Estimating the effect of early discharge policy on readmission rate. An instrumental variable approach
Eugenia Amporfu
.
DOI: 10.4236/health.2010.25075   PDF    HTML     4,703 Downloads   8,578 Views   Citations

Abstract

Early discharge policy, common in the developed countries, refers to the reduction of hospital length of stay as a way of reducing the cost of care. The effect of the policy on quality of care has received a lot of attention in the literature. Some of the earlier papers have ignored the endogeneity of length of stay in the readmission equation, an approach that could lead to inconsistent estimation. This study develops a statistical technique for the consistent estimation of the effect of the early discharge policy. An instrument that can be used extensively across different diagnostic groups is provided, hence solving the difficult problem of finding an instrument for length of stay. The exogeneity test in Gorgger (1990), the test for weak instruments in Staiger and Stock (1997) as well as the Hensen (1982) for over identification confirmed respectively that length of stay is endogenous the instrument is strong and the valid.

Share and Cite:

Amporfu, E. (2010) Estimating the effect of early discharge policy on readmission rate. An instrumental variable approach. Health, 2, 504-510. doi: 10.4236/health.2010.25075.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Thomspon, A.H., Sauders, A.L.D., Cumming D.C. and Thanigasalam, N. (2003) Post-maternity outcomes following health care reform in Alberta: 1992-1996. Canadian Journal of Public Health, 94(4), 104-108.
[2] Gazmararian, J.A. and Koplan, J.P. (1996) Length-of- stay after delivery: Managed care versus fee-for-service. Health Affairs, 15(4), 74-80.
[3] Kosecoff, J., Kahn, K., Rogers, W., Reinisch, E., Sherwood, M., Rubenstein, L., Draper, D., Roth, C., Chew, C. and Brook, R. (1990) Prospective payment system and impairment at discharge: ‘The quicker and sicker’ story revisited. Journal of the American Medical Association, 264(15), 1980-1983.
[4] Tai-Seale, M., LoSasso, A.T., Freund, D.A. and Gerber, S.E. (2001) The long-term effects of medicaid managed care on obstetric care in three California counties. Health Services Research, 36(4), 751-771.
[5] Rubenstein, L., Kahn, K., Reinisch, E., Sherwood, M., Rogers, W., Karnberg, Draper, D. and Brook, R. (1990) Changes in quality of care for five diseases measured by implicit review. Journal of the American Medical Association, 264(15), 1981-1986.
[6] Kahn, K., Rogers, W., Rubenstein, L., Sherwood, M., Reinisch, E., Keeler, E., Draper, D., Kosecoff, J. and Brook. R. (1990) Comparing outcomes of care before and after implementation of the DRG-based prospective payment system. Journal of the American Medical Association, 264(15), 1984-1988.
[7] Keeler, E., Kahn, K., Draper, D., Sherwood, M., Rubenstein, L., Reinisch, E., Kosecoff, J. and Brook, R. (1990) Changes in sickness at admission following the introduction of the prospective payment system. Journal of the American Medical Association, 264, 1962-1968.
[8] Iezzoni, L.I., (1994) Risk adjustment for measuring health care outcomes. Health Administration Press, Ann Arbor, IM.
[9] Gowrinsandaran, G. and Town, R.J. (1999) Estimating the quality of care in hospitals using instrumental variables. Journal of Health Economics, 18(6), 747-767.
[10] Heggestad, T. (2002) Do hospital length of stay and staffing ratio affect elderly patient’s risk of readmission? A nation-wide study of Norwegian hospitals. Health Services Research, 37(3), 647-665.
[11] Malkin, J.D., Broder, M.S. and Keeler, E. (2000) Do longer postpartum stays reduce newborn readmissions’ analysis using instrumental variables. Health Services Research, 35(5), 1071-1091.
[12] Amporfu, E. (2008) Quality effect of early discharge of maternity patients: Does hospital specialization matter? Forum for Health Economics & Policy. Health Econmics, 11(2). http://www.bepress.om/fhep/11/2/11
[13] Staiger, D. and Stock, J.H. (1997) Instrumental variables regression. Econometrica, 65, 557-586.
[14] Grogger, J. (1990) A simple test for exogeneity in probit and logit, and poisson regression models. Economics Letters, 33(4), 329-332.
[15] Hensen, L. (1982) Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029-1054.
[16] Gazmararian, J.A., Koplan, J.P., Cogswell, M.E., Bailey, C.M., Davis, N.A. and Cutler, C.M. (1997) Maternity experiences in a managed care organization. Health Affairs, 16(3), 198-208
[17] Wray, N.P., Hollingsworth, J.C., Petersen, N.J. and Aston, C.M. (1997) Case-mix adjustment using administrative databases: A paradigm to guide future research, Medical Care Research and Review, 54(3), 326-356.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.