Advertisement

Health Care Management Science

, Volume 19, Issue 3, pp 241–248 | Cite as

The cost of hospital readmissions: evidence from the VA

  • Kathleen Carey
  • Theodore Stefos
Article

Abstract

This paper is an examination of hospital 30-day readmission costs using data from 119 acute care hospitals operated by the U.S. Veterans Administration (VA) in fiscal year 2011. We applied a two-part model that linked readmission probability to readmission cost to obtain patient level estimates of expected readmission cost for VA patients overall, and for patients discharged for three prevalent conditions with relatively high readmission rates. Our focus was on the variable component of direct patient cost. Overall, managers could expect to save $2140 for the average 30-day readmission avoided. For heart attack, heart failure, and pneumonia patients, expected readmission cost estimates were $3432, $2488 and $2278. Patient risk of illness was the dominant driver of readmission cost in all cases. The VA experience has implications for private sector hospitals that treat a high proportion of chronically ill and/or low income patients, or that are contemplating adopting bundled payment mechanisms.

Keywords

Hospital Readmission Cost VA 

Notes

Acknowledgments

Funding for this study was provided by the VA Office of Quality, Safety and Value. The authors also acknowledge Eileen Moran, Peter Almenoff, and the efforts of the VA Office of Productivity, Efficiency and Staffing in support of this work. The opinions are solely those of the authors, and do not necessarily reflect those of the U.S. Department of Veterans Affairs or Boston University.

References

  1. 1.
    Jencks SF, Williams MV, Coleman EA (2009) Rehospitalizations among patients in the medicare fee-for-service program. N Engl J Med 360:1418–1428CrossRefGoogle Scholar
  2. 2.
    Cutler DM (2010) How health care reform must bend the cost curve. Health Aff 29:1131–1135CrossRefGoogle Scholar
  3. 3.
    Mullahy J (1998) Much ado about two: reconsidering retransformation and the two-part model in health econometrics. J Health Econ 17:247–281CrossRefGoogle Scholar
  4. 4.
    McCullagh P, Nelder JA (1989) Generalized linear models. Chapman & Hall, LondonCrossRefGoogle Scholar
  5. 5.
    Carey K, Stefos T (2011) Measuring the cost of hospital adverse patient safety events. Health Econ 20:1417–1430CrossRefGoogle Scholar
  6. 6.
    Manning WG, Mullahy J (2001) Estimating log models: to transform or not to transform? J Health Econ 20:461–494CrossRefGoogle Scholar
  7. 7.
    Barnett PG (2009) An improved set of standards for finding cost for cost-effectiveness analysis. Med Care 47:S82–S88CrossRefGoogle Scholar
  8. 8.
    Behnood B, Wayda B, Bao H, Ross JS, Xu X, Chaudhry S, Spertus JA, Bernheim SM, Lindenauer PK, Krumholz HM (2014) Place of residence and outcomes of patients with heart failure. Circ Cardiovasc Qual Outcomes. doi: 10.1161/CIRCOUTCOMES.113.000911 Google Scholar
  9. 9.
    Hu J, Gonsahn MD, Nerenz DR (2014) Socioeconomic status and readmission: evidence from an urban teaching hospital. Health Aff 33:1–8CrossRefGoogle Scholar
  10. 10.
    Medicare Payment Advisory Commission. June (2013). Refining the hospital readmission reduction program. In: report to the congress: medicare and the health care delivery systemGoogle Scholar
  11. 11.
    Ash AS, Ellis RP, Pope GC, Ayanian JZ, Bates DW, Burstin H, Iezzoni LI, MacKay E, Yu W (2000) Using diagnoses to describe populations and predict costs. Health Care Financ Rev 21:7–28Google Scholar
  12. 12.
    Ellis RP, Pope GC, Iezzoni LI et al (1996) Diagnosis-based risk adjustment for medicare capitation payments. Health Care Financ Rev 17:101–128Google Scholar
  13. 13.
    Friedman B, Jiang HJ, Elixhauser A, Segal A (2006) hospital inpatient costs for adults with multiple chronic conditions. Med Care Res Rev 63:327–346CrossRefGoogle Scholar
  14. 14.
    Friedman B, Jiang J, Elixhauser A (2008) Costly hospital readmissions and complex chronic illness. Inquiry 45:408–421Google Scholar
  15. 15.
    Kaboli PJ, Go JT, Hockenberry J, Glasgow JM, Johnson SR, Rosenthal GE, Jones MP, Vaughn-Sarrazin M (2012) Associations between reduced hospital length of stay and 30-day readmission rate and mortality: 14-year experience in 129 Veterans Affairs hospitals. Ann Intern Med 157:837–45CrossRefGoogle Scholar
  16. 16.
    Carey K (2014) Measuring the hospital length of stay/readmission cost trade-off under a bundled payment mechanism. Health Econ. doi: 10.1002/hec.3061 Google Scholar
  17. 17.
    Coleman EA, Parry C, Chalmers S et al (2006) The care transitions intervention: results of a randomized controlled trial. Arch Intern Med 166:1822–1828CrossRefGoogle Scholar
  18. 18.
    Kind AJ, Smith MA, Frytak JR et al (2007) Bouncing back: patterns and predictors of complicated transitions 30 days after hospitalizations for acute ischemic stroke. J Am Geriatr Soc 55:365–373Google Scholar
  19. 19.
    Carey K (2000) A multilevel modeling approach to analysis of patient costs under managed care. Health Econ 9:435–446CrossRefGoogle Scholar
  20. 20.
    O’Brien W, Chen Q, Hull HJ, Shwartz M, Borzecki AM, Hanchate A, Rosen AK (2014) What is the value of adding medicare data in estimating VA hospital readmission rates? Health Serv Res. doi: 10.1111/1475-6773.12207 Google Scholar
  21. 21.
    Manning WG (1998) The logged dependent variable, heteroscedasticity, and the retransformation problem. J Health Econ 17:283–295CrossRefGoogle Scholar
  22. 22.
    Duan N (1983) Smearing estimate: a nonparametric retransformation method. J Am Stat Assoc 78:605–610CrossRefGoogle Scholar
  23. 23.
    Blough DK, Ramsey SD (2000) Using generalized linear models to assess medical care costs. Health Serv Outcome Res Methodol 1:185–202CrossRefGoogle Scholar
  24. 24.
    Liang KY, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73:13–22CrossRefGoogle Scholar
  25. 25.
    Kahn JM, Werner RM, Carson SS, Iwashyna TJ (2012) Variation in long-term acute care hospital use after intensive care. Med Care Res Rev 69:339–350CrossRefGoogle Scholar
  26. 26.
    Medicare Payment Advisory Commission. June (2004). Defining long-term care hospitals. In: report to the congress: new approaches in medicareGoogle Scholar
  27. 27.
    Belsley DA, Kuh E, Welsch RE (1980) Regression diagnostics: identifying influential data and sources of collinearity. Wiley, New YorkCrossRefGoogle Scholar
  28. 28.
    Pan W (2001) Akaike’s information criterion in generalized estimating equations. Biometrics 57:120–125CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Boston University School of Public HealthBostonUSA
  2. 2.VA Office of Productivity, Efficiency and StaffingBoston University School of Public HealthBedfordUSA

Personalised recommendations