Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-30T19:42:03.788Z Has data issue: false hasContentIssue false
  • English
  • Français

Technology and Staffing in Japanese University Hospitals: Government Versus Private

Published online by Cambridge University Press:  10 March 2009

William B. Vogt ,
Layanta Bhattacharya ,
Scott Kupor ,
Aki Yoshikawa  and
Toshitaka Nakahara
William B. Vogt
Affiliation:
Stanford University
Layanta Bhattacharya
Affiliation:
Stanford University
Scott Kupor
Affiliation:
Stanford University
Aki Yoshikawa
Affiliation:
Stanford University
Toshitaka Nakahara
Affiliation:
National Institute of Public Health, Japan
Get access Rights & Permissions [Opens in a new window]

Abstract

We examined staffing levels, acquisition of medical technologies, and utilization of those technologies in private and government teaching hospitals in Japan. Adjusting for size and case mix, we found that government hospitals acquire more technology, use that technology less, and employ a more highly skilled staff than do private hospitals.

Type
General Essays
Information
International Journal of Technology Assessment in Health Care , Volume 12 , Issue 1 , Winter 1996 , pp. 93 - 103
Copyright
Copyright © Cambridge University Press 1996

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.American Hospital Association. Hospital statistics, 1989–90 ed. Chicago, IL: American Hospital Association, 1989.Google Scholar
2.Aoki, K., Bhattacharya, J., Vogt, W. B. et al. Measuring technical efficiencies of Japanese general hospitals: A DEA analysis of public vs. private hospitals (mimeo). Stanford: Asia/ Pacific Research Center, 1995.Google Scholar
3.Becker, E., & Sloan, F.Hospital ownership and performance. Economic Inquiry, 1985, 23, 21–36.Google Scholar
4.Cowing, T., & Holtman, A.Multiproduct short-run hospital cost functions: Empirical evidence and policy implications from cross-section data. Southern Economic Journal, 1983, 49, 637–53.CrossRefGoogle Scholar
5.Duffy, S. Q.Do competitive hospitals really adopt technology faster: An analysis of the influence of alternative relevant market definitions. Eastern Economic Journal, 1992, 18, 187–208.Google Scholar
6.Fournier, G. M., & Mitchell, J. M.Hospital costs and competition for services: A multiproduct analysis. Review of Economics and Statistics, 1992, 74, 627–34.CrossRefGoogle Scholar
7.Granneman, T., Brown, R., & Pauly, M.Estimating hospital costs: A multiple-output approach. Journal of Health Economics, 1986, 5, 107–27.CrossRefGoogle Scholar
8.Greene, W. H.Econometric analysis. New York: MacMillan, 1990.Google Scholar
9.Grosskopf, S., & Valdmanis, V. Measuring hospital performance: A non-parametric approach. Journal of Health Economics, 1987, 89–107.CrossRefGoogle Scholar
10.Holt, M., Ishikawa, K. B., Kaihara, S., & Yoshikawa, A.Medical ivory towers and the high cost of health care. Stanford: Asia/Pacific Research Center, 1992.Google Scholar
11.Jolly, P., & Hudley, D. M.AAMC data book: Statistical information related to medical education. Washington, DC: AAMC, 1991.Google Scholar
12.Kopit, W. G., & McCann, R. W.Toward a definitive antitrust standard for nonprofit hospital mergers. Journal of Health Politics, Policy, and Law, 1988, 14, 635–62.CrossRefGoogle Scholar
13.Lee, M. L.A conspicuous production theory of hospital behavior. Southern Economic Journal, 1971, 38, 48–58.CrossRefGoogle Scholar
14.Lee, R., & Waldman, D.The diffusion of innovations in hospitals: Some econometric considerations. Journal of Health Economics, 1985, 4, 373–80.CrossRefGoogle ScholarPubMed
15.Luft, H., Robinson, J. C., Garnick, D. W. et al. The role of specialized clinical services in competition among hospitals. Inquiry, 1986, 23, 83–94.Google ScholarPubMed
16.Newhouse, J.Toward a theory of non-profit institutions: An economic model of hospitals. American Economic Review, 1970, 60, 64–74.Google Scholar
17.Niki, R.The wide diffusion of CT scanners in Japan. Social Science and Medicine, 1985, 21, 1131–37.CrossRefGoogle ScholarPubMed
18.Niki, R., & Mankovich, N. J.How to balance the wide diffusion of high technology medicine and cost containment: A case study of MRI in Japan (unpublished mimeo). Los Angeles: UCLA School of Public Health, 1993.Google Scholar
19.Niskanen, W.Bureaucracy and representative government. New York: Aldine Atherton, 1971.Google Scholar
20.Okimoto, D. I., & Yoshikawa, A.Japan’s health system: Efficiency and effectiveness in universal care. New York: Falkner & Gray, 1993.Google Scholar
21.Powell, M., & Anesaki, M.Health care in Japan. New York: Routledge, 1990.Google Scholar
22.Register, C. A., & Bruning, E. R.Profit incentives and technical efficiency in the production of hospital care. Southern Economic Journal, 1987, 53, 899–914.CrossRefGoogle Scholar
23.Robinson, J. C.Market structure, employment, and skill mix in the hospital industry. Southern Economic Journal, 1988, 55, 315–25.CrossRefGoogle Scholar
24.Robinson, J. C., & Luft, H. S.The impact of hospital market structure on patient volume, average length of stay, and the cost of care. Journal of Health Economics, 1985, 4, 333–56.Google Scholar
25.Russell, L. B.Technology in hospitals: Medical advances and their diffusion. Washington, DC: Brookings Institute, 1979.CrossRefGoogle Scholar
26.Sloan, F. A., & Steinwald, B.Insurance, regulation, and hospital costs. Lexington: Lexington Books, 1980.Google Scholar
27.Sloan, F. A.Valvona, J., Perrin, J. M., & Adamache, K. W.Diffusion of surgical technology: An exploratory analysis. Journal of Health Economics, 1986, 5, 31–61.CrossRefGoogle Scholar
28.Technology Marketing Group. Aggregate site data. Des Plaines, IL: TMG, 1994.Google Scholar
29.Tobin, J.Estimation of relationships for limited dependent variables. Econometrica, 1958, 16, 24–36.CrossRefGoogle Scholar
30.Valdmanis, V.Ownership and technical efficiency of hospitals. Medical Care, 1990, 28, 552–61.CrossRefGoogle ScholarPubMed
31.Valdmanis, V.Sensitivity analysis for DEA models: An empirical example using public vs. NFP hospitals. Journal of Public Economics, 1992, 48, 185–205.CrossRefGoogle Scholar