A Structural Approach to Market Definition With an Application to the Hospital Industry

Abstract

Market definition is common in merger analysis, and often the decisive factor in antitrust cases. This has been particularly relevant in the hospital industry, where many merger challenges have been denied due to disagreements over geographic market definition. We compare geographic markets produced using frequently employed ad hoc methodologies to structural methods that directly apply the ‘SSNIP test’ to California hospitals. Our results suggest that markets produced using previous methods overstate hospital demand elasticities by a factor of 2.4 to 3.4 and were likely a contributing factor to the permissive legal environment for hospital mergers.

Market power and provider consolidation in physician markets

“…Payment is calculated according to the formula [(work RVU) * (work GPCI) + (Practice Expense RVU) * (Practice Expense GPCI) + (Malpractice RVU) * (Malpractice GPCI)] * [Conversion factor] where the conversion factor is a dollar amount used to convert RVUs to physician payment. 10 Furthermore, we note that this assumption is consistent with subsequent studies that make us of the Capps et al (2003) model (Fournier and Gai 2007;Farrell et al 2011) and that Gaynor et al (2013) find that mergers estimated using the assumptions of Capps et al (2003) produce estimates of price increases due to merger that are close to those that would be implied using other economic models of hospital competition. 11 It is important to note that a limitation of this approach is that it assumes that the WTP-per-quantity for Medicare patients is a reasonable proxy for the WTP-per-quantity unit for private patients.…”

“…Overall, four of the six practice mergers analyzed predict small increases in price, with mergers in Market 1 predicted to result in price increases of less than 2 %, and mergers in Market 2 predicted to result in very small price increases of under 0.1 %. Practice mergers in Market 3 do, however, indicate the potential for price increases that exceed the 5 % threshold often determined by antitrust agencies to have the potential to result in significant consumer harm (Gaynor et al 2013). Specifically, we find that in Market 3, a merger of the two largest cardiology practices could potentially result in an increase in price of approximately 5.9 %, while our estimates indicate that a combination of the two largest ophthalmology practices could also raise price by 5.7 %.…”

“…This property is referred to as independence from irrelevant alternatives (IIA). Gaynor et al (2013) note that the use of detailed consumer-level micro data mitigates the IIA property at the level of a market, since the inflexible substitution patterns generated by the IIA assumption will apply only to consumers with identical characteristics. Thus, in our application, we include in a consumer's utility specification consumer-level characteristics such as the distance from a patient to a provider (which is essentially an interaction of the consumer's location with the provider location), as well as interactions between observable consumer characteristics and distance.…”

“…While it is hoped that these ACOs will coordinate care across networks of providers and realize cost-reducing efficiencies for Medicare patients, the coordination of providers through these organizations may potentially contribute to an increase in bargaining power with private insurers, thereby resulting in higher health care prices, raising concerns with antitrust authorities (Federal Trade Commission & Department of Justice 2011). While the antitrust agencies have instituted "safe-harbor" guidelines for ACO formation that are intended to guard against potentially harmful practice arrangements, these guidelines are voluntary, and use in their construction patient-flow methods which have been shown to understate the degree of market power for health care providers (Elzinga and Swisher 2011;Gaynor et al 2013).…”

Health Care Markets, Regulators, and Certifiers

“…These are described in much greater detail in Gaynor and Town (2011, this Handbook) and I will only briefly summarize them here. Gaynor and Vogt (2003) develop a model of competition in a differentiated goods market and derive estimates of cross-price elasticities of demand. They use these estimates to simulate merger effects, a crucial step in antitrust analysis that we describe below.…”