Commercial Price Variation for Breast Reconstruction in the Era of Price Transparency

This cross-sectional study investigates the extent of commercial price variation for breast reconstruction.

Key Points

Question

How do commercial payer–negotiated rates for breast reconstruction vary?

Findings

In a cross-sectional analysis of 2021 commercial payer–negotiated rates from 993 hospitals, commercial rates varied substantially.

Meaning

Study results suggest that commercial rates for breast reconstruction demonstrated large nationwide variation.

Abstract

Importance

Breast reconstruction is costly, and negotiated commercial rates have been hidden from public view. The Hospital Price Transparency Rule was enacted in 2021 to facilitate market competition and lower health care costs. Breast reconstruction pricing should be analyzed to evaluate for market effectiveness and opportunities to lower the cost of health care.

Objective

To evaluate the extent of commercial price variation for breast reconstruction. The secondary objective was to characterize the price of breast reconstruction in relation to market concentration and payer mix.

Design, Setting, and Participants

This was a cross-sectional study conducted from January to April 2022 using 2021 pricing data made available after the Hospital Price Transparency Rule. National data were obtained from Turquoise Health, a data service platform that aggregates price disclosures from hospital websites. Participants were included from all hospitals with disclosed pricing data for breast reconstructive procedures, identified by Current Procedural Terminology (CPT) code.

Main Outcomes and Measures

Price variation was measured via within- and across-hospital ratios. A mixed-effects linear model evaluated commercial rates relative to governmental rates and the Herfindahl-Hirschman Index (health care market concentration) at the facility level. Linear regression was used to evaluate commercial rates as a function of facility characteristics.

Results

A total of 69 834 unique commercial rates were extracted from 978 facilities across 335 metropolitan areas. Commercial rates increased as health care markets became less competitive (coefficient, $4037.52; 95% CI, $700.12 to $7374.92; P = .02; for Herfindahl-Hirschman Index [HHI] 1501-2500, coefficient $3290.21; 95% CI, $878.08 to $5702.34; P = .01; both compared with HHI ≤1500). Commercial rates demonstrated economically insignificant associations with Medicare and Medicaid rates (Medicare coefficient, −$0.05; 95% CI, −$0.14 to $0.03; P = .23; Medicaid coefficient, $0.14; 95% CI, $0.07 to $0.22; P < .001). Safety-net and nonprofit hospitals reported lower commercial rates (coefficient, −$3269.58; 95% CI, −$3815.42 to −$2723.74; P < .001 and coefficient, −$1892.79; −$2519.61 to −$1265.97; P < .001, respectively). Extra-large hospitals (400+ beds) reported higher commercial rates compared with their smaller counterparts (coefficient, $1036.07; 95% CI, $198.29 to $1873.85, P = .02).

Conclusions and Relevance

Study results suggest that commercial rates for breast reconstruction demonstrated large nationwide variation. Higher commercial rates were associated with less competitive markets and facilities that were large, for-profit, and nonsafety net. Privately insured patients with breast cancer may experience higher premiums and deductibles as US hospital market consolidation and for-profit hospitals continue to grow. Transparency policies should be continued along with actions that facilitate greater health care market competition. There was no evidence that facilities increase commercial rates in response to lower governmental rates.

Introduction

Transparency in commercial insurance rates is novel for US medicine, including breast reconstruction, which is one of the most costly and commonly performed reconstructive operations. Although Medicare and Medicaid pay hospitals and clinicians based on publicly available rates set at the federal and state levels,^1,2 commercial payers reimburse based on negotiated contractual rates that have historically been hidden from public view. This lack of commercial price transparency has constrained prior research in this area to price estimations based on charges, frequently published as the chargemaster, which are often inflated arbitrarily and thus unrepresentative of the actual reimbursement that a hospital receives.^3,4 Several studies evaluate the cost of breast reconstruction based on charges that are converted to costs using database- or institution-specific cost-to-charge ratios.^5,6,7,8,9 Others examine payments for breast reconstruction based on claims in commercial or state-level databases.^{10,11,12,13,14,15,16} In the absence of research using commercial payer–specific negotiated rates, the economics of commercial reimbursement for breast reconstruction remain obscure.

Commercial price transparency reforms are intended to enable a credible assessment of current health care market efficiency for shoppable surgical services. In standard economic theory, market participants all have perfect information, and therefore, price transparency is complete.¹⁷ The absence of price transparency can lead to anticompetitive behavior and drive up the cost of health care. In an effort to promote cost-based competition and ultimately reduce the cost of health care, the Centers for Medicare & Medicaid Services (CMS) implemented the Hospital Price Transparency Rule on January 1, 2021, that requires hospitals to disclose discounted cash prices and commercial payer–specific negotiated rates for shoppable services.^18,19 Over the past year, investigators have leveraged the data made public from this mandate to demonstrate large variation in commercial pricing for procedures within otolaryngology,^20,21 radiology,^22,23 ophthalmology,²⁴ and orthopedics,²⁵ in addition to general medical and surgical hospital services.^26,27,28,29 For instance, the median commercial negotiated price for colonoscopy among 1225 disclosing hospitals ranged from $3677 to $27 679 among the 10% of highest-price hospitals and $44 to $3676 among the remaining hospitals.³⁰

For both autologous and implant-based breast reconstruction, commercial prices have yet to be evaluated in a transparent manner. The purpose of this study was to use newly accessible commercial payer–specific rates for breast reconstruction to characterize commercial price variation and market economics. We hypothesized that, as has been shown for charges for breast reconstruction,^{5,6,7,8,9,10,11,12,13,14,15,16} there is substantial variation in commercial prices throughout the US. In light of increasing consolidation of US hospital markets,^31,32,33 and decreasing public payer reimbursement for plastic surgery procedures,^34,35 our secondary objective was to evaluate commercial price variation in relation to health care market concentration and payer composition. In line with economic theory,^31,36 we hypothesized that commercial rates would increase as market consolidation increased. In addition, we anticipated that a decrease in hospital-specific public payer rates would be associated with increased commercial rates (ie, cost shifting) in attempts to offset budget shortfalls.

Methods

Study Design and Data Sources

This study, conducted from January to April 2022, did not require institutional review or approval because it does not involve human subjects research. We performed a cross-sectional analysis of hospital pricing data for 17 breast reconstructive procedures, as identified by Current Procedural Terminology (CPT) code. These procedures included autologous reconstruction, alloplastic reconstruction, secondary breast reconstructive procedures, and other breast reconstructive procedures (eTable in the Supplement). Hospital pricing information for each CPT code, including 2021 public payer (Medicare and Medicaid) rates, self-pay rates (ie, the price that patients pay out-of-pocket if they are uninsured or do not use insurance), list prices (ie, chargemaster prices), and commercial payer–specific rates (ie, the price per plan that a commercial payer negotiates with a hospital), were obtained from Turquoise Health, a data service platform that mines hospital data warehouses for price disclosures.³⁷ Turquoise Health price transparency data cover 5700 US hospitals (94% of 6090 total hospitals) and have been used previously for academic study.^{22,27,28,30,38,39} Data from Maryland were excluded because this state controls acute care hospital prices via its Global Budget Program.⁴⁰ This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

Price transparency data were merged at the hospital level with the 2021 Lown Institute Hospitals Index, a publicly available data set containing descriptive facility-level data (eg, hospital size, safety-net status, profit status [for-profit hospital vs nonprofit hospital], teaching status [major or minor teaching hospital vs nonteaching hospital], and local population density [urban vs rural]) for more than 3709 US hospitals.⁴¹ Methodology for compiling the index is available from the Lown Institute.⁴² Briefly, a safety-net hospital is defined as the 20% of hospitals with the highest proportion of patients eligible for both Medicare and Medicaid. Hospital size is based on bed count: extra small (6-49 beds), small (50-99 beds), medium (100-199 beds), large (200-399 beds), and extra large (400+ beds).

Health care market competition was measured with the Herfindahl-Hirschman Index (HHI), a widely used measure that equals the sum of the squared market share (ie, share of annual inpatient admissions) of each hospital system in the market multiplied by 10 000.^31,43,44 A larger HHI indicates a more concentrated (ie, less competitive) market, such that 0 represents perfect competition, and 10 000 represents a monopoly. HHI 2019 data for 185 US metro areas were compiled by the Health Care Cost Institute according to published methodology.⁴⁵ The eFigure in the Supplement contains details regarding data set construction.

Statistical Analysis

All rates were adjusted to account for geographic variation in input costs using the geographic adjustment factor (GAF), with the exception of Medicare rates which already contain this adjustment.⁴⁶ Commercial price variation was measured by comparing ratios within and across facilities for CPT codes, as performed in earlier iterations of price variation research.^20,21 Within-hospital ratios per CPT code were calculated as the median of the maximum commercial rate divided by the minimum commercial rate for each hospital. Across-hospital ratios were calculated as the 90th percentile median commercial rate divided by the 10th percentile median commercial rate across all hospitals for a given CPT code; these percentiles were selected to diminish the effect of outliers, as per previous methodology.^20,26 The Wilcoxon rank sum test was used to compare commercial rates between reconstruction types due to the non-Gaussian distribution.

Mixed-effects linear regression modeled an expected value of the median commercial rate with other median payer rates, list price, and HHI, with a random intercept by facility. HHI was modeled as a categorical variable to allow for nonlinear trends in market competition based on Department of Justice standards for highly competitive (≤1500), moderately concentrated (1501-2500), and highly concentrated (>2500) markets.⁴⁷ Comparing rates across hospitals is complicated by 2 factors: first, the share of patients that corresponds to each payer rate and second, unobservable hospital factors (eg, facility’s contract experience) that could be correlated with their rates. Therefore, we included a random intercept by facility to account for interhospital variation. The likelihood ratio test was used to compare model fitness of the mixed-effects model to a simple linear regression model. The Akaike information criterion was evaluated to optimize model parsimony.

Because the facility intercept is perfectly collinear with facility characteristics, a second linear regression was used to model associations of commercial rate with facility-level variables.⁴⁸ The focus on commercial rate alone removes confounders that could result from varying shares of patients across hospitals. For all analyses, 2-sided P values < .05 were considered significant. Analyses were conducted using Stata/SE, version 15.0 (StataCorp LLC). Geographic mapping of GAF-normalized commercial rates across hospital referral regions throughout the US was performed with Tableau (Tableau Software LLC).

Results

A total of 69 834 unique commercial rates were extracted from 978 unique hospitals across 335 metropolitan areas; commercial rates were unique in terms of hospital, CPT code, payer, and plan. Hospitals had at least 1 published commercial rate (808 [82.6%]), Medicare rate (522 [53.4%]), Medicaid rate (353 [36.1%]), list price (559 [57.2%]), or self-pay rate (606 [62.0%]) for any of the queried breast reconstruction CPT codes. A total of 671 hospitals had facility characteristic data; 116 (11.9%) were safety-net hospitals, 585 (59.8%) were nonprofit hospitals, 334 (34.2%) were nonteaching hospitals, and 147 (15.0%) were in rural areas. Median (IQR) HHI was 2338 (1717-3205); overall range was 622 to 9067.

The variation in GAF-adjusted commercial payer–negotiated rates for breast reconstruction is illustrated in Figure 1. Median payer-negotiated rates per CPT code, in addition to within-hospital and across-hospital ratios for commercial rates, are enumerated in Table 1. Within-hospital ratios ranged from 1.61 (IQR, 1.00-3.02) to 2.50 (IQR, 1.02-6.25). Across-hospital ratios ranged from 4.45 to 18.31. Figure 2 shows the distribution of average payer rate per hospital for CPT 19357 (insertion of tissue expander) and CPT 19364 (breast reconstruction with free flap). Commercial prices per hospital for alloplastic reconstruction (median [IQR], $6979.71 [$3351.44-$12 466.73]) were significantly higher than those for autologous reconstruction ($4844.9 [$2990.21-$8.150.48]; Wilcoxon rank sum P < .001). The nationwide geographic variation in GAF-normalized commercial rates is illustrated in Figure 3.

Figure 1. Commercial Rates in Breast Reconstruction.

Variation in geographic adjustment factor–normalized commercial rate per Current Procedural Terminology (CPT) code for 69 834 individual hospital-specific commercial plans. Table 1 contains descriptions of CPT codes. Outliers are excluded from the graph.

Table 1. Descriptive Statistics for Commercial Negotiated Rates in Breast Reconstruction.

Service (CPT code)a	No. of rates	No. of hospitals	GAF-normalized payer-negotiated rate, $b			Within-hospital ratio (IQR)c	Across-hospital ratiod
			Median (IQR)	10th Percentile median rate	90th Percentile median rate
Alloplastic reconstruction
TE replacement with implant (11970)	5542	531	6371.97 (2444.25-12 451.69)	1046.60	20 073.58	2.50 (1.00-5.82)	11.54
Insertion of TE (19357)	5456	530	8422.51 (3576.34-16 848.75)	1796.60	31 836.15	2.11 (1.00-6.58)	14.79
Immediate insertion of prosthesis (19340)	5653	530	5258.48 (2068.82-10 414.65)	1068.84	19 240.41	2.38 (1.00-6.61)	11.87
Delayed insertion of prosthesis (19342)	4362	419	6065.90 (2548.00-10 622.64)	1215.74	18.141.23	2.02 (1.00-5.73)	14.99
Augmentation with implant (19325)	4082	352	6168.16 (2396.85-11 066.48)	936.65	20 227.62	1.87 (1.00-5.03)	18.31
Autologous reconstruction
Latissimus dorsi ± implant (19361)	2040	212	4782.56 (2336.64-8449.04)	1530.63	13 353.50	1.71 (1.00-4.35)	11.15
Free-flap reconstruction (19364)	1323	141	5539.46 (3293.75-14 742.22)	2150.64	14 742.22	1.88 (1.00-3.39)	4.45
TRAM
1 Pedicle (19367)	1298	173	4564.86 (1523.42-7624.02)	1523.42	14 166.58	1.61 (1.00-3.02)	9.52
1 Pedicle w/supercharging (19368)	1109	123	4895.70 (2788.02-8.151.75)	1870.29	8.151.75	1.92 (1.02-3.72)	4.78
Bipedicle (19369)	1612	126	4173.39 (2551.27-7553.21)	1572.73	7553.21	1.95 (1.11-4.96)	4.93
Secondary breast procedures
Removal of intact implant (19328)	6077	492	3574.49 (1792.11-8894.93)	733.09	13 685.15	2.50 (1.02-6.25)	8.29
Removal of ruptured implant (19330)	3996	417	3341.15 (1583.05-6467.22)	737.98	10 057.87	2.22 (1.00-5.26)	9.35
Nipple/areola reconstruction (19350)	5338	454	3563.80 (2084.23-6171.75)	961.39	6171.75	2.09 (1.00-4.10)	7.16
Revision of implant capsule (19370)	4167	403	3594.02 (2043.51-6947.87)	871.20	12 036.07	2.18 (1.00-4.50)	8.65
Revision of reconstructed breast (19380)	5796	549	5095.77 (2124.66-8814.57)	994.55	15 730.30	2.21 (1.00-5.03)	10.03
Other breast reconstruction
Mastopexy (19316)	5623	488	4914.36 (2300.71-8.459.55)	1122.93	18.419.46	1.85 (1.00-5.16)	10.58
Reduction mammaplasty (19318)	6360	604	6434.16 (3290.69-12 838.43)	1523.36	22 967.60	2.37 (1.00-5.68)	8.95

Abbreviations: CPT, Current Procedural Terminology; GAF, geographic adjustment factor; TE, tissue expander; TRAM, transverse rectus abdominis myocutaneous.

^a Service names are abbreviated. Full service/procedure names are listed in the eTable in the Supplement.

^b Calculated based on the median payer-negotiated rate at each hospital.

^c Calculated as the median of the maximum payer-negotiated rate divided by the minimum payer-negotiated rate for each hospital (each hospital may contain multiple contracted commercial insurance rates that vary by insurance plan).

^d Calculated as 90th percentile median Medicare-normalized rate divided by the 10th percentile median Medicare-normalized across all hospitals.

Figure 2. Distribution of Median Payer Rate per Hospital for Procedures .

Distribution of median payer rate per hospital for the insertion of tissue expander (A) and free-flap breast reconstruction (B). All rates, except Medicare, are geographic adjustment factor normalized. Outliers are excluded from the graph.

Figure 3. Adjusted Commercial Rates for Breast Reconstruction by Hospital Referral Region.

Minimum and maximum were set at the 10th and 90th percentile of rates. Color gradation centered at median rate. Median rate for hospital referral region was used to represent all zip codes within that hospital referral region.

Mixed-Effects Model Evaluating Payer and HHI

Commercial rate was positively associated with Medicaid rate (coefficient, $0.14; 95% CI, 0.07-0.22; P < .001), self-pay rate (coefficient, $0.65; 95% CI, 0.57-0.72; P < .001), and list price (coefficient, $0.04; 95% CI, $0.01-$0.07; P = .02) (Table 2). Commercial rates demonstrated economically an insignificant association with Medicare rates (Medicare coefficient, −$0.05; 95% CI, −$0.14 to $0.03; P = .23). Commercial rate was also significantly associated with an HHI of 1501 to 2500 (coefficient, $4037.52; 95% CI, $700.12-$7374.92; P = .02) and greater than 2500 (coefficient, $3290.21; 95% CI, $878.08-$5702.34; P = .01), using an HHI of 1500 or less as a reference.

Table 2. Mixed-Effects Linear Regression Output for Geographic Adjustment Factor–Adjusted Commercial Rate, Total Breast Reconstruction^a.

Variable	SE	Coefficient (95% CI), $	P value
Payers and HHI, random intercept by provider
Medicare rate	0.05	−0.05 (−0.14 to 0.03)	.23
Medicaid rateb	0.04	0.14 (0.07 to 0.22)	<.001
Self-pay rateb	0.04	0.65 (0.57 to 0.72)	<.001
List priceb	0.02	0.04 (0.01 to 0.07)	.02
HHI
≤1500	Reference	Reference	NA
1501-2500	1702.79	4037.52 (700.12 to 7374.92)	.02
>2500	1230.70	3290.21 (878.08 to 5702.34)	.01
Facility factors, random intercept by CPT code
Size (bed count)
Extra small (6-49)	Reference	Reference	NA
Small (50-99)	428.47	−508.79 (−1348.57 to 330.99)	.24
Medium (100-199)	396.89	446.71 (−331.18 to 1224.60)	.26
Large (200-399)	407.73	−157.44 (−956.58 to 641.71)	.70
Extra large (400+)	427.45	1036.07 (198.29 to 1873.85)	.02
Safety net	278.50	−3269.58 (−3815.42 to −2723.74)	<.001
Nonprofit	319.81	−1892.79 (−2519.61 to −1265.97)	<.001
Nonteaching	240.25	−290.71 (−761.59 to 180.17)	.23
Rural location	314.78	−140.41 (−757.38 to 476.55)	.66

Abbreviations: CPT, Current Procedural Terminology; HHI, Herfindahl-Hirschman Index; NA, not applicable.

^a Model P values <.001. First/top model with 573 observations, second/bottom model with 4296 observations. Likelihood ratio test for both regressions, P value <.001.

^b Geographic adjustment factor–normalized rate.

Mixed-Effects Model Evaluating Facility Characteristics

Commercial rate was positively associated with largest hospital size (400+ bed count), compared with the smallest size (6-49 bed count) (coefficient, $1036.07; $198.29-$1873.85; P = .02), and negatively associated with safety-net status (coefficient, −$3269.58; −$3815.42 to −$2723.74; P < .001) and nonprofit status (coefficient, −$1892.79; −$2519.61 to −$1265.97; P < .001) (Table 2). Commercial rate was not associated with teaching status or local population density. The likelihood ratio test comparing the mixed-effects linear model to a simple linear regression yielded a P value of <.001, suggesting superior fit of the mixed effects model.

Discussion

The Hospital Price Transparency Rule of 2021 has forced commercial price transparency for the first time in American medicine. This legislation takes a leap forward in allowing the public and payers a view into negotiated rates with the hope of increasing competition and reducing health care costs. As such, this cross-sectional study is the first, to our knowledge, to explore nationwide commercial payer–negotiated rates for breast reconstructive services, and results suggest substantial variation both within and across hospitals. For instance, for tissue expander placement (CPT 19357), the median payer-negotiated price per hospital had a median value of $8422.51 (IQR, $3576.34-$16 848.75), and within- and across-hospital ratios of 2.11 and 14.79, respectively. In other words, on average at a given hospital, the maximum negotiated rate was 2.11 times more than the minimum negotiated rate. Among the total group of hospitals, the median 90th percentile price was 14.79 times more than the median 10th percentile price. For free-flap breast reconstruction (CPT 19364), the median payer-negotiated price at each hospital had a median value of $5539.46 (IQR, $3293.75-$9303.02), and within- and across-hospital ratios of 1.18 and 4.45, respectively. Alloplastic reconstruction demonstrated higher prices and greater variability in price compared to autologous reconstruction.

This large variation in commercial payer–negotiated rates for breast reconstruction parallels that of shoppable procedures within other medical and surgical specialties.^{20,22,23,24,25,26,27,29,30} In comparison with prior studies of otolaryngology procedures that used similar methodology to quantify variability in commercial price,^20,21 the range of across-hospital ratios was comparable (breast reconstruction, 4.5-18.3 vs Wang et al,²⁰ 3.5-18.6) and slightly lower for within-hospital ratios (breast reconstruction 1.6-2.5 vs Wang et al,²⁰ 2.7-5.4), though nonetheless substantial. Overall, this suggests that privately insured patients are paying markedly different prices for breast reconstruction depending on their insurer, plan, and hospital.

Variation in commercial payer-negotiated rates may result from hospital- or market-specific factors. Hospitals that provide higher-quality care, offer more complex services, have a more widely recognized institutional reputation, and/or use new technologies may leverage these qualities to negotiate higher commercial prices,²⁰ although, generally, higher price has not been associated with quality.⁴⁹ Hospitals that have greater market power may negotiate higher commercial rates irrespective of cost or quality of care as insurers struggle to bargain in concentrated hospital markets. Economists and physicians alike have sought to elucidate the association between hospital competition and commercial prices with mixed results. Although leading studies support the argument that consolidations and subsequent reduced competition lead to higher prices,^50,51,52,53 others contest that consolidations generate efficiencies that result in lower prices.^54,55 These opposing viewpoints are central to debates regarding Mass General Brigham’s proposed expansion in the Boston area and the lawsuit filed against Sutter alleging violation of antitrust laws in Northern California.^56,57 In both scenarios, opponents cite concerns regarding rising health care prices secondary to consolidation, whereas the health systems argue that the expansions facilitate higher quality and lower cost of care.

Our results suggest that greater hospital market concentration (ie, less competition) was associated with higher commercial payer–negotiated rates for breast reconstructive services. Based on our modeling, hospitals in markets with an HHI between 1501 and 2500 had commercial rates that averaged $4037.52 more than markets with an HHI of 1500 or less. There was a less pronounced jump comparing hospital markets with an HHI of greater than 2500 to those with an HHI of 1500 or less, suggesting that once a market is concentrated within the 1501 to 2500 range, adding more concentration is not associated with a linear increase in rate. Higher prices in more concentrated markets may ultimately be passed down to patients in the form of higher premiums and deductibles. Existing studies using HHI as a measure of market concentration in breast reconstruction have shown that HHI is associated with an increased odds of immediate breast reconstruction and of breast reconstruction with a free flap.^58,59 In terms of the association with commercial rates, Cerullo et al⁶⁰ found that for privately insured patients who undergo breast reconstruction, increasing market concentration (ie, increasing HHI) was associated with decreasing costs and procedural markup (ie, proportional difference between charges and average procedural costs).⁶⁰ This study was limited, however, by using Healthcare Cost and Utilization Project data based on cost-to-charge ratios, which have questionable accuracy. Based on their findings, the authors suggest that the unique needs of the patient with breast cancer, particularly the need for multidisciplinary care, translate into efficiency gains in consolidated markets. In contrast, our finding that commercial rates for breast reconstructive services increased in association with decreasing market competition concurs with dominant economic theory and contemporary examples, such as the anticompetitive pricing behavior of Sutter Health,⁵⁷ suggesting that hospitals prioritize profit over efficiency gains. Overall, this implies that the trend of increasing hospital market concentration may not be in the best interest of the patient with breast cancer.

Our analysis additionally demonstrates significant positive associations between commercial rates and both self-pay and Medicaid rates. There was also a significant positive association of commercial price with list price, though the magnitude of the coefficient suggests a weak association, consistent with prior investigations that list price loosely follows but generally is unrepresentative of true prices.^3,4,61 Cost shifting describes a theoretical relationship between commercial and public payer rates, in which hospitals raise prices for private payers to offset shortfalls in payments from Medicare and Medicaid.³⁶ The health economic literature contains weak empirical support for this theory, demonstrating a small or nonexistent effect of payer composition on commercial rates in general.^36,62,63,64 In plastic surgery, this is relevant given decreasing Medicare reimbursements and highly variable Medicaid reimbursements with often unexplained discounts.^{2,34,35,65,66} Given the positive and insignificant correlations of Medicaid and Medicare rates with commercial rates for breast reconstruction, respectively, our data provide no evidence to suggest that hospitals shift costs across private and public payers. In addition, teaching status and population density were not significantly associated with commercial rates in our analysis. Extra-large hospitals (400+ bed count) were associated with higher commercial rates compared with extra-small hospitals (6-49 bed count); other size comparisons to the extra-small reference were not significant, suggesting that only very large institutions may realize the size-based boost in commercial rate negotiation. Nonprofit and safety-net hospitals were associated with significantly lower commercial rates compared with for-profit and nonsafety net peer institutions; additional research is needed to explore why these hospital characteristics may translate into diminished negotiating power with commercial insurers.

Limitations

The main limitation of this study is a high nationwide nondisclosure rate due to noncompliance with the Price Transparency Rule. As of June 2021, 55% of 3558 Medicare-certified general acute care hospitals were noncompliant.³⁹ This high degree of noncompliance may be related to the inconsequential penalty of $300 per day for nondisclosure, which could be a worthwhile trade-off for hospitals that charge higher prices.^21,27,39 Although this has the potential to introduce selection bias, a study sampling 100 random hospitals and 100 highest-revenue hospitals found that 83% and 75%, respectively, were noncompliant with at least 1 requirement, thus suggesting that such bias is minimal.⁶⁷ In addition, Turquoise Health data are relatively new and lack rigorous external validation. This study is cross-sectional in nature, and thus, our findings do not imply causality. In the future, it may be possible to compare negotiated rates before and after market consolidation to test the hypothesis of whether negotiated payer rates increase after hospital mergers. Additionally, our study lacks data regarding hospital outcomes and equity measures, and thus we are unable to test for associations between commercial prices and such metrics. By introducing commercial pricing data to the surgery literature, we hope to inspire future investigators to examine whether commercial pricing behavior is congruent with public payer value-based health care reforms.

Conclusions

Results of this cross-sectional analysis of 69 834 commercial payer-negotiated rates for breast reconstructive services suggest substantial variation within hospitals, across hospitals, and across reconstructive methods. Commercial prices increased in association with increasing hospital market consolidation, and thus privately insured patients with breast cancer may see higher premiums and deductibles as the US hospital market consolidation continues to grow. Policy considerations may include disruption of highly concentrated markets as a means of lowering the cost of health care. Commercial insurance rates did not increase in relation to lower public payer rates, suggesting that facilities do not offset lower Medicaid and Medicare rates with higher negotiated commercial rates. Instead, it appears facilities maximize commercial rates regardless of public payer rates. Future studies should continue to investigate drivers of commercial prices in surgery, with the ultimate objective of facilitating cost-based competition and reducing the cost of health care.

Supplement.

eFigure. Flowchart of Data Set Construction

eTable. Current Procedural Terminology (CPT) Codes for Reconstructive Breast Procedures in Study