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界定市场中的竞争:为何以及如何进行?

Defining competition in markets: why and how?

作者信息

Bernstein A B, Gauthier A K

机构信息

Alpha Center, Washington, DC 20036, USA.

出版信息

Health Serv Res. 1998 Dec;33(5 Pt 2):1421-38.

Abstract

OBJECTIVE

To examine the variety of perspectives from which to study the measurement of competition in the healthcare marketplace. Based on a meeting held by The Robert Wood Johnson Foundation in 1996, the authors discuss the complications inherent in the way markets and products are defined by key stakeholders, including economists, policymakers, federal antitrust officials, purchasers, and the competitors themselves.

CONCLUSION

The consensus among those who study this issue is that the way competitors, markets, and geographic areas are currently defined, and the ways of measuring competition, are inadequate, due mainly to the fact that both the measures and the definitions have been constructed from very limited data. Confounding this is the fact that analyses of competition are undertaken for such a wide variety of uses and that creating one database to solve the problems mentioned can be extremely daunting.

RECOMMENDATIONS

Future research should examine ways to develop better definitions of the new healthcare structures that are competing with each other and ways to create measures of competition that include these new structures. To remedy gaps in the ability to measure competition, the field might also benefit from a public use data file, similar to the Area Resource File (ARF), that would contain HMO data according to geographic area, as well as provider data, employer data, payer data, and sociodemographic data.

摘要

目的

探讨研究医疗市场竞争衡量方法的各种视角。基于罗伯特·伍德·约翰逊基金会1996年召开的一次会议,作者们讨论了关键利益相关者(包括经济学家、政策制定者、联邦反垄断官员、购买者以及竞争者自身)界定市场和产品的方式中所固有的复杂性。

结论

研究该问题的人士达成的共识是,目前界定竞争者、市场和地理区域的方式以及衡量竞争的方式并不充分,主要原因在于这些衡量方法和定义均基于非常有限的数据构建而成。更为复杂的是,对竞争进行分析是出于各种各样的用途,而创建一个数据库来解决上述问题可能极其困难。

建议

未来的研究应探讨如何更好地界定相互竞争的新型医疗结构,以及如何创建包含这些新结构的竞争衡量方法。为弥补竞争衡量能力方面的差距,该领域或许还能从一个类似区域资源文件(ARF)的公共使用数据文件中受益,该文件将按地理区域包含健康维护组织(HMO)数据,以及提供者数据、雇主数据、支付方数据和社会人口数据。

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