Price Transparency in Healthcare in the United States: For Patients Or Algorithms? (Preprint)

Abstract

Increasing healthcare expenditure in the United States has put policymakers under enormous pressure to find ways to curtail costs. Starting January 1st, 2021, hospitals operating in the U.S. were mandated to publish transparent, accessible pricing information online about the items and services in a consumer-friendly format within comprehensive machine-readable files on their websites. Is the content that’s being put out by hospital systems usable?

To analyze the available files on hospitals’ websites answering the question: is price transparency information as provided usable for patients or for machines? And providing a solution.

We analyzed 39 main hospitals in Florida that have published machine-readable files on their website including commercial carriers. We created an Excel file that included those 39 hospitals along with the four most popular services – CPT 45380, 29827, 70553, and DRG 807 – for the four most popular commercial carriers (HMO/PPO plans) – Aetna, FL Blue, Cigna, and UnitedHealth care. We conduct an A/B test using 67 MTurkers investigating the level of awareness about price transparency legislation and the usability of available files. We also suggest format standardization such as master field names using schema-integration to make machine-readable files consistent and usable for machines.

Due to the poor usability and inconsistency of formats, we did not find evidence that price transparency information as currently provided appears to be neither useful for patients – in contrast to the legislation that it should be consumer-friendly – nor is its quality good for machines – again, in contrast to the legislation that it should be machine-readable. Based on the responses to the first part of the experiment (price transparency awareness), it was evident that participants need to be made aware of the price transparency legislation. However, they believe it is important to know the service price before receiving it. Based on the responses to the second part of experiment (Human usability of price transparency information), the average number of correct responses was not equal between the two groups, i.e., the treatment group (M = 1.23, SD = 1.30) found more correct answers than the control group (M = 2.76, SD = 0.58), t(65) = 6.46, p < 0.05, d = 1.52.

Consistent machine-readable files across all providers facilitate the development of tools for estimating customer out-of-pocket costs, aligning with the price transparency rule's main objective: providing patients valuable information and reducing healthcare expenditures.

The study was conducted in adherence to approved protocols by the University of South Florida Institutional Review Board (Study ID: STUDY004145).