Association of Physician Management Companies and Private Equity Investment With Commercial Health Care Prices Paid to Anesthesia Practitioners

Ambar La Forgia; Amelia M Bond; Robert Tyler Braun; Leah Z Yao; Klaus Kjaer; Manyao Zhang; Lawrence P Casalino

doi:10.1001/jamainternmed.2022.0004

. 2022 Feb 28;182(4):396–404. doi: 10.1001/jamainternmed.2022.0004

Association of Physician Management Companies and Private Equity Investment With Commercial Health Care Prices Paid to Anesthesia Practitioners

Ambar La Forgia ^1,^✉, Amelia M Bond ², Robert Tyler Braun ², Leah Z Yao ², Klaus Kjaer ³, Manyao Zhang ², Lawrence P Casalino ²

¹Department of Health Policy and Management, Mailman School of Public Health, Columbia University, New York, New York

²Division of Health Policy and Economics, Department of Population Health Sciences, Weill Cornell Medical College, New York, New York

³Department of Anesthesiology, Weill Cornell Medical College, New York, New York

Accepted for Publication: January 1, 2022.

Published Online: February 28, 2022. doi:10.1001/jamainternmed.2022.0004

^✉

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 (al4048@cumc.columbia.edu).

Author Contributions: Dr La Forgia and Ms Zhang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: La Forgia, Bond, Braun, Kjaer, Casalino.

Acquisition, analysis, or interpretation of data: La Forgia, Bond, Braun, Yao, Zhang, Casalino.

Drafting of the manuscript: La Forgia, Yao, Kjaer.

Critical revision of the manuscript for important intellectual content: La Forgia, Bond, Braun, Kjaer, Zhang, Casalino.

Statistical analysis: La Forgia, Bond, Braun, Zhang.

Obtained funding: La Forgia, Bond, Casalino.

Administrative, technical, or material support: La Forgia, Bond, Braun, Yao.

Supervision: Casalino.

Conflict of Interest Disclosures: Dr Bond reported receiving grants from the Commonwealth Fund outside the submitted work. Dr Braun reported receiving grants from Arnold Ventures outside the submitted work. Dr Casalino reported receiving personal fees from the American Medical Association Advisory Committee on Professional Satisfaction and Practice Sustainability outside the submitted work. No other disclosures were reported.

Funding/Support: This research was supported by the Physicians Foundation Center for the Study of Physician Practice and Leadership at Weill Cornell Medical College, Arnold Ventures, and the Commonwealth Fund.

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 the Physicians Foundation Center, Arnold Ventures, or the Commonwealth Fund.

Additional Contributions: The authors acknowledge the assistance of the HCCI and its data contributors, Aetna, Humana, and UnitedHealthcare, in providing the claims data analyzed in this study. The authors also thank Jin Kim (Weill Cornell Medicine) and Shruti Kanna (Cornell University) for assisting in the database construction.

^✉

Corresponding author.

PMCID: PMC8886444 PMID: 35226052

This cohort study assesses changes in prices paid to practitioners (anesthesiologists and certified registered nurse anesthetists) before and after an outpatient facility contracted with a physician management company.

Key Points

Question

What is the association between outpatient facilities that contract with physician management companies (PMCs) and prices paid to anesthesia practitioners?

Findings

This cohort study of 2 255 933 privately insured patients who received anesthesia services in hospital outpatient departments and ambulatory surgery centers from 2012 to 2017 found that allowed amounts and unit prices increased by 16.5% and 18.7%, respectively, when facilities contracted with a PMC relative to non-PMC facilities. Larger increases were found if the PMC received private equity investment.

Meaning

In this study, PMCs appeared to negotiate significantly higher prices for anesthesia services, raising concerns that upward pressure on prices may lead to higher insurance premiums and patient cost-sharing.

Abstract

Importance

Physician management companies (PMCs), often backed by private equity (PE), are increasingly providing staffing and management services to health care facilities, yet little is known of their influence on prices.

Objective

To study changes in prices paid to practitioners (anesthesiologists and certified registered nurse anesthetists) before and after an outpatient facility contracted with a PMC.

Design, Setting, and Participants

This retrospective cohort study used difference-in-differences methods to compare price changes before and after a facility contracted with a PMC with facilities that did not and to compare differences between PMCs with and without PE investment. Commercial claims data (2012-2017) from 3 large national insurers in the Health Care Cost Institute database were combined with a novel data set of PMC facility contracts to identify prices paid to anesthesia practitioners in hospital outpatient departments and ambulatory surgery centers. The cohort included 2992 facilities that never contracted with a PMC and 672 facilities that contracted with a PMC between 2012 and 2017, collectively representing 2 255 933 anesthesia claims.

Exposures

Temporal variation in facility-level exposure to PMC contracts for anesthesia services.

Main Outcomes and Measures

Main outcomes were (1) allowed amounts and the unit price (allowed amounts standardized per unit of service) paid to anesthesia practitioners; and (2) the probability that a practitioner was out of network.

Results

From before to after the PMC contract period, allowed amounts increased by 16.5% (+$116.39; 95% CI, $76.11 to $156.67; P < .001), and the unit price increased by 18.7% (+$18.79; 95% CI, $12.73 to $24.84; P < .001) in PMC facilities relative to non-PMC facilities. Results did not show evidence that anesthesia practitioners were moved out of network (+2.25; 95% CI, −2.56 to 7.06; P < .36). In subsample analyses, PMCs without PE investment increased allowed amounts by 12.9% (+$89.88; 95% CI, $42.07 to $137.69; P < .001), while PE-backed PMCs (representing half of the PMCs in the sample) increased allowed amounts by 26.0% ($187.06; 95% CI, $133.59 to $240.52; P < .001). Similar price increases were observed for unit prices.

Conclusions and Relevance

In this cohort study, prices paid to anesthesia practitioners increased after hospital outpatient departments and ambulatory surgery centers contracted with a PMC and were substantially higher if the PMC received PE investment. This research provides insights into the role of corporate ownership in health care relevant to policy makers, payers, practitioners, and patients.

Introduction

Physician management companies (PMCs) are an example of the increasing corporatization of medicine in the US.¹ A PMC is a privately held or publicly traded for-profit company that manages the back-end administrative functions of medical practices, such as insurance contracting and billing. Many PMCs, often referred to as staffing companies, also contract with hospitals and ambulatory surgery centers (ASCs) to provide professional staffing and management services. This type of PMC is particularly common in anesthesiology.^2,3 The 8 largest anesthesia-focused PMCs employ nearly 22% of the anesthesia practitioners in the US.⁴ The growth of these PMCs is partly driven by investments from private equity (PE) firms attracted to the high volume and high margins of anesthesiology⁵: anesthesia is administered during 100 million surgical procedures annually, and the industry is valued at more than $26.2 billion.^{6,7,8,9,10,11}

Health care facilities can choose to employ anesthesia practitioners or outsource to an independent anesthesia group or a PMC. From the facility’s perspective, outsourcing relieves the burden of recruiting practitioners, managing the complexity of anesthesia billing, and scheduling anesthesia coverage of the operating rooms.^12,13,14 Most PMCs argue that they have the size, infrastructure, and managerial expertise needed to increase facility revenue and decrease costs.^15,16,17

To gain facility contracts, PMCs can either acquire an anesthesia group and take over the group’s existing facility contracts, or they can submit bids on facility requests for proposals.¹⁸ After winning a contract bid, PMCs may employ some or all of the existing anesthesia practitioners in the facility, fill positions using practitioners already employed by the PMC, or a combination of both.^16,19 A practitioner may choose to join a PMC to reduce administrative responsibilities and receive the economic benefits of a larger organization, such as greater income stability, particularly given recent concerns of underpayment from large insurance companies.^20,21

Health care delivery might be influenced by PMCs in several ways. When a PMC begins providing services in a facility, the PMC typically renegotiates payer contracts.^19,22 They might leverage their market power to negotiate higher payment rates from insurers, benefiting practitioners but potentially increasing prices for commercially insured patients.^23,24,25,26 Additionally, PMCs might command higher prices by threatening to move their practitioners out of network, though recent legal disputes suggest large insurers might also cancel in-network contracts with PMCs because of cost concerns.^27,28,29,30 By standardizing care and improving managerial processes, PMCs might also be able to increase quality and lower costs.^31,32

This study combined commercial claims data with a novel data set of PMC facility contracts to assess (1) whether prices paid to anesthesiologists and certified registered nurse anesthetists (CRNAs) changed after a hospital outpatient department or ASC contracted with a PMC; (2) whether practitioners moved out of network after a PMC contract; and (3) whether differences existed between facilities that contracted with PMCs with and without PE investment.

Methods

Study Design

We used a difference-in-differences design to compare changes in prices and a practitioner’s out-of-network status before and after a facility contracted with a PMC to a control group of facilities that never contracted with a PMC. Most PMCs seek to negotiate exclusive contracts in which only 1 group provides services to a facility.^7,18,33 However, in addition to contracting with a PMC, facilities may choose to employ some anesthesia practitioners, contract with individual practitioners at the request of facility surgeons, or use locum tenens practitioners (see eMethods 1 in the Supplement for details). Therefore, we defined a facility as starting a PMC contract when a switch from 0% of practitioners to greater than 60% of practitioners in a facility billed under the tax identification number (TIN) of a PMC. By potentially including non-PMC practitioners in the treatment group, the results would be attenuated. The institutional review board of Weill Cornell Medical College reviewed and approved the analysis and waived the need for informed consent because deidentified data were used.

Data Sources

We built a longitudinal data set from 2012 to 2017 that identified the year an ASC or hospital outpatient department contracted with a PMC. First, we collected the names of PMC subsidiary companies. To identify these subsidiaries, we used corporate filing data from the websites HIPAASpace (https://www.hipaaspace.com/) and OpenCorporates (https://opencorporates.com/), US Securities and Exchange Commission filings for publicly traded companies, and mergers and acquisitions data from Irving Levin and SDC Platinum. The Irving Levin and SDC Platinum data also provided dates for when PMCs received PE investment. We identified 22 PMCs, half of which received PE funding, as providers of anesthesia services during our sample period (eTable 1 in the Supplement).

Second, we used Medicare Data on Provider Practice and Specialty (MD-PPAS) to identify the TIN of the PMC subsidiaries and when a practitioner billed under a PMC TIN. For all practitioners who billed Medicare, MD-PPAS provided their National Provider Identifier (NPI) and the 2 main TINs they billed under in each month. We created a data set of all TINs associated with a PMC by searching for the name of each subsidiary in MD-PPAS, allowing us to identify when an anesthesia practitioner billed a PMC’s TIN (eTable 2 in the Supplement).³⁴

Third, we merged the PMC data set with commercial claims for professional (clinician) services from the Health Care Cost Institute (HCCI) from 2012 to 2017 using physician NPIs to identify when a hospital outpatient department or ASC contracted with a PMC (eTable 3 in the Supplement). The HCCI data included claims for patients insured by Aetna, Humana, and UnitedHealthcare, 3 of the largest US health insurers. We identified new facility contracts when a switch from 0% to 60% of practitioners billed under the TIN of a PMC.

Study Population

The analysis focused on claims for anesthesia provided during same-day procedures in ASCs and hospital outpatient departments. The database created included 6710 facilities, of which 2992 never had a practitioner bill under a PMC TIN (control), 672 had a switch from 0% to greater than 60% of practitioners bill a PMC TIN (treatment), 750 had at least 1 practitioner bill under a PMC TIN in all years (excluded from analyses), and 2296 did not fall into either category (excluded from analyses).

As shown in eFigure 1 in the Supplement, this database included 7 227 912 claims for professional services after exclusions (2 255 933 claims were from eligible treatment and control facilities) for anesthesia services provided by anesthesiologists and CRNAs between January 1, 2012, and December 31, 2017. Anesthesia services were identified using Current Procedural Terminology codes 00100-01999. To allow for accurate comparisons between facilities before and after PMC contract, the database was limited to facilities with at least 2 claims a year in the HCCI data for at least 4 consecutive years. See eMethods 1 in the Supplement for further sample details and exclusions.

Study Variables

Outcomes

The primary outcome of interest, prices for anesthesia services, was measured using allowed amounts, which represent the actual amount paid by the insurer to the practitioner plus the patient cost share. For each claim, we also converted the allowed amount into a single “unit price” because in anesthesiology, contract negotiations are based on the price paid per unit of service. The unit price standardizes payment across all procedures according to procedure complexity (base units) and length of time (time units). Therefore, the unit price captures the price paid to anesthesia practitioners irrespective of procedure type or duration. Both allowed amounts and unit prices were winsorized at the top and bottom 0.5% and were geographically adjusted and inflation adjusted into 2017 dollars.

The secondary outcome of interest, the practitioner’s out-of-network status, was estimated using an indicator variable for whether the anesthesia practitioner was out of a patient’s network, available in HCCI for 2014 to 2017. The primary analyses combined in-network and out-of-network claims to reflect overall changes in prices, but we also conducted analyses using only in-network claims.

Covariates

Analyses for allowed amounts and unit prices included controls for patient age, sex, and predicted health risks, using indicators for Elixhauser comorbidities; analyses of allowed amounts also included controls for procedure base and time units. In secondary analyses, the probability of a PMC contract was estimated as a function of the following facility and market characteristics: the setting (hospital outpatient department or ASC), region (Northwest, Midwest, West, South, or Pacific), the number of anesthesiologists and CRNAs, the number of claims, the distribution of procedure base and time units, the level of market concentration (defined as a hospital referral region [HRR]), and the percentage of PMC facilities in an HRR.

Statistical Analysis

The primary analysis was prespecified to use linear regression and a difference-in-differences approach to estimate changes in (1) prices and (2) a practitioner’s network status for anesthesia services provided in facilities before and after a PMC contract compared with facilities that never contracted with a PMC. Regressions included controls for patient characteristics, facility fixed effects to adjust for time-invariant facility characteristics, state fixed effects interacted with year to adjust for state-specific trends, an indicator for the year of contract (referred to as the transition period) to adjust for the facility’s transition to a PMC staffing model, and an indicator for the post-PMC contract period, which is the variable of interest (see eMethods 2 in the Supplement for estimating equations).

In a prespecified subgroup analysis, we included interactions between the PMC contract indicators (transition and post-PMC contract period) and an indicator for whether the PMC ever received investment from a PE firm during the sample period to test whether outcomes differ for PE-backed PMCs. In secondary post hoc analysis, to explore whether PMCs target certain types of facilities, we used linear regression to estimate the probability that a facility contracted with a PMC or with a PE-backed PMC as a function of facility and market characteristics. All analyses included robust SEs clustered at the facility level and were conducted using Stata, version 16.0 (StataCorp LLC). P values were 2-tailed, and statistical significance was defined as P < .05.

A key assumption required for difference-in-differences is that the pre-PMC contract difference between treatment and control facilities would have remained constant in the absence of the PMC contract. To test this assumption, we conducted 2 prespecified secondary analyses. First, we graphed coefficients from interaction terms between indicators for each year relative to the time of PMC contract and an indicator for whether a facility contracted with a PMC to test for preexisting trends. Given concerns of bias in settings with multiple treatment periods, we also graphed these interaction terms using the methods of Borusyak et al.³⁵ Second, we tested for differential changes in patient characteristics after a PMC contract and compared regressions with and without the inclusion of patient risk adjustment.

Lastly, we assessed the sensitivity of the results to (1) adding practitioner fixed effects, (2) using HRR by year fixed effects, (3) using an alternative control group of facilities that contracted with a PMC after the sample period, (4) using a cutoff of 80% of practitioners billing under a PMC TIN to identify a PMC contract, (5) limiting the sample to in-network claims, and (6) estimating hospital outpatient departments and ASCs separately.

Results

Facility and Patient Characteristics

The primary analysis included 672 facilities that contracted with a PMC (treated) and 2992 facilities that did not (control). Before the PMC contract, treated facilities had more claims per year (709.61 vs 355.14) and more anesthesiologists (24.43 vs 13.33) and were more likely to perform procedures with a higher number of base units and time units compared with control facilities (Table 1 and Table 2). These patterns are confirmed in post hoc regression analyses of the types of facilities targeted by PMCs (eTable 4 in the Supplement). While the unadjusted differential changes in patient characteristics in treatment facilities compared with control facilities were small, treatment facilities had a reduction in procedures of lower base and time units, suggesting a shift away from shorter, less complicated procedures (Table 2). The unit price accounts for these changes in procedure type and duration because it is standardized by base units and time units.

Table 1. Unadjusted Facility and Market Characteristics, Before Physician Management Company (PMC) Contract.

Characteristic	PMC facility (treatment)^a	Never PMC facility (control)^a	Difference (95% CI)
Facility characteristics^b
No. of facilities	672	2992	NA
Hospital outpatient department, No. (%)	378 (56.25)	1591 (53.18)	3.07 (–1.10 to 7.25)
Ambulatory surgery center, No. (%)	294 (43.75)	1401 (46.82)	–3.07 (–7.25 to 1.10)
Facility region, No. (%)
Northeast	121 (18.01)	393 (13.14)	4.87 (1.97 to 7.77)
Midwest	142 (21.13)	856 (28.61)	–7.48 (–11.20 to –3.76)
West	118 (17.56)	755 (25.23)	–7.67 (–11.23 to –4.12)
South	290 (43.15)	962 (32.15)	11.00 (7.05 to 14.96)
Total claims	297 147	1 457 060	NA
Claims per facility	709.61	355.14	354.46 (352.26 to 356.67)
Anesthesiologists per facility	24.43	13.33	11.1 (11.03 to 11.17)
CRNAs per facility	6.91	7.68	–0.76 (–0.82 to –0.71)
Market characteristics ^c
Concentration (HHI)	1061.09	1225.14	–164.06 (–168.55 to –159.56)
PMC facilities, %	11.58	9.93	1.65 (1.60 to 1.70)

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Abbreviations: CRNA, certified registered nurse anesthetist; HHI, Hirschman Herfindahl Index; NA, not applicable.

^{^a}

Facilities that contracted with PMCs (treatment) were compared with PMCs that did not contract with PMCs (control) before the PMC contracts were implemented. The pre-PMC facility mean includes all years prior to the start of contract, and the never PMC facility mean represents the mean of all years of data.

^{^b}

The facility setting (hospital outpatient department or ambulatory surgery center) and region values are presented as a proportion of the number of facilities. The remainder of facilities are located in the Pacific census region.

^{^c}

The market represents the hospital referral region (HRR) of the facility as defined by the Dartmouth Atlas of Health Care. The HHI is measure of the market concentration of the HRR calculated using the share of anesthesia claims per facility. A market with an HHI of less than 1500 is generally considered a competitive market. “PMC facilities” represents the percentage of facilities in an HRR under PMC contract using our full sample of 6710 facilities.

Table 2. Unadjusted Outcomes, Procedure Time and Base Units, and Patient Characteristics, Before and After Physician Management Company (PMC) Contract.

Variable/characteristic	PMC facility (treatment)^a		Never PMC facility (control),^a mean of all years	Difference (95% CI)
	PMC facility (treatment)^a			Difference from before to after PMC contract period^b	Unadjusted differential change from before to after PMC contract period^c
	Pre-PMC contract mean	Post-PMC contract mean		Difference from before to after PMC contract period^b
Outcome variables
Allowed amounts, $	704.40	805.62	651.00	101.21 (98.89 to 103.54)	145.57 (144.06 to 147.09)
Unit price, $^d	100.39	118.07	100.64	17.69 (17.33 to 18.05)	17.48 (17.23 to 17.73)
OON practitioner, %^e	15.08	15.44	13.27	0.35 (0.06 to 0.65)	2.01 (1.80 to 2.19)
Control variables ^d
Time units, quintile, %
1	37.79	33.35	45.15	–4.45 (–4.66 to –4.23)	–10.55 (–10.71 to –10.40)
2	13.58	16.27	12.33	2.69 (2.53 to 2.85)	3.73 (3.62 to 3.83)
3	15.27	18.21	14.57	2.94 (2.77 to 3.11)	3.53 (3.41 to 3.64)
4	15.12	16.62	14.54	1.51 (1.34 to 1.67)	1.99 (1.88 to 2.10)
5	18.23	15.54	13.42	–2.69 (–2.86 to –2.52)	1.31 (1.20 to 1.42)
Base units, %
2-4	34.84	31.56	38.92	–3.28 (–3.49 to –3.07)	–6.66 (–6.82 to –6.51)
5	52.04	54.66	48.25	2.63 (2.40 to 2.85)	5.78 (5.62 to 5.93)
6-8	12.47	13.01	12.24	0.53 (0.38 to 0.68)	0.73 (0.62 to 0.83)
≥9	0.64	0.77	0.60	0.12 (0.08 to 0.16)	0.16 (0.14 to 0.19)
Patient characteristics, %
Male	40.91	41.3	41.72	0.39 (0.16 to 0.61)	–0.29 (–0.44 to –0.13)
Age, y
18-24	6.07	5.19	6.48	–0.88 (–0.99 to –0.78)	–1.23 (–1.30 to –1.15)
25-34	10.81	10.08	10.71	–0.73 (–0.87 to –0.59)	–0.65 (–0.74 to –0.55)
35-44	17.83	16.89	16.76	–0.94 (–1.11 to –0.77)	–0.05 (–0.17 to 0.07)
45-54	31.22	31.15	29.43	–0.07 (–0.28 to 0.14)	1.42 (1.28 to 1.56)
55-64	34.07	36.69	36.62	2.62 (2.40 to 2.84)	0.51 (0.35 to 0.66)
Total claims	297 147	501 726	1 457 060	NA	NA

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Abbreviations: NA, not applicable; OON, out-of-network.

^{^a}

The pre-PMC contract period includes all years prior to the start of contract. The post-PMC contract period includes the year the contract started and all subsequent years. There were 0 facility contracts in 2012 (by construction), 125 facility contracts in 2013, 131 in 2014, 144 in 2015, 163 in 2016, and 109 in 2017.

^{^b}

The difference estimate indicates the absolute change in mean values from the pre-PMC contract period to the post-PMC contract period.

^{^c}

The unadjusted differential change represents the difference between the PMC facility from pre-PMC to post-PMC contract relative to facilities that never contracted with a PMC.

^{^d}

The unit price represents allowed amounts standardized by the duration of the anesthesia procedure, measured by time units (a single unit represents 15 minutes), and the complexity of the procedure, measured by base units (see eMethods 1 in the Supplement for details). In regression analysis using allowed amounts as the outcome, we included controls for time units and base units as follows: (1) Time units are binned into quintiles of the distribution, where the first quintile represents procedures of shorter duration and the fifth quintile represents procedures of longer duration, and (2) base units are binned into categories of similar complexity, where base units of 2 to 4 represent lower-complexity procedures, and base units of 9 or greater represent more complex procedures. Additional controls include 30 patient risk factors based on Elixhauser comorbidities, which are not shown for table clarity. See eMethods 3 in the Supplement for additional output.

^{^e}

The OON status is only available from 2014 to 2017. During this period, 416 facilities contracted with a PMC (total claims = 235 832), and 2992 facilities never contracted with a PMC (total claims = 1 005 082).

Of the 672 PMC facilities, 283 received PE investment at some point during the study period (eTables 5 and 6 in the Supplement). Compared with PMCs without PE, facilities that contracted with PE-backed PMCs were more likely to be in the South, be in markets with a greater share of facilities already under PMC contract, and perform procedures with higher time units (eTable 7 in the Supplement). See eMethods 3 in the Supplement for additional summary statistics.

Differential Changes in Outcomes Associated With PMC Contracts

Contracting with a PMC was associated with an increase in prices for anesthesia services compared with facilities that did not contract with a PMC (Table 3). In the post-PMC contract period, allowed amounts increased by $116.39 (95% CI, $76.11-$156.67; P < .001) more in PMC facilities than in non-PMC facilities, representing a 16.5% increase in allowed amounts from the precontract period. Similarly, unit prices increased by $18.79 (95% CI, $12.73-$24.84; P < .001), representing an 18.7% increase. Statistically significant price increases were also observed in the year of the PMC contract (the transition period). Results did not show evidence that practitioners were moved out of network.

Table 3. Adjusted Differential Changes in Outcomes Associated With Physician Management Company (PMC) Contract.

Outcome^a	Total claims	Pre-PMC contract mean^b	Adjusted difference-in-differences estimates^c
Outcome^a	Total claims	Pre-PMC contract mean^b	Transition year^d (95% CI)	P value	Post-PMC contract^e (95% CI)	P value	Relative change,^f %
Allowed amount, $	2 255 933	704.40	51.19 (29.10 to 73.28)	<.001	116.39 (76.11 to 156.67)	<.001	16.5
Unit price, $	2 255 933	100.39	7.15 (3.37 to 10.92)	<.001	18.79 (12.73 to 24.84)	<.001	18.7
Probability OON practitioner, %	1 240 914	15.08	1.80 (–0.06 to 3.67)	.06	2.25 (–2.56 to 7.06)	.36	15.2

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Abbreviation: OON, out-of-network.

^{^a}

Allowed amounts and unit prices are based on HCCI data from 2012 to 2017, while the indicator for practitioner network status was only available from 2014 to 2017. The unit price represents allowed amounts standardized by the duration of the anesthesia procedure, measured by time units, and the complexity of the procedure, measured by base units. The regression for allowed amount included controls for base and time units as shown in Table 2. Patient controls were not included in OON analyses because they would not influence network status.

^{^b}

The pre-PMC contract mean includes all years prior to the start of contract. There were 0 facility contracts in 2012 (by construction), 125 facility contracts in 2013, 131 in 2014, 144 in 2015, 163 in 2016, and 109 in 2017.

^{^c}

Facilities that contracted with PMCs (treatment) were compared with PMCs that did not contract with PMCs (control) before and after PMC contracts were implemented using a difference-in-differences specification with controls for patient characteristics and risk factors, facility and state by year fixed effects, and robust SEs clustered at the facility level.

^{^d}

The transition difference represents the differential change between treatment and control facilities from the pre-PMC contract period to the year of PMC contract.

^{^e}

The post-PMC contract difference represents the differential change between treatment and control facilities from the pre-PMC contract period to the years after the facility contracted with the PMC.

^{^f}

Relative change is the adjusted post-PMC contract estimate as a percentage of the pre-PMC contract mean.

Figure 1 shows adjusted differences in outcomes between facilities that did and did not contract with PMCs relative to the year of PMC contract (coefficient estimates and 95% CIs are reported in eTable 8 in the Supplement). The coefficients in the precontract period did not differ significantly between PMC and non-PMC facilities. Both allowed amounts and unit prices increased steadily from the year of contract to 4 years after the contract. The probability that a practitioner was out of network increased by 1.95 percentage points (95% CI, 0.09-3.80; P = .04) in the year of contract, but estimates were not statistically significant in subsequent years.

Subgroup, Secondary, and Sensitivity Analyses

Figure 2 shows the results of the subgroup analyses between facilities that contract with PMCs with and without PE investment relative to the regression-adjusted mean of the control facilities, $664.40. After PMC contract, allowed amounts were $754.28 for PMCs without PE and $851.46 for PMCs with PE, representing an increase of $89.88 (95% CI, $42.07-$137.69; P < .001) and $187.06 (95% CI, $133.59-$240.52; P < .001) relative to control facilities, respectively (Figure 2; eTable 9 in the Supplement). These are large magnitudes, representing a 12.9% increase for PMCs without PE and a 26.0% increase for PMCs with PE, relative to the pre-PMC contract mean (eTable 9 in the Supplement). The difference between PMCs is also significantly different: PE-backed PMCs increased allowed amounts by $97.18 (95% CI, $35.38-$158.97; P = .002) more than PMCs without PE. The same patterns were observed for unit prices, but there were no statistical differences in a practitioner’s out-of-network status.

In support of the difference-in-differences design, secondary analyses show that patient risk factors did not change significantly after a PMC contract (eFigure 2 in the Supplement) and that results were similar when excluding patient controls (eTable 10 in the Supplement). Sensitivity analyses (see eMethods 4 in the Supplement for detailed information) show that results were similar when adding practitioner fixed effects (eTable 11 in the Supplement), using HRR by year fixed effects (eTable 12 in the Supplement), using a higher cutoff of 80% of practitioners billing under a PMC TIN (eTables 13-15 and eFigures 3 and 4 in the Supplement) and an alternative control group of facilities that contracted with a PMC after 2017 (eTables 16-18 and eFigures 5 and 6 in the Supplement). The results were robust to including only in-network claims (eTable 19 in the Supplement) and similar between hospital outpatient departments and ASCs (eTable 20 in the Supplement). Lastly, estimates were similar after corrections for potential bias resulting from multiple treatment periods (eFigure 7 in the Supplement).

Discussion

The prices paid to anesthesia practitioners in hospital outpatient departments and ASCs increased after a PMC contract. Relative to the pre-PMC contract, allowed amounts increased by 16.5%, and unit prices increased by 18.7%. While both PMCs with and without PE investment had increased prices, this increase was partly driven by PE-backed PMCs: allowed amounts and unit prices increased by 26.0% and 25.6%, respectively, for facilities that contracted with PE-backed PMCs. Because unit prices are standardized by procedure type and duration, these results suggest that price increases were associated with higher prices paid per service.

The PMCs may have increased prices by negotiating better rates after a facility contract or by replacing existing anesthesia practitioners with practitioners already employed by the PMC. To account for compositional changes among practitioners, we added practitioner fixed effects to our primary specification and found similar price increases (eTable 11 in the Supplement). These results suggest that PMCs negotiated higher rates after a new facility contract.

One way PMCs may command higher prices is by amassing market share and by developing better negotiating expertise. For example, PMCs may acquire anesthesia groups and target facilities in a certain geographic area to increase their size and gain regional experience with practitioners and insurers.^4,36 While we did not conduct a formal analysis of changes in market concentration, we found evidence that PMCs, particularly PE-backed PMCs, were more likely to enter markets with greater shares of facilities already under PMC contract (eTables 4 and 7 in the Supplement). The PE-backed PMCs may also have had stronger incentives to create short-term returns for investors relative to those without PE investment.^34,37,38

The PMCs may also have gained negotiating leverage over insurers by threatening to move practitioners out of network.^28,29,30 We did not find evidence that practitioners moved out of network except for a modest increase in the year the contract started. However, the mere threat may be sufficient to influence negotiating dynamics between PMCs and insurance companies.

This research has important implications for payers, practitioners, patients, and policy makers. In recent legal disputes, insurance companies have argued that the prices they pay to PMC practitioners are too high, while PMCs have argued that large insurers do not adequately compensate practitioners.^21,29,30 Either way, the proliferation of PMCs and PE firms in health care has raised concerns about increasing upward pressure on prices for in-network care, which can contribute to higher insurance premiums and higher patient cost-sharing.³⁹

Limitations

This study had several limitations. First, while HCCI includes claims from 3 of the largest US insurers, it does not include all commercial claims, so the results may not generalize to other insurers. Second, we do not have the dates of PMC contracts; instead, we identified contracts when a switch from 0% of practitioners to greater than 60% of practitioners in a facility billed under a PMC TIN, which was robust to a more conservative 80% cutoff. Third, analyses of practitioner network status should be interpreted as short-term results because we only had access to a network indicator from 2014 through 2017. Fourth, given the lack of claims-based methods for measuring anesthesia quality, we were unable to determine whether higher quality justified higher prices. To minimize potential variation in quality, our analysis focused on anesthesia provided during same-day procedures among commercially insured patients. Fifth, the results may not generalize to inpatient settings.

Conclusions

In this cohort study of outpatient facilities that did and did not contract with PMCs, there were large and significant increases in the prices paid to anesthesia practitioners. These price increases were substantially larger if the PMC received PE investment.

Supplement.

eMethods 1. Data and Sample

eTable 1. Physician Management Companies (PMCs) Focused on Anesthesia Staffing and Management Between 2012-2017

eTable 2. Number of Anesthesia Practitioners that Bill Under a PMC TIN in MD-PPAS, 2012-2017

eTable 3. Number of Anesthesia Practitioners that Bill Under a PMC TIN in HCCI in Hospital Outpatient Departments and Ambulatory Surgery Centers, 2012-2017

eFigure 1. Sample Selection

eMethods 2. Estimating Equations and Identification

eMethods 3. Additional Summary Statistics and Results

eTable 4. Probability Facility Contracts with Any PMC

eTable 5. Unadjusted Facility and Market Characteristics, Before PMC Contract – Full PMC Sample and PMCs by PE Status

eTable 6. Unadjusted Outcomes, Procedure Time and Base Units, and Patient Characteristics, Before and After PMC Contract – Full PMC Sample and PMCs by PE Status

eTable 7. Probability Facility Contracts with PE-Backed PMC Relative to PMCs Without PE

eTable 8. Adjusted Differences in Outcomes Between Treatment and Control Facilities Relative to the Year of PMC Contract

eTable 9. Adjusted Differential Changes in Outcomes Associated with PMC Contract, PE Subsample Analysis

eMethods 4. Sensitivity Analysis

eFigure 2. Adjusted Differential Changes in Patient Risk Factors Associated with PMC Contract

eTable 10. Adjusted Differential Changes in Outcomes Associated with PMC Contract, Without Patient Risk Adjustment

eTable 11. Adjusted Differential Changes in Outcomes Associated with PMC Contract, Adding Practitioner Fixed Effects

eTable 12. Adjusted Differential Changes in Outcomes Associated with PMC Contract, Using HRR x Year Fixed Effects

eTable 13. Unadjusted Facility and Market Characteristics, Before PMC Contract – 80% Cut-Off

eTable 14. Unadjusted Outcomes, Procedure Time and Base Units, and Patient Characteristics, Before and After PMC Contract – 80% Cut-Off

eTable 15. Adjusted Differential Changes in Outcomes Associated with PMC Contract, 80% Cut-Off

eFigure 3. Adjusted Differences in Outcomes Between Treatment and Control Facilities Relative to the Year of PMC Contract, 80% Cut-Off

eFigure 4. Adjusted Differential Changes in Outcomes Associated with PMC Contract with and without Private Equity Investment, 80% Cut-Off

eTable 16. Unadjusted Facility and Market Characteristics, Before PMC Contract – Alternative Control Group

eTable 17. Unadjusted Outcomes, Procedure Time and Base Units, and Patient Characteristics, Before and After PMC Contract – Alternative Control Group

eTable 18. Adjusted Differential Changes in Outcomes Associated with PMC Contract, Alternative Control Group

eFigure 5. Adjusted Differences in Outcomes Between Treatment and Control Facilities Relative to the Year of PMC Contract, Alternative Control Group

eFigure 6. Adjusted Differential Changes in Outcomes Associated with PMC Contract with and without Private Equity Investment, Alternative Control Group

eTable 19. Adjusted Differential Changes in Outcomes Prices with PMC Contract, Only In-Network Claims 2014-2017

eTable 20. Adjusted Differential Changes in Prices Associated with PMC Contract, Hospital Outpatient Departments vs Ambulatory Surgery Centers (ASCs)

eFigure 7. Adjusted Differences in Outcomes Between Treatment and Control Facilities Relative to the Year of PMC Contract Using Event Study Imputation Adjustment of Borusyak, Jaravel, and Spiess (2021)

Click here for additional data file.^{(1.5MB, pdf)}

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