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Estimating a Hospital Production Function to Evaluate the Effect of Nurse Staffing on Patient Mortality in Taiwan: The Longitudinal Count Data Approach

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  • Yia-Wun Liang

    (Department of Senior Citizen Service Management, National Taichung University of Science and Technology, Taichung, Taiwan.)

  • Wen-Yi Chen

    (Department of Senior Citizen Service Management, National Taichung University of Science and Technology, Taichung, Taiwan.)

  • Yu-Hui Lin

    (Department of Business Administration, Nan Kai University of Technology, Nan-Tou, Taiwan.)

Abstract

This study employed the Random Effect Zero-Inflated Poisson model incorporating a first- order autoregressive structure to estimate the hospital production function. We specifically investigated the effect of nurse staffing on patient mortality in acute-care hospitals under Taiwan universal health insurance system. Our results showed that the probability of being mortality free in the high patient-to-nurse ratio group is 0.019 lower than that in its counterparts and those patients who were in the high patient-to-nurse ratio nursing unit generates 3.419 more deaths than its counterparts. These findings suggested that nurse staffing below target levels in acute-care hospitals is associated with increased mortality. The policymakers should consider healthcare policy that matches staffing with patients’ need for nursing care through setting a shift-based, m

Suggested Citation

  • Yia-Wun Liang & Wen-Yi Chen & Yu-Hui Lin, 2015. "Estimating a Hospital Production Function to Evaluate the Effect of Nurse Staffing on Patient Mortality in Taiwan: The Longitudinal Count Data Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 154-169, December.
    • Handle: RePEc:rjr:romjef:v::y:2015:i:4:p:154-169
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    References listed on IDEAS

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    1. Sule Akkoyunlu & Frank R. Lichtenberg & Boriss Siliverstovs & Peter Zweifel, 2010. "Spurious correlation in estimation of the health production function: A note," Economics Bulletin, AccessEcon, vol. 30(3), pages 2505-2514.
    2. Gaynor, Martin & Town, Robert J., 2011. "Competition in Health Care Markets," Handbook of Health Economics, in: Mark V. Pauly & Thomas G. Mcguire & Pedro P. Barros (ed.), Handbook of Health Economics, volume 2, chapter 0, pages 499-637, Elsevier.
    3. Richard Auster & Irving Leveson & Deborah Sarachek, 1969. "The Production of Health, an Exploratory Study," Journal of Human Resources, University of Wisconsin Press, vol. 4(4), pages 411-436.
    4. Adriana Castelli & Andrew Street & Rossella Verzulli & Padraic Ward, 2015. "Examining variations in hospital productivity in the English NHS," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(3), pages 243-254, April.
    5. Jinhyung Lee & Jeffrey S. McCullough & Robert J. Town, 2013. "The impact of health information technology on hospital productivity," RAND Journal of Economics, RAND Corporation, vol. 44(3), pages 545-568, September.
    6. Barbara A. Mark & David W. Harless & Michael McCue, 2005. "The impact of HMO penetration on the relationship between nurse staffing and quality," Health Economics, John Wiley & Sons, Ltd., vol. 14(7), pages 737-753, July.
    7. Grace Lordan & Eliana Jimenez Soto & Richard P. C. Brown & Ignacio Correa‐Valez, 2012. "Socioeconomic status and health outcomes in a developing country," Health Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 178-186, February.
    8. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    9. Kathleen Carey & James F. Burgess Jr. & Gary J. Young, 2015. "Economies Of Scale And Scope: The Case Of Specialty Hospitals," Contemporary Economic Policy, Western Economic Association International, vol. 33(1), pages 104-117, January.
    10. Daniel B. Hall, 2000. "Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study," Biometrics, The International Biometric Society, vol. 56(4), pages 1030-1039, December.
    11. Badi Baltagi & Francesco Moscone & Elisa Tosetti, 2012. "Medical technology and the production of health care," Empirical Economics, Springer, vol. 42(2), pages 395-411, April.
    12. Brown, Timothy T. & Martinez-Gutierrez, Maria S. & Navab, Bahar, 2014. "The impact of changes in county public health expenditures on general health in the population," Health Economics, Policy and Law, Cambridge University Press, vol. 9(3), pages 251-269, July.
    13. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    14. Grossman, Michael, 1972. "On the Concept of Health Capital and the Demand for Health," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 223-255, March-Apr.
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    More about this item

    Keywords

    health production; hospital production; nurse staffing; patient mortality; Random Effect Zero-Inflated Poisson;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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