See how Serif Health has been working with health plans and self-funded employers to utilize price transparency data more effectively to build preferred provider networks and steer patients to low cost, high quality care on a consistent basis.

This March edition of MRF Processing Notes explores a Swiss Cheese MRF from Florida Blue's Blue Options PPO. There's some meat to the file, so it retains the shell of a compliant MRF, but otherwise has so many holes you can’t get the complete pricing picture for entities that matter. Interestingly, the gaps also shift month over month, suggesting with some nonintuitive analysis, it still might be possible to get useful price intelligence from the data.

Join us for a tale from MRF land about maintaining MRF indexes.

Cut through the noise with our new real-time rate search tool

2024 comes with another big price transparency development - mandated prescription drug price disclosures. We’ve been keeping a close eye on the shifting disclosure timelines and enforcement ‘safe harbor’ rules regarding prescription drugs. The 1/1/24 deadline took a lot of folks by surprise, but not Serif Health - we’ve actively been refactoring our ingestion and parsing pipelines to handle this schema, so when 1/1 hit, we could easily leverage our existing ingestion and conversion pipelines to deliver prescription drug data in a preprocessed, normalized form to our customers. Read on for an analysis of postings from OptumRx and see which pharmacies rates are surprisingly non-competitive.

Serif Health's December product updates and new offerings for self-funded employers and TPAs

Generally good news on macro posting and processing trends to report out this quarter. Many payers we’d highlighted for failing to post have returned to posting monthly, and we’ve seen meaningful improvements in posting size and EIN/NPI count increases came from payers like Aetna, Ambetter, Multiplan, and Priority Health. Of course, it wouldn’t be a processing notes post without some lowlights and public calling-outing - Optum and Florida Blue take the stage this month. Read on for details.

A quick look at how robust current provider networks are for mental healthcare using private insurance's machine readable files.

This month, we’ll demonstrate another use case for price transparency machine readable file (MRF) data by geographically mapping and comparing negotiated rates. You don't have to be a payer to pull this off - Serif Health has built tools that make getting clean data for analyses like this simple and cost effective.

So here we go, on our first blog really getting into the meat of MRF pricing info. We at Serif Health frequently get questions about hospital MRFs and how the quality compares to payer MRFs. Which data set is more trustworthy? Which should you use when? Is this easy to do? Is it ‘apples to apples’? Read on and find out.

HealthSparq’s MRF portal allows payers to non-transparently forward date, backdate, and edit TiC postings without disclosure. Plus, we show you how to deal with BCBS of Minnesota's Imperva firewall which is improperly blocking machine access to their indexes.

We are excited to announce the launch of Serif Health’s new and improved website: www.serifhealth.com! Enjoy a bolder, sleeker site design and user experience to better understand Serif Health, explore our enhanced MRF data product suite, and learn more about our mission to power price transparency in healthcare!

We’re back for another round of MRF processing notes for April. For this month, we’ll go with a good, bad, and ugly approach. The good - some big payers posted more data (a LOT more). The bad - several BCBS entities didn't post or posted indexes full of links with March date codes. The ugly - Highmark.

Serif Health was launched in November 2021 to improve US healthcare pricing. We (founders Matt and Rafiq) had existing healthcare and pricing backgrounds, and wanted to put that experience to use in service of making healthcare costs more transparent and affordable. We believe that better market analytics and intelligence, especially for smaller players in healthcare, can reduce the price disparities that exist today and better align incentives to help patients get the right care at a fair price.

We are proud to announce that we secured $2.5MM in venture funding, with backers including 1984 Ventures, Olive Tree Capital, Rebel Fund, and YC. Our angel investors include engineering and product executives from Dropbox, Airbnb, Pilot, Webflow, and more. We’re proud of our progress and incredibly thrilled to have the support and backing of an incredible investor team.

‍The CMS fine for Northside Hospital should be a major wakeup call to hospital systems around the country who have delayed compliance. It’s also an incentive for all insurance plans to post their in-network negotiated rate files by July 1 to stay in compliance with the upcoming effective date for the Transparency in Compliance act. 

Today marks a MAJOR breakthrough in healthcare, but it has nothing to do with cutting edge technology, historic procedures or drug approval. Yet the advancement has the potential to impact care for patients around the country. So what is this massive breakthrough? Simply put - payer network reimbursement files are now available to the public, cataloging every negotiated rate between every payer and provider in the country.

Serif Health is excited to announce that we have achieved nationwide coverage of payer pricing data, available via our analytics portal or our new documented REST API. That’s right, we have price data coverage for insurance payers in every state in the US, including Hawaii and Alaska. The API is convenient, lighting fast, and scalable up to millions of queries per month - contact us for a test API key today! 

We get lots of outreach from folks who'd like to spot check an individual rate for price transparency purposes. You've probably heard there’s these Machine Readable Files out there that have this information. So, how do you get to the specific data you need? Let’s walk down the chain together, and learn about the different components of MRF postings (and health insurance networks) along the way.

Having trouble with Humana, Cigna, or Anthem MRF ingestion? Confused by the rates and place of service codes you're seeing in the file? In this post, we’ll lay out some of the key learnings and gotchas from our past few months of MRF processing, so you and your team don’t have to learn the hard way (like we did). ‍

Hi folks! We’re back from HLTH, where the interest and excitement around the payer price transparency data was palpable. We wanted to give folks a November update on our MRF processing tips and tricks post... the TL;DR is that payers were responsive to feedback from MRF data processors like ourselves, and the MRF data is getting (slightly) easier to work with and understand. Read on for details!

Serif Health continues to examine and refine data to identify quality issues, reduce noise, and ensure our customers can make great decisions with trustworthy information. Key learnings and highlights for December: Taxonomy filtering is now available in our price dashboard and APIs, we found schema misuse leading to millions of ambiguous data points, and erroneous modifiers and TINs are present in various payer MRFs. Read on for more details.

If you’re paying attention to healthcare news, you probably saw the recent posting in Fierce Healthcare about a report from Georgetown University stating that “many of the data files are far too large to access without help from a supercomputer.”We’re happy to report that simply is not accurate. You don’t need a supercomputer, you just need Serif Health. We’ve custom engineered a data pipeline to work with and extract data from the most complex payer files in the country quickly and cost-effectively, and our extractor can run on any hardware - even a laptop.

This month, Serif Health digs deeper into UnitedHealthcare's MRF files posted since last August. While UHC 'complies' with the price transparency rules with their postings, UnitedHealthcare is systematically reducing the data in those postings, and for a common use case, 70% fewer prices can be located in their files than were accessible in August. This reduction in data volume means in-network providers' rates can no longer be located in the MRF, and this is happening in every nationwide network file posted by UHC. If these data reductions continue, UHC TiC postings will become effectively useless. Read on for more!