ArticleInquiry : a journal of medical care organization, provision and financing
Estimating the Impact of New Health Price Transparency Policies.
Article in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Gender-Affirming Surgery Price Transparency and Online Information Availability in US Hospitals.Aesthetic plastic surgery · 2026Article
- Tennessee hospital noncompliance with price transparency legislation for 8 common laboratory tests.American journal of clinical pathology · 2024Article
- Hospitals with decreasing cost-to-charge ratios bill greater surgical charges for similar outcomes.Surgery · 2024Article
- Oncologic Surgery in the United States: Do You Get What You Pay For?Annals of surgical oncology · 2024Article
- Counting the Cost of Pins and Needles: A Case Study of Paresthesias and the Cost of Healthcare in the United States.Cureus · 2024Article
- Cloudiness in price transparency for hernia repair.American journal of surgery · 2023Article
- Price Transparency in United States' Health Care: A Narrative Policy Review of the Current State and Way Forward.Inquiry : a journal of medical care organization, provision and financingReview
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This analysis investigates and scores the impact of new health price transparency rules. Using a set of novel data sources, we estimate substantial savings are possible following the implementation of the insurer price transparency rule. Specifically, we estimate annual savings to consumers, employers, and insurers by 2025, assuming a robust set of tools to allow consumers to purchase medical services. We matched claims with 70 HHS defined shoppable services by CPT and DRG codes and replaced them with an estimated median commercial allowed payment multiplied by a reduced cost of 40% based on estimates found from literature for the difference in cost between negotiated and cash payment for medical services. We consider 40% to be an upper bound estimate of the potential savings based on existing literature. Several databases are used to estimate the potential benefits of insurer price transparency. Two different all-payer claim databases were used, representing the entire insured population in the US. For this analysis, only the private insurer commercial population was examined, comprised of over 200 million covered lives as of 2021. The estimated impact of price transparency will vary significantly by region and income level. The national upper bound estimate is $80.7 billion. The national lower bound estimate is $17.6 billion. For the upper bound, the region with the most significant impact in the US will be the Midwest, with $20 billion in potential savings and an 8% reduction in medical expenditure. The region with the lowest impact will be the South, with only a 5.8% reduction. Concerning income, those at lower levels of income will have the most significant impact with a -7.4% (<100% Federal Poverty Level) to -7.5% (100%-137% Federal Poverty Level) impact. Overall, the total impact could be a 6.9% reduction for the whole privately insured population in the United States. In summary, a unique set of national data resources were used to estimate the cost savings impact medical price transparency. This analysis suggests price transparency for shoppable services may yields significant savings between $17.6 to $80.7 billion by 2025. Consumers may have strong incentives to shop with the rise in the use of high deductibles, health plans, and health savings accounts. How these potential saving are to be shared by consumers, employers and health plans has yet to be determined.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.