National Health Insurance and Technology Adoption: Evidence from Taiwan

By Chou, Shin-Yi; Liu, Jin-Tan et al. | Contemporary Economic Policy, January 2004 | Go to article overview

National Health Insurance and Technology Adoption: Evidence from Taiwan


Chou, Shin-Yi, Liu, Jin-Tan, Hammitt, James K., Contemporary Economic Policy


I. INTRODUCTION

Persistent growth of health-care expenditures, extensive use of third-party payment mechanisms, and rapid technological progress have been prominent features of the medical-care sector over recent decades (Weisbrod, 1991). A more generous health-insurance system results in higher expected health-care utilization due to moral hazard and thus higher expected returns for health-care providers. This mechanism motivates the growth of biomedical research and encourages hospitals to adopt and use expensive medical technologies. Reciprocally, the dramatic progress of medical technology changes the demand for health insurance. Given that technological change is predominantly cost-increasing, people respond to higher levels of uncertainty about medical costs by demanding more insurance. (1)

Despite these conceptually well-established causalities, direct empirical evidence about the relationship between health insurance and changes in medical technology is limited. The purpose of this study is to provide such evidence. The authors examine the effects of Taiwan's 1995 implementation of National Health Insurance (NHI) on technology adoption, ownership, and utilization by hospitals. NHI provides coverage to nearly all Taiwanese residents. It replaced a set of worker insurance programs that typically did not cover workers' dependents. In the first three years after implementation, the insured population increased by 70%.

The adoption of NHI provides an opportunity to test the effects of insurance on demand for medical technology that is relatively uncontaminated by reverse causality. First, although rising health-care costs provided impetus for development of NHI, the program was adopted nationwide, replacing previous insurance programs, and so the change in coverage is exogenous to any given hospital. Second, the timing of adoption was primarily motivated by political factors rather than by developments in the health-care sector. NHI was proposed in 1984 and was initially scheduled for implementation in 2000. During the chaotic political situation of the late 1980s and 1990s, the political party in power (the Kuomingtung) attempted to consolidate its position by advancing the implementation of NHI to 1995. These factors suggest that the 1995 implementation of NHI may be viewed as exogenous to the adoption, ownership, and utilization of medical technologies by hospitals, and so one may identify its effect on technology adoption without contamination by the reciprocal effect of technology adoption on health-insurance reform.

This article employs difference-in-differences estimates to control for systematic structural changes in health-care-technology use. The authors use private hospitals as the treatment group, and public teaching and public nonteaching hospitals as control groups. The authors anticipate that private hospitals are the most responsive to changes in financial conditions associated with implementation of NHI and expect that public nonteaching hospitals responded more slowly than private hospitals to adoption of NHI. These hospitals are subsidized by the government and have weaker financial incentives to respond to the policy change. Moreover, managerial decisions at these hospitals often entail a long bureaucratic process. The authors also anticipate that public teaching hospitals responded more slowly because these hospitals' technology decisions are affected by their teaching mission as well as by financial factors. Prior to the reform, public teaching hospitals had acquired and used technologies more extensively than private and public nonteaching hospitals. By exploiting the variation in responses to the NHI reform, the authors attempt to identify its effect on technology adoption, ownership, and utilization for private hospitals.

This article employs a random-effect panel probit to estimate the probabilities of adoption and ownership of specific technologies and a panel tobit to estimate the use of these technologies.

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