Patterns of Use of a Price Transparency Tool for Childbirth Among Pregnant Individuals With Commercial Insurance

Gourevitch, Rebecca; Chien, Alyna T.; Bambury, Elizabeth; Shah, Neel; Riedl, Christine; Rosenthal, Meredith B.; Sinaiko, Anna D.

doi:10.1001/jamanetworkopen.2021.21410

Cited by 5 publications

(5 citation statements)

References 23 publications

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“… a Identification of children with disabilities was based on an initial 24 months of continuous insurance 32 …”

Section: Resultsmentioning

confidence: 99%

“…This is a cross‐sectional, descriptive study of 133,749 person‐years of commercially insured data from 89,987 unique 0‐ to 18‐year‐olds with disabilities between January 1, 2012, and December 31, 2016. This study population was identified from 3,131,954 person‐years of data on 1,774,948 unique 0‐ to 18‐year‐old enrollees who were insured for at least 24 months 32 . Children with disabilities were identified the validated CWDA 1–3 .…”

Section: Methodsmentioning

confidence: 99%

“…This study population was identified from 3,131,954 person-years of data on 1,774,948 unique 0-to 18-year-old enrollees who were insured for at least 24 months. 32 Children with disabilities were identified the validated CWDA. [1][2][3] Conceptually, our study team considers a disabling health condition to affect the whole person and therefore all the health care that they use.…”

Section: Study Design and Populationmentioning

confidence: 99%

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Specialist use among privately insured children with disabilities

Chien

Wisk

Beaulieu

et al. 2023

Health Services Research

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ObjectiveTo investigate primary care practice ownership and specialist‐use patterns for commercially insured children with disabilities.Data Sources and Study SettingA national commercial claims database and the Health Systems and Provider Database from 2012 to 2016 are the data sources for this study.Study DesignThis cross‐sectional, descriptive study examines: (1) the most visited type of pediatric primary care physician and practice (independent or system‐owned); (2) pediatric and non‐pediatric specialist‐use patterns; and (3) how practice ownership relates to specialist‐use patterns.Data Collection/Extraction MethodsThis study identifies 133,749 person‐years of commercially insured children with disabilities aged 0–18 years with at least 24 months of continuous insurance coverage by linking a national commercial claims data set with the Health Systems and Provider Database and applying the validated Children with Disabilities Algorithm.Principal FindingsThree‐quarters (75.9%) of children with disabilities received their pediatric primary care in independent practices. Nearly two thirds (59.6%) used at least one specialist with 45.1% using nonpediatric specialists, 28.8% using pediatric ones, and 17.0% using both. Specialist‐use patterns varied by both child age and specialist type. Children with disabilities in independent practices were as likely to see a specialist as those in system‐owned ones: 57.1% (95% confidence interval [95% CI] 56.7%–57.4%) versus 57.3% (95% CI 56.6%–58.0%), respectively (p = 0.635). The percent using two or more types of specialists was 46.1% (95% CI 45.4%–46.7%) in independent practices, comparable to that in systems 47.1% (95% CI 46.2%–48.0%) (p = 0.054). However, the mean number of specialist visits was significantly lower in independent practices than in systems—4.0 (95% CI 3.9%–4.0%) versus 4.4 (95% CI 4.3%–4.6%) respectively—reaching statistical significance with p < 0.0001.ConclusionsRecognizing how privately insured children with disabilities use pediatric primary care from pediatric and nonpediatric primary care specialists through both independent and system‐owned practices is important for improving care quality and value.

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“… a Identification of children with disabilities was based on an initial 24 months of continuous insurance 32 …”

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Study Design and Populationmentioning

confidence: 99%

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Specialist use among privately insured children with disabilities

Chien

Wisk

Beaulieu

et al. 2023

Health Services Research

Self Cite

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“…These findings suggest that price information may help individuals anticipate their out-of-pocket childbirth costs. 17 These more recent studies all vary in degree of impact, but most are showing directionally positive and significant consumer response to price transparency tools. The timetable for implementation of the new federal policies on transparency has been staggered over several years.…”

Section: Policy Backgroundmentioning

confidence: 99%

Estimating the Impact of New Health Price Transparency Policies

Parente

2023

INQUIRY

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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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“…A 2017 study found that only 1% of patients who consumed advanced imaging services had used a new price-shopping tool (Desai et al, 2017). A 2022 study focusing on childbirth services found 13% of pregnant individuals using a price tool (Gourevitch et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The effects of price transparency and debt collection policies on intentions to consume recommended health care: A randomized vignette experiment

Robertson,

Epstein,

2023

J Empirical Legal Studies

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New laws promote price transparency in health care, though effects on patient decision‐making are not known. Price disclosure may increase the salience of cost and cause lower‐income patients to decline recommended care, worsening inequities in health outcomes. Whether patients perceive a disclosed cost as higher or lower than their expectations may also affect care decisions, but has not been studied. Scholars and policymakers have paid much less attention to the question of whether patients will have to pay the prices charged (whether disclosed or not), and how expectations regarding collections may also affect healthcare consumption. Some hospitals aggressively collect on unpaid medical bills. Others hospitals do not. Actively disclosing collection policies (whether aggressive or protective) could magnify or counteract effects of price disclosures, especially for low‐income patients. To test the effect of price disclosure and debt‐collection disclosures on willingness to obtain recommended care, we recruited a nationally representative sample (N = 2997) and deployed a full factorial, controlled experiment in a standardized clinical vignette model. We find that disclosing a higher‐than‐anticipated price increases the probability of declining recommended care (odds ratio = 1.900), with larger effects for low‐income individuals. Even more, disclosing aggressive collections increases the risk of declining care (odds ratio = 4.493), at higher rates for low‐income patients. Where patients fear collections, but do not know prices, they are most likely to decline care. Disclosure of an aggressive collections policy makes patients feel less informed, harms patient trust in providers, makes them feel that they were not treated fairly, and undermines their confidence in the value of their care. Mediation analysis shows that about half of the effect of collections risk is via these attitudinal variables.

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Patterns of Use of a Price Transparency Tool for Childbirth Among Pregnant Individuals With Commercial Insurance

Abstract: This cross-sectional study examines the association between use of an insurance-owned patient-facing price estimator tool by pregnant individuals and out-of-pocket childbirth spending.

Cited by 5 publications

References 23 publications

Specialist use among privately insured children with disabilities

Specialist use among privately insured children with disabilities

Estimating the Impact of New Health Price Transparency Policies

The effects of price transparency and debt collection policies on intentions to consume recommended health care: A randomized vignette experiment

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