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The Rise Of Cross-Market Hospital Systems And Their Market Power In The US
Abstract
Although hospital consolidation within markets has been well documented, consolidation across markets has not, even though economic theory predicts-and evidence is emerging-that cross-market hospital systems raise prices by exerting market power across markets when negotiating with common customers (primarily insurers). This study analyzes hospital systems using the American Hospital Association Annual Survey Database and defines hospital geographic markets as commuting zones that link workers to places of employment. The share of community hospitals in the US that were part of hospital systems increased from 10 percent in 1970 to 67 percent in 2019, resulting in 3,436 hospitals within 368 systems in 2019. Of these systems, 216 (59 percent) owned hospitals in multiple commuting zones, in part because 55 percent of the 1,500 hospitals targeted for a merger or acquisition between 2010 and 2019 were located in a different commuting zone than the acquirer. Based on market-power differences among hospitals in systems, the number of systems in urban commuting zones that could potentially exert enhanced cross-market power increased from thirty-seven systems in 2009 to fifty-seven systems in 2019, an increase of 54 percent. The increase in cross-market hospital systems warrants concern and scrutiny because of the potential anticompetitive impact of hospital systems exerting market power across markets in negotiations with common customers.
... A very large fraction of vulnerable infants were treated in cross-market systems, which have become increasingly prevalent. 16 These systems have increasing market power, particularly in negotiations with private insurers. 17 Newborn hospitalizations are the second most expensive type of hospitalization for private payers. ...
Hospital care has consolidated rapidly into health systems in the United States. Infants born very preterm are among the most vulnerable pediatric populations, accounting for the majority of infant deaths each year. The pediatric health care delivery system for infants is unique as the birth hospitalization includes two patients, the mother and the infant. Further, regionalization goals for infants that are born preterm require care to be provided at neonatal intensive care units (NICUs) with the capacity to treat them. National patient-level data from the Vermont Oxford Network demonstrates that most very preterm infants were born in a horizontally integrated, multi-hospital system (84%), and they tended to remain in the system for their entire hospitalization including for risk-appropriate NICU care. Half of the infants were cared for in large systems with more than 10 hospitals that were disproportionately cross-market systems. With high transfer rates between hospitals (21%) it will be important to determine the implications of consolidation for the quality of care and patient-centeredness for families. The care for very preterm infants is important from a policy perspective as hospitalized newborn infants account for 21% of hospitalizations in Medicaid each year and 10% of aggregate hospital costs.
... 1500 hospitals targeted for acquisition in the 2010s, about 55% were in a different commuting zone than the acquiring hospital. 6 It is likely that the COVID-19 pandemic only increased the salience of cross-market mergers, as exemplified by the Atrium-Advocate Aurora merger and potential upcoming deals such as the proposed merger of Iowa-based UnityPoint and New Mexico-based Presbyterian Health. ...
This Viewpoint discusses how and why cross-market hospital mergers are different than prototypical within-market mergers in their effects on patients and communities, why the trend may be accelerating, and future policy and research directions.
This Viewpoint discusses ways for health systems, professional societies, and academic physicians to develop and share effective teaching materials and strategies with community-based colleagues.
Objective
To quantify the degree to which health care service area (HCSA) definitions captured hospitalizations and heterogeneity in social determinants of health (SDOH).
Data Sources and Study Setting
Geospatial data from the Centers for Medicare and Medicaid Services, the Census Bureau, and the Dartmouth Institute. Drive‐time isochrones from MapBox. Area Deprivation Index (ADI) data. 2017 inpatient discharge data from Arizona, Florida, Iowa, Maryland, Nebraska, New Jersey, New York, and Wisconsin, State Emergency Department Databases and State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality; and Fee‐For‐Service Medicare data in 48 states.
Study Design
Cross‐sectional, descriptive analysis.
Data Collection/Extraction Methods
The capture rate was the percentage of inpatient discharges occurring in the same HCSA as the hospital. We compared capture rates for each HCSA definition for different populations and by hospital type. We measured SDOH heterogeneity using the coefficient of variation of the ADI among ZIP codes within each HCSA.
Principal Findings
HCSA definitions captured a wide range of inpatient discharges, ranging from 20% to 50% for Public Use Microdata Areas (PUMAs) to 93%–97% for Metropolitan Statistical Areas (MSAs). Three‐quarters of inpatient discharges were from facilities within the same county as the patient's residential ZIP code, while nearly two‐thirds were within the same Hospital Service Area. From the hospital perspective, 74.7% of inpatient discharges originated from within a 30‐min drive and 90.1% within a 60‐min drive. Capture rates were the lowest for teaching hospitals. PUMAs and drive‐time‐based HCSAs encompassed more homogenous populations while MSAs, Commuting Zones, and Hospital Referral Regions captured the most variation.
Conclusions
The proportion of hospital discharges captured by each HCSA varied, with MSAs capturing the highest proportion of discharges and PUMAs capturing the lowest. Additionally, researchers face a trade‐off between capture rate and population homogeneity when deciding which HCSA to use.
Objective
To examine the impact of “cross‐market” hospital mergers on prices and quality and the extent to which serial acquisitions contribute to any measured effects.
Data Sources
2009–2017 commercial claims from the Health Care Cost Institute (HCCI) and quality measures from Hospital Compare.
Study Design
Event study models in which the treated group consisted of hospitals that acquired hospitals further than 50 miles, and the control group was hospitals that were not part of any merger activity (as a target or acquirer) during the study period.
Data Extraction Methods
We extracted data for 214 treated hospitals and 955 control hospitals.
Principal Findings
Six years after acquisition, cross‐market hospital mergers had increased acquirer prices by 12.9% (CI: 0.6%–26.6%) relative to control hospitals, but had no discernible impact on mortality and readmission rates for heart failure, heart attacks and pneumonia.
For serial acquirers, the price effect increased to 16.3% (CI: 4.8%–29.1%). For all acquisitions, the price effect was 21.8% (CI: 4.6%–41.7%) when the target's market share was greater than the acquirer's market share versus 9.7% (CI: −0.5% to 20.9%) when the opposite was true. The magnitude of the price effect was similar for out‐of‐state and in‐state cross‐market mergers.
Conclusions
Additional evidence on the price and quality effects of cross‐market mergers is needed at a time when over half of recent hospital mergers have been cross‐market. To date, no hospital mergers have been challenged by the Federal Trade Commission on cross‐market grounds. Our study is the third to find a positive price effect associated with cross‐market mergers and the first to show no quality effect and how serial acquisitions contribute to the price effect. More research is needed to identify the mechanism behind the price effects we observe and analyze price effect heterogeneity.
Background:
Hospitals may adopt various information transmission methods to participate in health information exchange (HIE) programs. However, even if they adopt multiple mechanisms, they may not actively use all of them to send inside information. This study analyzes the frequently used methods for sending data and the common barriers blocking sending practices in hospital settings.
Methods:
Our sample included 3,015 community hospitals that reported their methods of sending patient health information in the 2019 American Hospital Association Information Technology Supplement Survey. The relationship between obstacles hospitals experienced and their use of the information-sending method was analyzed by using robust Poisson regression models.
Results:
Many-to-many exchanges that involve intermediaries such as a health information service provider (HISP), electronic health record (EHR) vendor-based network, and national network, once adopted, were more often used by hospitals than one-to-one exchange methods such as provider portals and direct access to EHR by login credentials. Hospitals that lacked the technical capability to electronically send patient health information were less likely to use any of the methods (p <.01), while hospitals located in a more concentrated market were more likely to send information to outside providers by using provider portal, interface connection and national network (p <.01).
Discussion:
There is still a notable gap between hospitals' adoption and the actual use of different HIE methods to send inside information to outside organizations. Results argue that even if hospitals adopted an HIE method, they might not necessarily participate in the actual sharing of information, and the method may remain unused due to several usage barriers.
Conclusion:
Hospital and market-level barriers associated with using one-to-one and many-to-many HIE methods for sharing information may affect progress in interoperability. Examining the barriers to using multiple HIE methods and their impact on interoperability could offer implications for health information technology (IT) policy and inform health system leaders.
This study examines the association between hospital consolidation and loss of pediatric inpatient services.
Financial distress among rural hospitals in the US has increased in recent years. Using national hospital data, we investigated how the decline in profitability has affected hospital survival, either independently or with a merger. The answer has direct implications for access to care and competition in rural markets. We assessed the rate of hospital closures and mergers in predominantly rural markets during the period 2010-18, focusing on hospitals that were unprofitable at baseline. A minority of unprofitable hospitals (7 percent) closed. A larger share (17 percent) merged, most commonly with organizations from outside of their local geographic market. Most unprofitable hospitals (77 percent) continued to operate through 2018 without closure or merger. About half of these hospitals returned to profitability. At the market level, 22 percent of markets served by unprofitable hospitals lost a competitor to closure or within-market merger. Out-of-market mergers affected 33 percent of markets with an unprofitable hospital. Overall, our results suggest that rural markets are experiencing meaningful rates of hospital closures and mergers, yet many hospitals have survived despite poor financial performance. Policies targeting access to care will continue to be important. Similar attention will be needed to address the competitive effects of hospital closures and mergers on prices and quality.
Unlabelled:
Policy Points Hospital executives posit a number of rationales for system mergers which lack any basis in academic evidence. Decades of academic research question whether system combinations confer public benefits. Antitrust authorities need to continue to closely scrutinize these transactions. Recently, mergers of hospital systems that span different geographic markets are on the rise. Economists have alerted policymakers about the potential impacts such cross-market mergers may have on hospital prices. We suggest there are other reasons for concern that scholars have not often confonted. Cross-market mergers may be conducted for purely self-serving reasons of organizational growth that increases executive compensation. Combinations of sellers should have clear advantages to consumers. System executives and their boards should bear the burden of proof. Federal regulators and state attorney generals should be cognizant that rationales for cross-market systems advanced by merging parties are unlikely to be operative or dominant in merger decision making. Policymakers should be careful about passing legislation that encourages hospitals to consolidate.
Context:
There is a growing trend of combinations among hospital systems that operate in different geographic markets known as cross-market mergers. Economists have analyzed these broader systems in terms of their anticompetitive behavior and pricing power over insurers. This paper evaluates the benefits advanced by these new hospital systems that speak to a different set of issues not usually studied: increased efficiencies, new capabilities, operating synergies, and addressing health inequities. The paper thus "looks under the hood" of these emerging, cross-market systems to assess what value they might bestow and upon whom.
Methods:
The paper examines recently announced cross-market mergers in terms of their supposed benefits, as expressed by the systems' executives as well as by industry consultants. These presumed benefits are then evaluated against existing evidence regarding hospital system outcomes.
Findings:
Advocates of cross-market hospital mergers cite a host of benefits. Research suggests these benefits are nonexistent. Additional evidence suggests other motives may be at play in the formation of cross-market mergers that have nothing to do with efficiencies, synergies, or community benefits. Instead these mergers may be self-serving efforts by system chief executive officers (CEOs) to boost their compensation.
Conclusions:
Cross-market hospital mergers may yield no benefits to the hospitals involved or the communities in which they operate. The boards of hospital systems that engage in these cross-market mergers need to exercise greater diligence over the actions of their CEOs.
Importance
Little is known about the breadth of health care networks or the degree to which different insurers’ networks overlap.
Objective
To quantify network breadth and exclusivity (ie, overlap) among primary care physician (PCP), cardiology, and general acute care hospital networks for employer-based (large group and small group), individually purchased (marketplace), Medicare Advantage (MA), and Medicaid managed care (MMC) plans.
Design, Setting, and Participants
This cross-sectional study included 1192 networks from Vericred. The analytic unit was the network–zip code–clinician type–market, which captured attributes of networks from the perspective of a hypothetical patient seeking access to in-network clinicians or hospitals within a 60-minute drive.
Exposures
Enrollment in a private insurance plan.
Main Outcomes and Measures
Percentage of in-network physicians and/or hospitals within a 60-minute drive from a hypothetical patient in a given zip code (breadth). Number of physicians and/or hospitals within each network that overlapped with other insurers’ networks, expressed as a percentage of the total possible number of shared connections (exclusivity). Descriptive statistics (mean, quantiles) were produced overall and by network breadth category, as follows: extra-small (<10%), small (10%-25%), medium (25%-40%), large (40%-60%), and extra-large (>60%). Networks were analyzed by insurance type, state, and insurance, physician, and/or hospital market concentration level, as measured by the Hirschman-Herfindahl index.
Results
Across all US zip code–network observations, 415 549 of 511 143 large-group PCP networks (81%) were large or extra-large compared with 138 485 of 202 702 MA (68%), 191 918 of 318 082 small-group (60%), 60 425 of 149 841 marketplace (40%), and 21 781 of 66 370 MMC (40%) networks. Large-group employer networks had broader coverage than all other network plans (mean [SD] PCP breadth: large-group employer-based plans, 57.3% [20.1]; small-group employer-based plans, 45.7% [21.4]; marketplace, 36,4% [21.2]; MMC, 32.3% [19.3]; MA, 47.4% [18.3]). MMC networks were the least exclusive (a mean [SD] overlap of 61.3% [10.5] for PCPs, 66.5% [9.8] for cardiology, and 60.2% [12.3] for hospitals). Networks were narrowest (mean [SD] breadth 42.4% [16.9]) and most exclusive (mean [SD] overlap 47.7% [23.0]) in California and broadest (79.9% [16.6]) and least exclusive (71.1% [14.6]) in Nebraska. Rising levels of insurer and market concentration were associated with broader and less exclusive networks. Markets with concentrated primary care and insurance markets had the broadest (median [interquartile range {IQR}], 75.0% [60.0%-83.1%]) and least exclusive (median [IQR], 63.7% [52.4%-73.7%]) primary care networks among large-group commercial plans, while markets with least concentration had the narrowest (median [IQR], 54.6% [46.8%-67.6%]) and most exclusive (median [IQR], 49.4% [41.9%-56.9%]) networks.
Conclusions and Relevance
In this study, narrower health care networks had a relatively large degree of overlap with other networks in the same geographic area, while broader networks were associated with physician, hospital, and insurance market concentration. These results suggest that many patients could switch to a lower-cost, narrow network plan without losing in-network access to their PCP, although future research is needed to assess the implications for care quality and clinical integration across in-network health care professionals and facilities in narrow network plans.
Provider organizations are increasing in complexity, as hospitals acquire physician practices and physician organizations grow in size. At the same time, hospitals are merging with each other to improve bargaining power with insurers. We analyze 29 quality measures reported to the Center for Medicare and Medicaid Services’ Hospital Compare database for 2008 to 2015 to test whether vertical integration between hospitals and physicians or increases in hospital market concentration influence patient outcomes. Vertical integration has a limited effect on a small subset of quality measures. Yet increased market concentration is strongly associated with reduced quality across all 10 patient satisfaction measures at the 95% confidence level (p < .05) and 6 of the 10 patient satisfaction measures remain statistically significant with a Bonferroni corrected p value (p < .005). Regulators should continue to focus scrutiny on proposed hospital mergers, take steps to maintain competition, and reduce counterproductive barriers to entry.
This paper employs commuter flow data from the 1990 and 2000 Decennial Censuses, and the 2006–2010 American Community Survey to replicate, evaluate, and extend the delineation of commuting zones first proposed by Tolbert and Killian (Labor Market Areas for the United States, 1987). Commuting zones offer a valuable tool for research on regional economies and have long served rural sociologists, economists, and geographers interested in a representation of the economy that acknowledges a connection between urban and rural areas and the capacity of economic systems to cross state lines. Our delineations provide both an update in the form of new delineations for 2010 and a revised set of 1990 and 2000 delineations that benefit from a consistent methodology across decades. We also provide a set of tools for comparing delineations across methods and over time. In presenting our revised delineations, we shed light on the role of expert opinion in the original delineations, the strengths and weaknesses of the original method, and offer suggestions for further revision of this tool that may better reflect the theoretical conception of commuting zones.
The U.S. health-care sector is large and growing—health-care spending in 2011 amounted to $2.7 trillion and 18 percent of GDP. Approximately half of health-care output is allocated via markets. In this paper, we analyze the industrial organization literature on health-care markets, focusing on the impact of competition on price, quality, and treatment decisions for health-care providers and health insurers. We conclude with a discussion of research opportunities for industrial organization economists, including opportunities created by the U.S. Patient Protection and Affordable Care Act. (JEL J15, J24, J71, J81, K31)
Provider consolidation into vertically integrated health systems increased from 2016 to 2018. More than half of US physicians and 72 percent of hospitals were affiliated with one of 637 health systems in 2018. For-profit and church-operated systems had the largest increases in system size, driven in part by a large number of system mergers and acquisitions.
A broad literature has made it clear that geographic units must be selected with care or they are likely to introduce error and uncertainty into results. Nevertheless, researchers often use data “off the shelf” with the implicit assumptions that their observations are consistent with the geographical concept relevant for their research question, and that they are of uniformly high quality in capturing this geographic identity. In this paper, we consider the geographical concept of “labor market” and offer a template for both clarifying its meaning for research and testing the suitability of extant labor-market delineations. We establish a set of metrics for comparing the quality of existing labor-market delineations with respect to the diverse meanings that researchers apply to the concept. Using the fit metrics established here, researchers can explore how delineations vary geographically, how they vary over time, and how this variation may shape research outcomes. Our assessment is that the quality of the extant delineations is relatively high overall. However, we find that different delineations vary significantly in the types of labor markets they represent, and that regional variations in fit within any given delineation may introduce noise or regional bias that merits consideration in any analysis conducted with these units. More broadly, the kinds of metrics we propose here have applicability for many other geographic entities where boundaries and scale can be only imperfectly defined.
Background:
The hospital industry has consolidated substantially during the past two decades and at an accelerated pace since 2010. Multiple studies have shown that hospital mergers have led to higher prices for commercially insured patients, but research about effects on quality of care is limited.
Methods:
Using Medicare claims and Hospital Compare data from 2007 through 2016 on performance on four measures of quality of care (a composite of clinical-process measures, a composite of patient-experience measures, mortality, and the rate of readmission after discharge) and data on hospital mergers and acquisitions occurring from 2009 through 2013, we conducted difference-in-differences analyses comparing changes in the performance of acquired hospitals from the time before acquisition to the time after acquisition with concurrent changes for control hospitals that did not have a change in ownership.
Results:
The study sample included 246 acquired hospitals and 1986 control hospitals. Being acquired was associated with a modest differential decline in performance on the patient-experience measure (adjusted differential change, -0.17 SD; 95% confidence interval [CI], -0.26 to -0.07; P = 0.002; the change was analogous to a fall from the 50th to the 41st percentile) and no significant differential change in 30-day readmission rates (-0.10 percentage points; 95% CI, -0.53 to 0.34; P = 0.72) or in 30-day mortality (-0.03 percentage points; 95% CI, -0.20 to 0.14; P = 0.72). Acquired hospitals had a significant differential improvement in performance on the clinical-process measure (0.22 SD; 95% CI, 0.05 to 0.38; P = 0.03), but this could not be attributed conclusively to a change in ownership because differential improvement occurred before acquisition.
Conclusions:
Hospital acquisition by another hospital or hospital system was associated with modestly worse patient experiences and no significant changes in readmission or mortality rates. Effects on process measures of quality were inconclusive. (Funded by the Agency for Healthcare Research and Quality.).
We consider the effect of mergers between firms whose products are not viewed as direct substitutes for the same good or service, but are bundled by a common intermediary. Focusing on hospital mergers across distinct geographic markets, we show that such combinations can reduce competition among merging hospitals for inclusion in insurers' networks, leading to higher prices (or lower‐quality care). Using data on hospital mergers from 1996–2012, we find support that this mechanism operates within state boundaries: cross‐market, within‐state hospital mergers yield price increases of 7%–9 % for acquiring hospitals, whereas out‐of‐state acquisitions do not yield significant increases.
On December 15, 2011, Phoebe Putney Health acquired the only other hospital in Albany, Georgia-Palmyra Medical Center-despite the Federal Trade Commission's challenge of the merger as anticompetitive. The acquisition was consummated after the district and appellate courts ruled that Phoebe Putney had antitrust immunity due to its regulation by the local Hospital Authority of Albany-Dougherty County. In February 2013, the Supreme Court reversed these rulings and remanded the case back to the lower courts, after Palmyra Medical Center had become part of Phoebe Putney Memorial Hospital, making a divestiture infeasible. The acquisition of Palmyra Medical Center by Phoebe Putney provides an opportunity to study the effects of an otherwise anticompetitive hospital merger subject to local regulation. We found that, after a large price spike in the first post-merger year, the commercial price of inpatient hospital services in Albany, Georgia, moderated toward the control group price in subsequent post-merger years. Regarding quality, we found a significant post-merger reduction in inpatient hospital quality relative to controls across many quality metrics. We discuss the implications of these findings for recent initiatives that grant hospitals antitrust immunity in exchange for local regulation. © 2018 The Author(s). Published by Oxford University Press. All rights reserved.
Hospitals in the United States increasingly belong to multihospital systems that operate in numerous geographic markets. A large literature in management and economics suggests that competition between firms may be softened as a result of multimarket contact- i.e., firms competing with one another in multiple markets simultaneously. Exploiting plausibly exogenous variation in multimarket contact generated by out-of-market consolidation, I find that increases in multimarket contact over the 2000-2010 period led to higher hospital prices. These results suggest that continued hospital consolidation may produce higher prices even if that consolidation only minimally affects within-market concentration.
Policy makers and analysts have been voicing concerns about the increasing concentration of health care providers and health insurers in markets nationwide, including the potential adverse effect on the cost and quality of health care. The Council of Economic Advisers recently expressed its concern about the lack of estimates of market concentration in many sectors of the US economy. To address this gap in health care, this study analyzed market concentration trends in the United States from 2010 to 2016 for hospitals, physician organizations, and health insurers. Hospital and physician organization markets became increasingly concentrated over this time period. Concentration among primary care physicians increased the most, partially because hospitals and health care systems acquired primary care physician organizations. In 2016, 90 percent of Metropolitan Statistical Areas (MSAs) were highly concentrated for hospitals, 65 percent for specialist physicians, 39 percent for primary care physicians, and 57 percent for insurers. Ninety-one percent of the 346 MSAs analyzed may have warranted concern and scrutiny because of their concentration levels in 2016 and changes in their concentrations since 2010. Public policies that enhance competition are needed, such as stricter enforcement of antitrust laws, reducing barriers to entry, and restricting anticompetitive behaviors.
Analyses of hospital mergers typically focus on acquisitions that alter local market concentration. However, as prices are negotiated between hospital systems and insurers, this focus may overlook the impact of cross-market interdependence in the bargaining outcome. Using data on out-of-market acquisitions occurring across the United States from 2000–2010, we investigate the impact of cross-market dependencies on negotiated prices. We find that prices at hospitals acquired by out-of-market systems increase by about 17% more than unacquired, stand-alone hospitals and confirm that out-of-market mergers result in a relaxation of competition, the prices of nearby competitors to acquired hospitals increase by around 8%.
Proponents of hospital consolidation claim that mergers lead to significant cost savings, but there is little systematic evidence backing these claims. For a large sample of hospital mergers between 2000 and 2010, I estimate difference-in-differences models that compare cost trends at acquired hospitals to cost trends at hospitals whose ownership did not change. I find evidence of economically and statistically significant cost reductions at acquired hospitals. On average, acquired hospitals realize cost savings between 4 and 7 percent in the years following the acquisition. These results are robust to a variety of different control strategies, and do not appear to be easily explained by post-merger changes in service and/or patient mix. I then explore several extensions of the results to examine (a) whether the acquiring hospital/system realizes cost savings post-merger and (b) if cost savings depend on the size of the acquirer and/or the geographic overlap of the merging hospitals.
We investigate the impact of hospital system membership on negotiations between hospitals and managed care organizations (MCOs). Previous research finds that system hospitals secure higher reimbursements by exploiting local market concentration. By leveraging system membership in the bargaining game, however, system hospitals may also extract a higher percentage of their value to an MCO. Our findings reveal that more of the observed price gap between system and nonsystem hospitals can be attributed to bargaining power differences than to differences linked to relative concentration. These results highlight the importance of explicitly modeling the bargaining process when evaluating negotiated-price markets more generally.
Traditional analyses of industrial behavior typically link the exercise of market power in an industry to internal features such as demand conditions, concentration, and barriers-to-entry. Nevertheless, some economists have remained concerned that external factors, such as contact across markets, may also play a significant role in determining the level of competitiveness in any particular industry. In this article, we examine the effect of multimarket contact on the degree of cooperation that firms can sustain in settings of repeated competition. We isolate conditions under which multimarket contact facilitates collusion and show that these collusive gains are achieved through modes of behavior that have been identified in previous empirical studies of multimarket firms.
Managed care health insurers in the US restrict their enrollees' choice of hospitals to specific networks. This paper investigates the causes and welfare effects of the observed hospital networks. A simple profit maximization model explains roughly 63 per cent of the observed contracts between insurers and hospitals. I estimate a model that includes an additional effect: hospitals that do not need to contract with all insurance plans to secure demand (for example, providers that are capacity constrained under a limited or selective network) may demand high prices that not all insurers are willing to pay. Hospitals can merge to form "systems" which may also affect bargaining between hospitals and insurance plans. The analysis estimates the expected division of profits between insurance plans and different types of hospitals using data on insurers' choices of network. Hospitals in systems are found to capture markups of approximately 19 per cent of revenues, in contrast to non-system, non-capacity constrained providers, whose markups are assumed to be about zero. System members also impose high penalties on plans that exclude their partners. Providers that are expected to be capacity constrained capture markups of about 14 per cent of revenues. I show that these high markups imply an incentive for hospitals to under-invest in capacity despite a median benefit to consumers of over $330,000 per new bed per year.