Journal of General Internal Medicine

, Volume 6, Issue 3, pp 223–228 | Cite as

Risk factors for early unplanned hospital readmission in the elderly

  • Richard L. Reed
  • Robert A. Pearlman
  • David M. Buchner
Original Articles

Abstract

Study objective:To determine the prevalence of early (in 14 days or less) readmissions to the hospital, and to identify risk factors for readmission.

Design:Matched case-control. Cases (n=155) were readmitted to the hospital within 14 days of a hospital discharge, while controls ( n=155) were not. Controls and cases were matched by week of hospital discharge.

Patients:Two-year sequential sample of male veterans aged 65 years and over admitted to the Seattle Veterans Affairs (VA) Medical Center.

Measurements:Data about 31 potential risk factors were abstracted from the medical records.

Results:Three risk factors associated with readmission risk were identified and include two or more hospital admissions in the previous year [odds ratio (OR)=3.06], any medication dosage change in the 48 hours prior to discharge (OR=2.34), and a visiting nurse referral for follow-up (OR=2.78). One protective factor—discharge from the geriatric evaluation unit (GEU) (OR=0.09)—was also determined.

Conclusions:Early unplanned readmissions were frequent at this VA facility. Since the strongest risk factor for readmission was the number of admissions in the previous year, readmissions appeared most commonly among high utilizers of inpatient VA care. This risk factor and others may be useful in identifying a group at high readmission risk, which could be targeted in intervention studies. The reduced readmission rate associated with the GEU suggests one potential intervention to decrease readmission risk.

Key words

elderly readmission risk factor hospital utilization 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Anderson G, Steinberg EP. Hospital readmissions in the Medicare population. N Engl J Med. 1985;311:1349–53.CrossRefGoogle Scholar
  2. 2.
    Anderson G, Steinberg EP: Predicting hospital readmissions in the Medicare population. Inquiry. 1985;22:251–8.PubMedGoogle Scholar
  3. 3.
    Gooding J, Jette AM. Hospital readmissions among the elderly. J Am Geriatr Soc. 1985;33:595–601.PubMedGoogle Scholar
  4. 4.
    Fethke CC, Smith IM, Johnson N. “Risk” factors affecting readmission of the elderly into the health care system. Med Care. 1986;24:429–37.PubMedCrossRefGoogle Scholar
  5. 5.
    Smith DM, Norton JA, McDonald CJ. Nonelective readmissions of medical patients. J Chronic Dis. 1985;38:213–34.PubMedCrossRefGoogle Scholar
  6. 6.
    Phillips RS, Safran C, Cleary PD, Delbanco TL. Predicting emergency readmissions for patients discharged from the medical service of a teaching hospital. J Gen Intern Med. 1987;2:400–5.PubMedCrossRefGoogle Scholar
  7. 7.
    Smith DM, Weinberger M, Katz BP, Moore PS. Postdischarge care and readmissions. Med Care. 1988;26:699–708.PubMedCrossRefGoogle Scholar
  8. 8.
    Andersen R. A behavioral model of families’ use of health services, 1968. Chicago: University of Chicago Center for Health Administration Studies, No. 25, 1968.Google Scholar
  9. 9.
    Andersen R, Newman JF. Societal and individual determinants of medical care utilization in the United States. Milbank Q. 1973;51:95–124.Google Scholar
  10. 10.
    U.S. Department of Health and Human Services. The international classification of disease: ICD-9-CM: diseases: tabular list. 2nd ed. DHHS Publication No. (PHS) 1980;80–1260.Google Scholar
  11. 11.
    Horn SD, Sharkey PD, Bertram DA. Measuring severity of illness: homogeneous case-mix groups. Med Care. 1983;21:14–25.PubMedCrossRefGoogle Scholar
  12. 12.
    Breslow NE, Day NE. Statistical methods in cancer research. Volume 1 — The analysis of case-control studies. 1st ed. Lyon, France: IARC Scientific Publications No. 32, 1982;149.Google Scholar
  13. 13.
    Hosner DW, Lemeshow S. Applied logistic regression. New York: John Wiley and Sons, 1989;82–134.Google Scholar
  14. 14.
    Fitzgerald J. Personal communication, 1989.Google Scholar
  15. 15.
    Wray NP, DeBehnke RD, Ashton CM, Dunn SK. Characteristics of the recurrently hospitalized adult: an information synthesis. Med Care. 1988;26:1046–55.PubMedCrossRefGoogle Scholar
  16. 16.
    McMahon LF Jr, Billi JE. Measurement of severity of illness and the Medicare prospective payment system: state of the art and future directions. J Gen Intern Med. 1983;3:482–90.CrossRefGoogle Scholar
  17. 17.
    Williams MA, Ward SE, Campbell EF. Confusion: testing versus observation. J Gerontol Nursing. 1988;14:25–9.Google Scholar

Copyright information

© Glaxo Inc 1987

Authors and Affiliations

  • Richard L. Reed
    • 1
  • Robert A. Pearlman
    • 2
    • 3
  • David M. Buchner
    • 2
    • 3
  1. 1.the Department of Family and Community Medicine and the Division of Restorative MedicineUniversity of ArizonaTucson
  2. 2.the Health Services Research and Development Field Program, Seattle VA Medical CenterUSA
  3. 3.the Departments of Medicine and Health ServicesUniversity of WashingtonSeattle
  4. 4.Department of Family and Community MedicineUniversity Medical CenterTucson

Personalised recommendations