Publications, press releases, and news from the Simple Healthcare team — peer-reviewed research, white papers, and policy analysis on healthcare price transparency.
28 resources
Co-authored by Simple Healthcare CEO David Muhlestein, this National Academy of Medicine discussion paper examines how misaligned financial incentives contribute to rising costs, fragmented care, and poor health outcomes. It identifies three systemic drivers of misalignment and 12 potential policy levers for creating a more affordable, accountable, and outcomes-focused health system.
On April 28, 2026, Simple Healthcare presented to the Senate Finance Committee Office Hours on how price transparency data can be used to reduce healthcare spending for the commercial population. Click below to download the slides.
The links below present a collection of state-specific analysis of healthcare prices using the data released under the Hospital Price Transparency and Transparency in Coverage rules. The analysis highlights variation in healthcare prices across insurers and providers for each state. The results of the analyses consistently show that prices for the same service can vary substantially—often by thousands of dollars—depending on the insurance plan or provider chosen, even within the same market. By making these differences visible, the state level two-pagers aim to equip employers and other stakeholders with insights that were previously difficult to access. In addition to documenting price variation, each state profile outlines practical implications for employer decision-making, including opportunities to reduce healthcare spending through smarter insurance and provider selection. The analyses also highlight key limitations in current transparency data—such as incomplete reporting, lack of utilization information, and inconsistent formats—that constrain its full potential. Together, these state two-pagers provide a consistent, data-driven foundation for understanding local healthcare markets while also pointing toward policy and data improvements needed to make price transparency more actionable and impactful. We could not analyze healthcare prices for Maryland due to lack of data. This work is funded by the Peterson Center on Healthcare (PCH). We are thankful for their support. Click on each state to review the PDF. Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming
In a new article published in the American Journal of Managed Care: Population Health, Equity & Outcomes, we examine the significant variation in healthcare prices across providers and payers—and what it means for lowering costs in the U.S. healthcare system. Using examples from knee replacement surgery in New York City, the article highlights how prices for the same procedure can vary dramatically depending on the hospital and insurer. These disparities illustrate both the scale of inefficiency in current pricing structures and the opportunity to reduce costs through better use of price transparency data. While transparency has improved access to pricing information, the article emphasizes that information alone is not enough. The central challenge is making this data actionable—ensuring it reaches the right stakeholders in a usable form at the right time to inform real-world decisions.
This article, published in The American Journal of Managed Care explores how healthcare price transparency is only the first step toward reducing costs—and why simply making data available is not enough. It highlights how employers, payers, and innovators are increasingly leveraging detailed pricing data to drive actionable strategies, such as steering patients to high-value providers, improving contracting decisions, and redesigning benefits. While transparency can enable more informed decision-making and foster competition, its real impact depends on how effectively stakeholders translate data into behavior change and system-level interventions that lower spending and improve value.
In February 2026, Simple Healthcare submitted a comment letter on the proposed updates to the Transparency in Coverage (TiC) rule. Based on our extensive experience analyzing TiC data, we strongly support efforts to improve data quality and usability, while highlighting key structural issues such as “ghost rates,” incomplete reporting, inconsistent network definitions, and file formats that limit real-world use. We recommend adding provider-group level procedure volume, combining claims-based utilization with specialty taxonomy to reduce ghost rates, improving bundled payment disclosure, standardizing network identifiers, reporting average paid amounts, and requiring relational (rectangular) file formats instead of nested JSON. These changes would make TiC data more accurate, accessible, and actionable for employers, researchers, and policymakers.
Simple Healthcare’s white paper provides technical recommendations to help strengthen the proposed Transparency in Coverage rule from the Centers for Medicare & Medicaid Services by improving how price transparency data is structured, reported, and filtered. Drawing on empirical analysis of current TiC data, the paper outlines 17 practical, implementation-ready recommendations across ghost rate filtering, utilization reporting, bundled payment disclosure, and machine-readable file architecture. The goal is to help ensure transparency data is accurate, interpretable, and usable for real-world decision-making by employers, researchers, and policymakers, while remaining feasible for payer implementation using data already maintained within existing systems. The analysis was developed by Simple Healthcare to support more effective use of transparency data in purchasing, policy analysis, and market oversight
Simple Healthcare has released a press release announcing its latest white paper focused on improving the usability and real-world impact of Transparency in Coverage data. The release highlights how specific technical implementation decisions within the proposed rule from the Centers for Medicare & Medicaid Services could determine whether price transparency data can be effectively used by employers, researchers, and policymakers. The press release summarizes the paper’s core findings and outlines 17 practical, implementation-ready recommendations across ghost rate filtering, utilization reporting, bundled payment reporting, and machine-readable data architecture. The press release also reinforces Simple Healthcare’s focus on advancing practical, evidence-based solutions that help transparency policy achieve its intended goals. By translating complex technical recommendations into clear, actionable policy direction, the white paper and accompanying press release are intended to support policymakers, industry stakeholders, and market participants working to make healthcare pricing data more accurate, interpretable, and decision-ready.
Simple Healthcare has released a new white paper, History of Price Transparency in U.S. Healthcare: How Healthcare Became a Market Without Visible Prices, that chronicles how the U.S. healthcare system evolved into one of the few major markets where prices have historically been opaque. The paper traces the shift from direct payment to complex financing, managed care, and negotiated contracts that separated care delivery from clear prices, leaving patients, employers, and purchasers without meaningful price information. While recent federal mandates like the Hospital Price Transparency and Transparency in Coverage rules have made millions of negotiated rates publicly available, the paper emphasizes that disclosure alone isn’t enough — inconsistent formats, data quality problems, and complexity hinder usability. The next phase of transparency must focus on transforming raw data into clean, validated, decision-ready intelligence to support better choices, stronger purchasing power, improved negotiations, and more effective oversight across the healthcare market.
For decades, U.S. healthcare has operated as a market without visible prices — an anomaly unlike almost any other sector of the economy. How Healthcare Became a Market Without Visible Prices explores how this system evolved, tracing the shift from direct-pay medicine to a complex web of insurance, contracts, and payment models that embedded prices deep within private negotiations. The paper explains why transparency efforts historically fell short, and how well-intentioned reforms often increased complexity without improving real-world decision-making. Today, healthcare has crossed a one-way threshold. Federal transparency rules have made negotiated prices technically public, but disclosure alone has not created accountability, competition, or better purchasing decisions. This paper argues that the next phase of price transparency will be defined by whether the industry can convert fragmented disclosures into trusted, decision-ready intelligence. Doing so is critical to improving negotiations, enabling smarter purchasing, informing policy, and ultimately restoring price as a meaningful economic signal in healthcare.
McKnight’s Senior Living highlighted a recent Simple Healthcare analysis that evaluates how well the three largest health insurers comply with federal Transparency in Coverage (TiC) requirements by reporting complete negotiated price data. The piece notes that Simple Healthcare’s research found significant gaps in insurer-reported data, meaning employers and other purchasers may struggle to compare costs and make informed decisions because key negotiated rates are missing or incomplete in publicly accessible TiC files. The coverage emphasizes the broader implications of these data gaps for employer healthcare affordability efforts, underscoring how incomplete TiC disclosures can undermine transparency policy goals and limit stakeholders’ ability to leverage price information for benefit design and cost negotiation.
Axios featured a recent paper by Simple Healthcare analyzing how completely major insurers disclose negotiated prices under federal transparency rules. The report found that UnitedHealthcare, Aetna, and Cigna all left gaps in their data, with Aetna disclosing only about half of common hospital outpatient rates and UnitedHealthcare reporting just 8% of hospital inpatient pricing — despite high completeness in other service categories. The article also includes comments from payers disputing the study’s conclusions — Cigna called any suggestion of noncompliance “false,” and UnitedHealthcare said it aims to provide “clear, complete and actionable data.”Axios noted that the Centers for Medicare & Medicaid Services (CMS)has not taken public enforcement action, even as regulators reaffirm commitments to transparency oversight.
Becker’s Payer Issues reported on Simple Healthcare’s evaluation of 2025 Transparency in Coverage (TiC) files, showing that major insurers are not fully meeting federal disclosure expectations. The article detailed the study’s methodology — comparing published provider counts and negotiated rates across specialties and settings — and found particular weaknesses in hospital inpatient and outpatient data. Becker’s also highlighted that no insurers have been publicly fined by CMS for noncompliance, even as hospitals face penalties for their own transparency violations. The report included insurer responses disputing the findings and noted broader regulatory context, including a 2025 executive order and updated federal guidance to improve TiC data quality
TechTarget covered Simple Healthcare’s study assessing compliance with the Transparency in Coverage rule, which requires insurers to publish machine-readable negotiated rates. The report found major gaps in the completeness of pricing data across the three largest U.S. payers, with Aetna reporting roughly half of hospital outpatient codes, Cigna showing very limited outpatient disclosures, and UnitedHealthcare reporting strong physician specialty data but minimal inpatient pricing. The piece also quoted research stakeholders — including Simple Healthcare’s principal author — highlighting that incomplete data makes it harder for employers and individuals to use transparency tools for cost comparison. TechTarget pointed to upcoming federal guidance and updated data schemas that may help improve compliance and usability.
In this paper, the authors analyzed 2025 publicly available Transparency in Coverage (TIC) machine-readable files from three major national insurers — Aetna, Cigna, and UnitedHealthcare — to assess how complete the data are for physician, hospital outpatient, and hospital inpatient service lines. The analysis revealed wide variation by insurer and service type: Aetna and Cigna generally listed as many—or more—physicians and hospitals as their marketing materials did, whereas UnitedHealthcare listed fewer. Physician specialties and outpatient hospital services were much more thoroughly documented; however, inpatient hospital data were often sparse or incomplete. The authors conclude that while TIC data today can support analyses of prices for physician and outpatient hospital services, they are inadequate for reliable inpatient benchmarking— and recommend that the Centers for Medicare & Medicaid Services (CMS) audit insurers’ TIC data and enforce compliance to improve data quality.
Research by Simple Healthcare CEO highlights major data quality challenge in Transparency in Coverage files. A new study published in Health Affairs Scholar finds that “ghost rates”, or negotiated prices listed for services that providers almost certainly never perform, are highly prevalent in insurer Transparency in Coverage (TiC) files, raising concerns about the usability of federal price transparency data.
New platform puts nationwide negotiated rates at users’ fingertips, empowering healthcare industry leaders with actionable insights at no cost. Designed for investors, life science teams, and physician groups, this tool is a one-of-a-kind resource that allows users to compare prices by payer, billing code, and region completely free of charge—turning complex Transparency in Coverage (TiC) data into clear, actionable insights.
Introduction In 2019, an executive order1 required hospitals and insurers to release negotiated rates for services—hospitals in 2021 and insurers in 2022. In 2025, an additional executive order confirmed this requirement and expanded efforts to make drug prices available. These transparency efforts are intended to increase competition, innovation, and value in healthcare by making prices public. A major challenge with the transparency in coverage (TiC) data, which covers all inpatient, outpatient, postacute, and physician offices, is that many rates relate to providers and groups that do not provide those services. For example, a psychiatrist will never perform a heart transplant, but insurers may report a negotiated rate for that service. These negotiated rates—known as ghost rates—undermine the goals of transparency data. Ghost rates can significantly increase the size of the data and make evaluation more difficult as researchers and analysts do not know if they should include each reported rate in their analysis, resulting in distrust of the TiC data. This research letter provides estimates of how common ghost rates appear in TiC data from 61 insurers including 3 national commercial insurers (CVS/Aetna, Cigna, and UnitedHealthcare), and 58 Blue Cross Blue Shield insurers (including plans sponsored by Elevance/Anthem and Health Care Service Corporation). Methods I identify ghost rates at the group level, the individual provider level, and across networks and calculate the percentage of reported negotiated rates that are ghost rates. The process to identify ghost rates is composed of 3 steps. (1) Identify the types of providers that perform various billing codes utilizing claims data from Medicare and multiple state All Payer Claims Databases. (2) For each individual provider—based on their National Provider Identifier (NPI)—determine if they are likely to perform a service based on either having performed that claim previously (from claims data) or if their specialty is likely to perform that service. (3) Since negotiated rates are provided at the provider-group level, determine whether any provider within that group is likely to perform each billing code; if no providers in the group are likely to perform the code that negotiated rates is a ghost rate. A subanalysis evaluates the prevalence of ghost rates for only the 100 most common billing codes; while there are more than 12,000 billing codes in the data, these 100 represent more than half (56.5%) of claims. A more complete description of the methodology is available in the Supplementary Appendix. Results Figure 1A contains a histogram of the percent of rates for each insurer that are ghost rates and the percent of the 100 most common billing codes that are ghost rates. The median insurer's data consisted of 84.3% ghost rates with the mode (15 insurers) having from 80% to 85% ghost rates; the range was 12.6% to 97.3%. Across a combination of all 61 insurers, 91.8% of all the negotiated rates were ghost rates (3 153 469 476 out of 3 433 560 471). The 100 most common billing codes represent 1.1% of the data; across the 61 insurers, 70.3% of the negotiated rates were ghost rates with a range of 6.3% to 89.8%. Download slide All TiC negotiated rate data are presented at the provider-group level, but includes individual NPIs, allowing me to calculate how many of the included NPIs have ghost rates. Figure 1B provides a histogram of the percent of all providers (based on NPIs) and their corresponding billing rates that are ghost rates. Across all 61 insurers, the median insurer had 95.7% ghost rates, with a range of 16.8% to 98.6%. Combining all 61 insurers, 95.4% of provider-to-billing code pairs were ghost rates (112 297 416 974 out of 117 682 739 557 pairs). The 100 most common billing codes represent 1.1% of the provider-level data; across the 61 insurers, 75.5% of the negotiated rates were ghost rates with a range of 5.3% to 89.2%. Discussion The goal of the TiC data is to empower the healthcare industry to make better informed decisions. However, with over 90% of all listed rates across these 61 insurers being ghost rates, it is far from ideal to achieve that purpose. For the TiC data to become actionable, it needs significant processing and cleaning, or working with a third party that can provide clean data. The prevalence of ghost rates is lower for the most common billing codes, as more providers are likely to perform those codes. For example, most specialties of providers regularly perform office visits, so very few negotiated rates for office visits are ghost rates. However, the 100 most common billing rates, which represent over half of all claims, only account for 1.1% of the negotiated rates, and over 70% were still ghost rates. There are 2 competing goals with the data that are reflected with ghost rates. First, the goal of providing as much information as possible; in this case, every negotiated rate that the payer has contracted with every provider. Second, providing data that is accurate and easy to act upon; in this case, data that is for providers who currently perform, or may perform, the service. The way to address both issues is to require insurers to include volume information at the network-level that indicates how many times each provider group has been paid for that code over the previous year. With that data, it would be straight-forward to remove low-volume or no-volume providers, allowing accurate lists of providers rendering those services. Without volume data, there is not a simple approach to remove ghost rates and most analysts will be reliant on data vendors to identify ghost rates. Given the size and structure of the data, it is unlikely that the TiC files will ever readily be accessible to patients and unsophisticated employers, so the design should be focused on optimizing the data for analysts and researchers. Ghost rates are very common and represent the majority of TiC data, limiting its usefulness without significant cleaning and processing. To maximize the potential of the TiC data, CMS should require payers to include volume information, allowing users to quickly identify ghost rates.
Simple Healthcare’s latest publication emphasizes how negotiated rate data can guide smarter investment decisions across the healthcare sector. The new white paper, new white paper, From Data to Deal: Price Transparency Data for Private Equity Investors, examining how the availability of hospital and insurer Price Transparency data is reshaping healthcare investment strategies.
The U.S. spends more on healthcare than any other similarly developed country, amounting to nearly a fifth of total GDP in 2024. This high level of spending is driven by high prices of healthcare services, prescription drugs, and medical devices, among others. However, accurate and reliable information on healthcare prices has been hard to come by and those looking to gain insight into the healthcare system have had to rely on proxy sources to estimate prices. These sources include Medicare rates, claims data, and other proprietary tools that vary in granularity, completeness, and accuracy. While people have done the best they could with these sources, without information on negotiated rates, the true picture of healthcare prices has remained blurry. The recent Price Transparency rules promise to bring some much-needed clarity. As the healthcare landscape continues to evolve, price transparency has the potential to shift how investors evaluate opportunities and risks, providing a clearer foundation for strategy and decision-making.
A new report from the Commonwealth Foundation discusses how physician payments are set in Medicare under the Resource-Based Relative Value System (RBRVS), and how this process has historically led to primary care being undervalued.
A recent analysis in Health Affairs Forefront calls for CMS to reform physician payment to reflect the value of cognitive effort in primary care. The article, published in Health Affairs Forefront, proposes four key policy recommendations for CMS, and calls for a re-evaluation of how the relative value units (RVUs) work components are calculated for primary care.
Payer-driven healthcare price transparency holds promise for enhancing competition and facilitating informed decision-making across the healthcare system. However, multiple barriers—including inconsistent data formats, incomplete coverage of services (particularly drugs and volumes), and a lack of clarity regarding data sources—are limiting its usability. In response, this article outlines five key recommendations to improve the practical utility of transparency data in real-world settings: Deliver data in a relational structure to enable easier sorting, querying, and integration with other datasets. Report data provenance and structure (i.e., data location and source context) to enhance interpretability and trust. Include drug price data within transparency disclosures, recognizing pharmaceuticals as a critical component of total healthcare costs. Incorporate volume data, which provides context for price variations and helps assess whether rates reflect typical or outlier use. Report negotiated rates, not just list prices, so that transparency reflects the actual costs paid by payers and consumers. These recommendations, born out of practical experience, aim to unlock the full potential of price transparency by making data more accessible, actionable, and meaningful for policymakers, researchers, providers, employers, and patients alike."
A new report urges reforms to improve healthcare price transparency, making data more accessible and usable for patients, employers, and policymakers. The report, featured in Health Affairs Forefront, underscores the need for regulatory improvements to make hospital and insurer price transparency data more accessible and useful for patients, employers, and policymakers.
Background The goal of this study is to estimate the association between hospital system market share and negotiated prices. Hospital system consolidation has led to many highly concentrated markets where systems can leverage their market share to negotiate higher commercial prices. Recently, the Centers for Medicare & Medicaid Services, under its Transparency in Coverage initiative, required health insurers to release all negotiated commercial prices, providing, for the first time, publicly available, nationally representative data on commercial rates. We utilize this newly available data on negotiated prices of healthcare services to show that a hospital with 10% higher market share charges 880-1,180 more per admission. Study design We used commercial price data for national networks of three large, national insurers and performed a linear regression based on more than 1.3 million negotiated rates across 1,784 hospitals to estimate the association between a hospital’s system-level market share and commercial negotiated rates, adjusting for service (DRG), health system, and area level time-invariant characteristics. Results We find that a one percentage point increase in hospital system market share is associated with an $88 to $118 higher negotiated rate per admission. All else equal, a hospital that is part of a system with a 10-percentage point higher market share can expect from $880 to $1,180 more per admission relative to a hospital with lower system market share (5.4% to 6.2% of the median price). Conclusion These findings confirm that higher hospital system market share is strongly associated with higher commercial negotiated prices and should aid policymakers and decisionmakers in assessing the impact of various policy options aimed at reducing provider consolidation in the healthcare market.
Background: While healthcare spending in the United States remains high relative to other nations, research suggests this is driven more by elevated prices than by usage rates. Recent federal initiatives—namely, Hospital Price Transparency (HPT) since January 2021 and Transparency in Coverage (TIC) since July 2022—mandate the public release of prices for common, "shoppable" medical services, aiming to enhance consumer decision-making and market competition. Objective: This study evaluates whether U.S. adults are aware of their ability to access hospital price data before care and whether they actively use that information; it also assesses public support for stricter enforcement of transparency rules. Methods: Researchers analyzed data from a weighted, nationally representative survey conducted by Gallup in collaboration with West Health Institute between November 2023 and January 2024. It included over 5,000 U.S. adults and assessed awareness, usage, and enforcement preferences concerning price transparency. Results: Awareness: Only 27% of respondents knew hospitals are required to post service prices online. Awareness was lower among men (23%) than women (30%) and consistent across age and racial groups. Use: A mere 19% had ever looked up healthcare prices prior to receiving services. Younger adults (ages 18–29) were more proactive (29%) compared to older adults (ages 65 and over: 11%). Enforcement Sentiment: 78% supported stronger penalties against non-compliant hospitals. Conversely, only 26% favored extending timelines for hospitals to comply with transparency requirements. Conclusions: Despite mandates making healthcare prices more available, a large portion of the population remains unaware and does not utilize these data. However, there is robust public demand for accountability, with most respondents endorsing stricter enforcement. The authors recommend stronger CMS enforcement and heightened public education on price transparency to amplify the value of these initiatives.
The Hospital Price Transparency Rule, effective January 2021, mandates that U.S. hospitals publicly post prices for 200 shoppable services in a machine-readable format, with penalties for noncompliance. Yet, compliance has been uneven: only 57% are fully compliant, while 31% report partial compliance; some studies show compliance as low as 36%. Noncompliance stems from several factors: Hospitals needing more time or resources to compile accurate data; The high cost of compliance itself; Concerns that disclosing negotiated rates might weaken their competitive bargaining position—although Transparency in Coverage rules now require payers to report those rates independently, reducing this concern. To address these challenges, the article proposes several policy interventions: Substantially raise enforcement penalties: CMS has already increased fines up to $2,007,500 annually for large hospitals—aligning the cost of noncompliance with, or exceeding, the cost of compliance. Capitalize on payer-based transparency initiatives: As insurers are required to disclose negotiated rates under new Transparency in Coverage policies, hospitals' compliance—or lack thereof—has less competitive risk. Launch public awareness campaigns: Informing consumers about price transparency and its benefits could drive demand for the data, increase usage, and incentivize hospitals to comply. Overall, achieving the goals of transparency—empowering consumers and encouraging healthcare competition—requires both stronger enforcement and enhanced public engagement.
Background: Healthcare price transparency laws now enable disclosure of negotiated rates between hospitals and payers. However, clarity is lacking on how different commercial insurers compare in that transparency. This article examines how effectively four national commercial payers disclose pricing information, exploring variation and gaps in transparency. Methods: The study analyzes publicly available hospital pricing data under the Hospital Price Transparency Rule (effective as of early 2023) for four prominent national commercial insurers. It assesses the completeness of disclosure, range of services reported, and consistency in presenting negotiated rates in a machine-readable format. Findings: Significant variation exists across the four payers in both the breadth of services disclosed and the structure of data presentation. Some payers provide more comprehensive, standardized, and easy-to-use files; others deliver fragmented or poorly formatted disclosures. These inconsistencies hinder meaningful comparisons for consumers, researchers, employers, and policy analysts seeking to understand pricing differences across insurers and markets. Conclusions: Although transparency rules have improved access to data, meaningful comparison of prices across commercial payers remains limited by disparities in how the data are shared. To enhance transparency, the article recommends: Improving data standardization across insurers (consistent formatting, complete service lists). Expanding the scope of services disclosed. Adopting best practices from more transparent payers. These steps are needed to maximize the potential of price transparency to drive fair competition and enable empowered decision-making.