For several years, the federal government has taken steps to increase price transparency in healthcare, with the hope that better access to data will benefit consumers and other key stakeholders.
In 2021, to disclose pricing information online for every service, drug, and item they provide. This includes the prices that hospitals have negotiated with insurers and the amounts that patients paying cash for services would be charged.
to learn how PlanOptix turns price transparency data into usable information for healthcare brokers, payers, and employers.
Similar rules were then created for many group health plans and issuers of group or individual insurance. Since July 2022, the has required insurers and large employers to publish machine-readable files (MRF) which include in-network rates for covered items and services, as well as allowed amounts and historical billed charges for providers who are out of network.
Public policy makers hoped that improved access to this information would support better health insurance network negotiations and market positioning, help the healthcare sector attain its access and cost goals, and enable various healthcare players to make data-driven decisions. The healthcare industry is still collectively striving to achieve this vision.
The Rocky Road of Machine-Readable Files and Healthcare Pricing Data
To derive value from healthcare pricing information, users must have confidence in the integrity and completeness of the data. Unfortunately, data quality varies widely across different payers and locations. Key challenges include:
- Massive data volumes. Price transparency mandates have resulted in an unprecedented amount of complex data that requires extensive validation and evaluation before it can be used for practical applications. This is time-consuming work.
- Low data quality. No standardized measures exist to assess the quality of price transparency data in MRF. is work that is usually done at the organizational level. Some hospitals and insurers have stronger data governance cultures than others.
- Poor data integrity. recently analyzed pricing data from 2,000 hospitals and found only around one-third (34.5%) were fully compliant with all aspects of the Hospital Price Transparency Rule.
Healthcare Price Transparency Solutions Can Help, But Not All are Created Equal
To make it easier to work with publicly available healthcare price transparency data, many technology vendors have developed tools and platforms. Those solutions, however, are only as good as the underlying data. The undeniable reality is that cleaning up healthcare pricing information is no simple task. Not only are the volumes of information enormous, but the .
For example, within the MRFs from hospitals and insurers, the payer name may be included, but not the associated plan name. It鈥檚 common for price data to be represented as a formula instead of a dollar amount. The fields for negotiated rates may contain zeros, asterisks, or blanks.
The formatting of the data files can also be problematic. For instance, some hospitals and insurers post multiple files, even though the federal mandate requires a single file. Another issue is that files may be created in 鈥渢all format鈥 rather than 鈥渨ide format.鈥 With tall formatted files, the same item or service is repeated in multiple rows, instead of allocating one row for each item or service. This results in large volumes of repetitive information. It also makes it challenging to compare prices or identify missing price data.
Healthcare price transparency solution vendors may assert that their data quality is high, but how true are their claims? Some companies simply jettison large portions of their data sets because they鈥檙e too complicated to clean up. While the remaining information may look sound, it鈥檚 only a fraction of the original data set.
A Tool for Informed Decision-Making
PlanOptix transforms healthcare price transparency data into usable information that healthcare brokers, payers, and employers can trust. PlanOptix is unique because the solution includes a Data Usability Rating. In addition, PlanOptix users can benchmark pricing data against Medicare rates. This is important in a world where hospitals don鈥檛 follow a standard formula for setting prices and aren鈥檛 required to reveal markups on the services or supplies they purchase. Since chargemaster data varies widely, it isn鈥檛 a useful benchmark.
Although Medicare pricing is subject to change, it鈥檚 still a logical benchmark that is familiar to everyone in the industry. Medicare is used so widely throughout the United States healthcare system that , reducing the time and resources needed to negotiate contracts.
The objective assessment of data quality offered by PlanOptix means you can make important decisions about healthcare costs with confidence.