Plots show adjusted differences in the out-of-network unit price between each treated state and control group relative to the date on which the law was passed; error bars represent 95% CIs for the point estimates in each quarter (calculated using standard errors clustered by physician); the y-axis is rescaled by the difference in the mean unit price between treatment and control states in the reference period (first quarter [Q1] 2014) when the mean out-of-network unit prices compared with control states were: –$51.69 in California, +$110.54 in Florida, and +$16.52 in New York; and vertical lines within the graphs indicate the time period between the law's passage (orange) and its effective date (blue): California, Q4 2016 and Q3 2017; Florida, Q2 2016 and Q3 2016; New York, Q2 2014 and Q2 2015).
Plots show adjusted differences in the in-network unit price between each treated state and the control group relative to the date on which the law was passed; error bars represent 95% CIs for the point estimates in each quarter (calculated using standard errors clustered by physician); the y-axis is rescaled by the difference in the mean unit price between treatment and control states in the reference period (first quarter [Q1] 2014) when mean in-network unit prices compared to control states were –$2.92 in California, +$3.70 in Florida, and +$11.39 in New York; and vertical lines between panels indicate the time period between the law's passage and its effective date (California, Q4 2016 and Q3 2017; Florida, Q2 2016 and Q3 2016; New York, Q2 2014 and Q2 2015).
eMethods 1. Data and Sample Details
eMethods 1.1 State Sample
eMethods 1.2 Claims Sample
eFigure1. Sample Selection
eMethods 1.3 Unit Price Calculation
eMethods 2. Estimating Equations and Identification
eMethods 3. Summary Statistics and Additional Results
eTable 1. Descriptive Statistics for Treatment and Control States, 2014-2017
eTable 2. Adjusted Differences in Unit Prices Between California and Control States
eTable 3. Adjusted Differences in Unit Prices Between Florida and Control States
eTable 4. Adjusted Differences in Unit Prices Between New York and Control States
eTable 5. Changes in Unit Prices Before and After States Introduced Comprehensive Surprise-Billing Legislation: Accounting for Anticipatory Effects in California and Florida
eFigure 2. Adjusted Differences in Unit Prices Paid to Out-of-Network Anesthesiologists at In-Network Facilities Between Treatment and Control States: Accounting for Anticipatory Effects in California and Florida
eFigure 3. Adjusted Differences in Unit Prices Paid to In-Network Anesthesiologists Between Treatment and Control States: Accounting for Anticipatory Effects in California and Florida
eMethods 4. Sensitivity Analysis
eTable 6. Changes in Unit Prices Before and After States Introduced Comprehensive Surprise-billing legislation: With Patient Controls
eTable 7. Changes in Unit Prices Before and After States Introduced Comprehensive Surprise-billing legislation: Balanced Physician Panel
eTable 8. Changes in Unit Prices Before and After States Introduced Comprehensive Surprise-billing legislation: Fully-Insured vs Self-Funded Plans
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La Forgia A, Bond AM, Braun RT, Kjaer K, Zhang M, Casalino LP. Association of Surprise-Billing Legislation with Prices Paid to In-Network and Out-of-Network Anesthesiologists in California, Florida, and New York: An Economic Analysis. JAMA Intern Med. 2021;181(10):1324–1331. doi:10.1001/jamainternmed.2021.4564
What is the association of state surprise-billing legislation with prices paid to anesthesiologists in hospital outpatient departments and ambulatory surgery centers?
This retrospective economic analysis of more than 2.5 million claims filed for patients with private health insurance who received anesthesia services in hospital outpatient departments and ambulatory surgery centers from 2014 to 2017 found that prices paid to out-of-network anesthesiologists at in-network facilities and to in-network anesthesiologists decreased in California, Florida, and New York after each state passed comprehensive surprise-billing legislation.
State surprise-billing legislation appears to directly lower out-of-network prices and indirectly lower in-network prices by changing payer-practitioner negotiating dynamics.
Several states have passed surprise-billing legislation to protect patients from unanticipated out-of-network medical bills, yet little is known about how state laws influence out-of-network prices and whether spillovers exist to in-network prices.
To identify any changes in prices paid to out-of-network anesthesiologists at in-network facilities and to in-network anesthesiologists before and after states passed surprise-billing legislation.
Design, Setting, and Participants
This retrospective economic analysis used difference-in-differences methods to compare price changes before and after the passage of legislation in California, Florida, and New York, which passed comprehensive surprise-billing legislation between January 1, 2014, and December 31, 2017, to 45 states that did not. Commercial claims data from the Health Care Cost Institute were used to identify prices paid to anesthesiologists in hospital outpatient departments and ambulatory surgery centers. The final analytic sample comprised 2 713 913 anesthesia claims across the 3 treated states and the 45 control states.
Temporal and state-level variation in exposure to surprise-billing legislation.
Main Outcomes and Measures
The unit price (allowed amounts standardized per unit of service) paid to out-of-network anesthesiologists at in-network facilities and to in-network anesthesiologists.
This retrospective economic analysis of 2 713 913 anesthesia claims found that after surprise-billing laws were passed in 3 states, the unit price paid to out-of-network anesthesiologists at in-network facilities decreased significantly in 2 of them: California, −$12.71 (95% CI, −$25.70 to −$0.27; P = .05) and Florida, −$35.67 (95% CI, −$46.27 to −$25.07; P < .001). In New York, a decline in the overall out-of-network price was not statistically significant (−$7.91; 95% CI, −$17.48 to −$1.68; P = .10); however, by the fourth quarter of 2017, the decline was −$41.28 (95% CI, −$70.24 to −$12.33; P = .01). In-network prices decreased in California by −$10.68 (95% CI, −$12.70 to −$8.66; P < .001); in Florida, −$3.18 (95% CI, −$5.17 to −$1.19; P = .002); and in New York, −$8.05 (95% CI, −$11.46 to −$4.64; P < .001).
Conclusions and Relevance
This retrospective study found that prices paid to in-network and out-of-network anesthesiologists in hospital outpatient departments and ambulatory surgery centers decreased after the introduction of surprise-billing legislation, providing early insights into how prices may change under the federal No Surprises Act and in states that have recently passed their own legislation.
On December 18, 2020, the US Congress passed the No Surprises Act to protect patients from surprise medical bills, which occur when an individual unknowingly receives care from an out-of-network practitioner at an in-network health care facility.1 In addition to protecting patients from financial liability for surprise medical bills, the law also established a method of determining payments made by a patient’s insurer to the out-of-network practitioner. The No Surprises Act requires that insurers and practitioners first negotiate out-of-network rates. If negotiations are unsuccessful, they may proceed to a federal independent dispute resolution (IDR) process in which each party submits a price, and an arbiter decides using the insurer’s median in-network rate as a benchmark.2
The federal No Surprises Act was enacted after 18 states had already implemented comprehensive surprise-billing legislation; therefore, it defers to the states’ provider payment rules for out-of-network practitioners at in-network facilities.1,3 Several states, such as New York and Texas, adopted a dispute resolution process similar to that of the federal legislation but with higher price benchmarks to guide arbiter decision-making, which raises concerns that out-of-network payments may actually increase under the law.4 Other states, such as California and Florida, developed payment standards that ranged from basing payments on in-network or Medicare rates to the usual and customary charges for similar services.5 If state provider payment rules are effective in lowering the prices paid for out-of-network care, they may also influence in-network prices by altering practitioners’ negotiating leverage and incentives to remain out-of-network.6
Anesthesiology is among the specialties with the highest proportion of potential surprise bills because patients do not usually choose an anesthesiologist.7,8 In this study, we used commercial claims data to explore the association between state surprise-billing legislation and prices paid to out-of-network anesthesiologists at in-network facilities, and the potential spillovers onto prices paid to in-network anesthesiologists. We focused on nonemergency anesthesia services provided in hospital outpatient departments and ambulatory surgery centers (ASCs).
This retrospective economic analysis used Health Care Cost Institute (HCCI) commercial claims data for patients who received anesthesia services in hospital outpatient departments and ASCs between January 1, 2014, and December 31, 2017, to compare prices changes before and after the passage of surprise billing laws in California, Florida, and New York with states that had not passed such legislation. The institutional review board of Weill Cornell Medical College reviewed and approved the analysis and waived the need for informed consent because only deidentified data were used.
Before 2018, only 6 states had passed comprehensive legislation to protect patients from surprise bills: California, Connecticut, Florida, Illinois, Maryland, and New York. We excluded Connecticut from the analysis because the number of out-of-network claims was insufficient to accurately calculate prices; and Illinois and Maryland because they passed laws before the study period (ie, before 2014). Therefore, the treated sample comprised California, Florida, and New York, and 45 control states, which included all remaining US states and the District of Columbia. Following prior research,9 we defined a state’s surprise-billing law as comprehensive if it included emergency and nonemergency services applied to both Health Maintenance Organizations (HMOs) and Preferred Provider Organization/Point-of-Service (PPO/POS) plans, held patients harmless from extra practitioner charges and prohibited balance billing, and adopted a rule or dispute resolution process to determine how insurers would pay out-of-network practitioners at in-network facilities.9 See eMethods 1.1 in the Supplement for details.
While the surprise-billing laws passed by California, Florida, and New York are similar, they differ in their methods for determining prices paid to practitioners for out-of-network services. Table 1 summarizes the provider payment rules that apply to nonemergency services for patients with PPO/POS plans. California established a payment standard where the insurer pays the greater of 125% of Medicare or the average in-network rate paid by the insurer for that region.3 Florida established a payment standard where the insurer reimburses the lesser of: (1) the practitioner’s charges (the price for a given billing code); (2) the usual and customary practitioner charges for similar services; or (3) the charge mutually agreed to by the insurer and practitioner.3 New York implemented a dispute resolution process where insurers establish a reasonable payment amount and disagreements are resolved via arbitration.9 New York law established the 80th percentile of billed charges (calculated by FAIR Health, fairhealthconsumer.org) as the benchmark for reasonable payment in the IDR process, often several times higher than the in-network negotiated rates.4 Therefore, differences in surprise-billing legislation across states may lead to variation in prices paid to out-of-network practitioners.
To calculate prices paid to anesthesiologists, we used patient-level commercial claims data from the HCCI between 2014 and 2017, which includes claims from Aetna, Humana, and UnitedHealthcare. The HCCI data provides an indicator for the network status of both the practitioner and facility, allowing for identification of claims by in-network practitioner and by out-of-network practitioner at in-network facilities.
The final analytic sample comprised 2 713 913 claims, including all anesthesia procedures performed by an in-network or out-of-network practitioner at a hospital outpatient department or ASC, identified by current procedural terminology (CPT) codes 00100-01999 with base units assigned by the Centers for Medicare & Medicaid Services (CMS). As shown in eFigure 1 of the Supplement, we excluded claims for anesthesia services provided to patients with HMO plans (n = 334 919), procedures that involved more than 1 anesthesiology claim (n = 260 765), claims with time units at the top or bottom 1 percent of the distribution (n = 49 965), claims with negative allowed amounts (n = 1344), and claims with missing network status (n = 118 133). See eMethods 1.2 in the Supplement for more details on the sample. We excluded HMOs because they are subject to different provider payment rules under state surprise-billing legislation.3 This study included patients who are in self-insured and fully-insured plans, even though the Employee Retirement Income Security Act prohibits application of the surprise-billing laws to self-insured plans. This decision is supported by previous research that suggests strong spillover effects between plan types10 and by this study’s sensitivity analysis, which showed qualitatively similar results for self-funded and fully-insured plans.
We measured prices paid to in-network anesthesiologists and out-of-network anesthesiologists at in-network facilities using allowed amounts that are equal to the sum of the actual amount paid by the insurer to the practitioner plus the patient-cost share, if any. For in-network anesthesiologists, the allowed amount represents the contracted price between the insurer (payer) and anesthesiologist. For out-of-network anesthesiologists in states with no surprise-billing legislation, the allowed amount represents the price that the health plan was willing to pay and in states with surprise-billing legislation, it represents the price that the health plan would pay according to the state’s provider payment rules. While it is not possible to identify surprise bills in claims data, we used claims for services provided by out-of-network anesthesiologists at in-network facilities to identify instances that could produce a surprise bill.
We geographically adjusted the allowed amounts using the CMS Geographic Variation Public Use File (cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Medicare-Geographic-Variation/GV_PUF) and converted prices to 2017 dollars using the US Bureau of Labor Statistics Consumer Price Index (bls.gov/news.release/cpi.toc.htm). Then we converted the allowed amounts into a single unit price (also known as the conversion factor) because in anesthesiology, contract negotiations are based on the price paid per unit of service (eMethods 1.3 in the Supplement). The unit price standardizes payment across all procedures according to procedure complexity (base units), length of time (time units), and a patient’s health status (modifying units). Therefore, the unit price captures the price paid to anesthesiologists irrespective of patient risk status, procedure type, or procedure length. Time units and modifying units are reported per claim in the HCCI data. Base units are assigned to anesthesia CPT codes by CMS11 and capture anesthesia procedure complexity, risk, and skill requirements. Anesthesia time is measured continuously from the start of an anesthesia service to the end, with each 15-minute interval representing 1 time unit. Modifying units account for a patient’s preanesthesia medical comorbidities reported on a scale of 1 to 6. We winsorized unit prices at the top and bottom 0.5 percent to limit the influence of idiosyncratically high or low unit prices.
We used linear regression and a difference-in-differences approach to measure the differential change in prices paid to anesthesiologists in states that passed comprehensive surprise-billing legislation (California, Florida, and New York) to 45 states that did not.9 For both in-network and out-of-network prices, a separate regression was run between each treated state and the set of control states. The key explanatory variable of interest was an indicator for when the state’s surprise-billing legislation became operative and enforceable, referred to as the effective date. We also included an indicator to control for the period the date the law was passed and its effective date (ie, the transition period). We adjusted for physician and quarter-year fixed effects to account for secular variation and time-invariant differences across physicians during the study period. Standard errors were clustered at the physician level. P values were 2-tailed and statistical significance was defined as P < .05. Statistical analyses were performed using Stata, release 16.0 (StataCorp LLC).
To address concerns that the patient physical status score may not fully account for differences in patient risk, the sensitivity analysis included controls for patient age, sex, and indicators for the 30 comorbidities in the Elixhauser Comorbidity Index.12 We also conducted analysis using a balanced sample of physicians to account for compositional changes in the practitioner population and conducted subsample analysis that compared prices paid in fully-insured with self-funded plans to validate combining the different plan types.
The key assumption of our difference-in-differences model is that the treatment and control states would have had similar trends in prices in the absence of the surprise-billing legislation. To assess whether trends in the period before legislation were not meaningfully different, we graphed coefficients from interaction terms between indicators for each quarter relative to the passage of the law and an indicator for whether the state passed a surprise-billing law. Since payer-practitioner negotiations could occur in anticipation of a state passing the law, we also conducted analyses using interactions with indicators relative to the quarter during which the law was introduced to the state legislature. The first quarter of 2014 was set as the omitted category; therefore, the coefficients on the interaction terms describe changes in prices relative to this reference period.13 For New York, we were unable to identify preexisting differential trends because the data set includes only 1 quarter before the legislation was passed. See eMethods 2 in the Supplement for more details on the statistical analysis
Summary statistics for the sample are presented in eMethods 3 of the Supplement (see eTable 1) and show that patient characteristics are similar between treatment and control states. Because the unit price represents allowed amounts standardized by base units, time units, and patient physical status scores, it takes into account any changes in procedure type, duration, and patient health status before and after the laws.
Table 2 shows adjusted differential changes in unit prices relative to control states. After the laws’ effective dates, prices paid to out-of-network anesthesiologists at in-network facilities decreased by −$12.71 (95% CI, −$25.70 to $0.27; P = .05) in California and by −$35.67 (95% CI,−$46.27 to −$25.07; P < .001) in Florida, while the differential change was negative (−$7.91) but not statistically significant in New York (95% CI, −$17.48 to $1.68; P = .10). In-network prices decreased by −$10.68 (95% CI, −$12.70 to −$8.66; P < .001), −$3.18 (95% CI, −$5.17 to −$1.19; P = .002) and −$8.05 (95% CI, −$11.46 to -−$4.64; P < .001), in California, Florida and New York, respectively. To put these unit prices in context, for a routine colonoscopy provided by an in-network anesthesiologist, allowed amounts decreased by 10.8% (−$74.36), 3.2% (−$23.29), and 7.4% (−$58.92) relative to the before-law period in California, Florida, and New York, respectively (see the calculation in eMethods 1.3 of the Supplement).
Figure 1 and Figure 2 plot estimates of adjusted price differences between treatment and control states relative to the fiscal quarter during which a state’s law was passed (coefficient estimates and 95% CIs are reported in eTables 2-4 in the Supplement). Compared with control states, out-of-network prices in California started to decline in the first quarter after the law was passed and continued to decline in subsequent quarters (Figure 1; eTable 2 in the Supplement). However, Figure 2 shows that in-network prices sharply declined 3 quarters before the law was passed (−$7.41; 95% CI, −$10.90 to −$3.91; P < .001); eTable 2 in the Supplement) and continued to decline after the law’s effective date. In Florida, there is also evidence of a small, although not statistically significant, anticipatory decline in the quarter before the law was passed for both out-of-network prices (−$2.60 (95% CI, −$17.87 to $12.67; P = .74); eTable 3 in the Supplement) and in-network prices (−$0.97; 95% CI, −$4.51 to $2.56; P = .59); eTable 3 of the Supplement). The early price declines in California coincided with the reintroduction of the bill in the state senate after a previous version had failed. In Florida, the early price declines coincided with the quarter during which the surprise-billing legislation was first introduced to the state house of representatives. If practitioners and insurers believed this legislation would pass, they may have been motivated toward preemptive contract negotiations. Because anticipatory effects would invalidate the difference-in-differences assumption of no preexisting trends, eTable 5 and eFigures 2 and 3 in the Supplement present results of the analyses for California and Florida using the quarter during which the law was introduced to the state legislature.14 Observed price declines are not statistically different compared with the main results and provide evidence that unit prices evolved similarly between treatment and control states before the state introduced surprise-billing legislation.
In New York, the short study period before the law precluded evaluation of preexisting price trends; however, relative to the quarter before the law, in the third, fourth, and fifth quarters after the law was passed, prices paid to out-of-network anesthesiologists increased and only began to decline in the 11th quarter (−$31.07; 95% CI, −$53.53 to −$8.62; P = .007; eTable 4 in the Supplement). Price declines for in-network prices followed a similar pattern (Figure 2; eTable 4 in the Supplement): significant declines were not observed until the seventh quarter after the law was passed (−$9.01; 95% CI, −12.73 to −5.29; P < .001; eTable 4 in the Supplement).
Results shown in Table 2 were robust to the sensitivity tests described in eMethods 4 of the Supplement (see eTables 6 and 7). We also found that the state surprise-billing laws were associated with price changes for self-funded plans (eTable 8 in the Supplement): price declines were qualitatively similar for both self-funded and fully-insured plans after the law’s effective date, although as expected, out-of-network price declines were larger for fully-insured plans.
California, Florida, and New York saw reductions in prices paid to anesthesiologists in hospital outpatient departments and ASCs after passing comprehensive surprise-billing legislation. In-network prices decreased in the 3 states compared with control states, providing evidence of an association between these laws and payer-practitioner negotiating dynamics. The 3 states also had declines in prices paid to out-of-network anesthesiologists at in-network facilities, although the timing and magnitude of price declines varied, likely reflecting each state’s provider payment rules for out-of-network services.9,10 These results only apply to PPO/POS plans and would differ for HMO plans because HMOs do not cover out-of-network care; however, when states pass surprise-billing legislation, insurers are required to cover surprise medical bills for patients with an HMO plan.
California established a payment standard tied to Medicare or the insurer’s average in-network rate. After the effective date of California’s surprise-billing law, out-of-network prices declined by 13.6% and in-network prices by 10.8% . However, even before the law, mean out-of-network prices were consistently below in-network prices (Table 2; $93.20 vs $99.31). Consequently, practitioners have heavily criticized California’s benchmark for being too low and giving insurers too much negotiating leverage, which according to a survey by the California Medical Association led to contracting difficulties, including the sudden termination of long-standing contracts.15 California also had a lengthy process to pass surprise-billing legislation. The initial effort narrowly failed in late 2015; it was then updated and reintroduced as part of a new bill in 2016.16,17 Consistent with Figure 2, insurers may have anticipated that this new payment standard would pass, and thus renegotiated contracts with lower in-network payment rates in the interim. The experience of practitioners in California led to substantial lobbying by the California Medical Association for the federal No Surprises Act to adopt an IDR process similar to that of New York, rather than a payment standard.18
Florida also established a payment standard based on the lesser of several options, including the usual and customary practitioner charges for similar services. Compared with California and New York, Florida saw the largest decline in out-of-network prices (17.4%) and the smallest decline in in-network prices (3.2%). However, as seen in Table 2, out-of-network prices were twice as large as in-network prices before the law was passed (Table 2, $204.87 vs $100.74). A potential reason for the relatively small in-network decline is that after the law was passed, the out-of-network unit prices remained markedly higher than the in-network prices, so anesthesiologists continued to have an incentive to remain out of network.
Instead of a payment standard, New York implemented an IDR process. Recent research suggests that this process may lead to higher prices by using 80% of billed charges as a benchmark in the arbitration decision.2,4 We found that out-of-network prices decreased by 5.1% after the effective date, but that this aggregated difference obscured changes in out-of-network prices over time. Out-of-network prices initially increased, but then declined nearly 3 years later. Prices may have initially increased because of the 80% benchmark and very few cases underwent IDR, but then prices adjusted downwards as insurers and practitioners gained more experience with the process.19 The eventually lower out-of-network prices also coincided with a 7.4% decline in in-network prices, consistent with recent research on surprise bills in New York emergency departments.6
This study had several limitations. First, while the HCCI data includes claims from 3 of the largest US insurers, it does not include all commercial claims, so these results may not generalize to other insurers. Second, because the data set includes only claims for 2014 to 2017, we observed short before-law and after-law periods. In New York, there was only 1 quarter in the study period before the law was passed, and so we are unable to assess the extent of preexisting trends compared with control states. In California, there were only 2 quarters in the after-law period, although declines in prices were observed during the transition period (after passage and before the effective date). Third, we excluded HMO claims and so did not measure price changes for all anesthesiologists after the surprise-billing legislation. Lastly, these results may not generalize to other specialties and health care service settings.
In California, Florida, and New York, prices paid to anesthesiologists in hospital outpatient departments and ASCs decreased after these states passed surprise-billing legislation. Their experience offers early insights into how prices may change under the federal No Surprises Act and in states that have recently passed their own legislation.
Accepted for Publication: June 26, 2021.
Published Online: August 16, 2021. doi:10.1001/jamainternmed.2021.4564
Corresponding Author: Ambar La Forgia, PhD, Department of Health Policy and Management, Mailman School of Public Health, Columbia University, 722 W 168th St, Room 475, New York, NY 10032 (email@example.com).
Author Contributions: Dr La Forgia had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: La Forgia, Braun, Kjaer, Casalino.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: La Forgia, Zhang.
Critical revision of the manuscript for important intellectual content: La Forgia, Bond, Braun, Kjaer, Casalino.
Statistical analysis: La Forgia, Bond, Braun, Zhang.
Obtained funding: La Forgia, Bond, Casalino.
Supervision: Kjaer, Casalino.
Conflict of Interest Disclosures: Dr Bond reports grants from The Commonwealth Fund outside the submitted work. Dr Braun reports grants from Arnold Ventures outside the submitted work. Dr Casalino reports personal fees from the American Medical Association outside the submitted work. No other disclosures were reported.
Funding/Support: This research was supported by Arnold Ventures, The Commonwealth Fund, and the Physician’s Foundation Center for the Study of Physician Practice and Leadership at Weill Cornell Medicine.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: The views presented here are those of the authors and not necessarily those of Arnold Ventures, The Commonwealth Fund, or the Physicians Foundation Center. Neither organization had a role in the design or interpretation of the study.
Additional Contributions: The authors acknowledge the assistance of the Health Care Cost Institute and its data contributors (Aetna, Humana, and UnitedHealthcare) in providing the claims data analyzed in this study. We thank Leah Yao, BA (Weill Cornell Medical College), for researching and compiling information on state surprise-billing legislation. Ms Yao was supported by The Commonwealth Fund.