Skip to main content
SpringerLink
Log in

Predicting rehospitalization and outpatient services from administration and clinical databases

  • Brief Reports
  • Published:
The Journal of Behavioral Health Services & Research Aims and scope Submit manuscript

Abstract

The study tests whether psychiatric services utilization may be predicted from administrative databases without clinical variables equally as well as from databases with clinical variables. Persons with a psychiatric hospitalization at an urban medical center were followed for 1 year postdischarge (N=1384.) Dependent variables included statewide rehospitalization and the number of hours of outpatient services received. Three linear and logistic regression models were developed and cross-validated: a basic model with limited administrative independent variables, an intermediate model with diagnostic and limited clinical indicators, and a full model containing additional clinical predictors. For rehospitalization, the clinical cross-validated model accounted for twice the variance accounted by the basic model (adjusted R2=.13 and .06, respectively). For outpatient hours, the basic cross-validated model performed as well as the clinical model (adjusted R2=.36 and .34, respectively.) Clinical indicators such as assessment of functioning and co-occurring substance use disorder should be considered for inclusion in predicting rehospitalization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Mazade MA, Lutterman T, Glover R. State mental health agency performance measure initiatives in the public mental health system. Center for Mental Health Services. In: Mandersheid RW, Henderson MJ, eds.Mental Health, United States, 1998. Washington, DC: Supt. of Docs., US Government Printing Office; 1998:52–59. DHHS Publication No. (SMA)99-3285.

    Google Scholar 

  2. Teague GB, Ganju V, Hornik JA, et al. The MHSIP mental health report card.Evaluation Review. 1997;21:330–341.

    Google Scholar 

  3. Banks SM, Pandiani JA, Schacht L, et al. A risk-adjusted measure of hospitalization rates for evaluating community mental health program performance.Administration and Policy in Mental Health. 1999;26:269–279.

    Google Scholar 

  4. Hornbrook MC, Goodman MJ. Assessing relative health plan risk with the RAND-36 health survey.Inquiry. 1995;32:56–74.

    Google Scholar 

  5. Fowles JB, Weiner JP, Knutson D, et al. Taking health status into account when setting capitation rates.JAMA. 1996;276:1316–1321.

    Google Scholar 

  6. Lee C, Rogal D.Risk Adjustment: A Key to Changing Incentives in the Health Insurance Market. Alpha Center; Washington DC March 1997.

  7. Weiner JP, Dobson A, Maxwell SL, et al. Risk-adjusted Medicare capitation rates using ambulatory and inpatient diagnoses.Health Care Financing Review. 1996;17(3):77–99.

    Google Scholar 

  8. Newhouse JP, Manning WG, Keeler EB, et al. Adjusting capitation rates using objective health measures and prior utilization.Health Care Financing Review. 1989;10:41–54.

    Google Scholar 

  9. Ettner SL, Frank RG.Risk Adjustment for Mental Health and Substance Abuse. Center for Mental Health Service, Substance Abuse and Mental Health Services Administration; Washington DC January 1999.

  10. Kapur K, Young AS, Murata D. Risk adjustment for high utilizers of public mental health care.The Journal of Mental Health Policy and Economics. 2000;3:129–137.

    Google Scholar 

  11. Vogel S, Huguelet P. Factors associated with multiple admissions to a public psychiatric hospital.Acta Psychiatrica Scandinavica. 1997;95:244–253.

    Google Scholar 

  12. Doering S, Muller E, Kopcke W, et al. Predictors of relapse and rehospitalization in schizophrenia and schizoaffective disorder.Schizophrenia Bulletin. 1998;24:87–98.

    Google Scholar 

  13. Mercer GT, Molinari V, Kunik ME, et al. Rehospitalization of older psychiatric inpatients: an investigation of predictors.Gerontologist. 1999;39:591–598.

    Google Scholar 

  14. Olfson M, Mechanic D, Boyer CA, et al. Assessing clinical predictions of early rehospitalization in schizophrenia.Journal of Nervous and Mental Disease. 1999;187:721–729.

    Google Scholar 

  15. Perlick DA, Rosenheck RA, Clarkin JF, et al. Symptoms predicting inpatient service use among patients with bipolar affective disorder.Psychiatric Services. 1999;50:806–812.

    Google Scholar 

  16. Rabinowitz J, Lichtenberg P, Kaplan Z, et al. Rehospitalization rates of chronically ill schizophrenic patients discharged on a regimen of risperadone, olanzapine, or conventional antipsychotics.American Journal of Psychiatry. 2001;158:266–269.

    Google Scholar 

  17. Russo J, Roy-Byrne P, Jaffe C, et al. Psychiatric status, quality of life, and levels of care as predictors of outcomes of acute inpatient treatment.Psychiatric Services. 1997;48:1427–1434.

    Google Scholar 

  18. Hollingsworth EJ, Sweeney JK. Mental health expenditures for services for people with severe mental illnesses.Psychiatric Services. 1997;48:485–490.

    Google Scholar 

  19. Larson MJ, Farrelly MC, Hodgkin D, et al. Payments and use of services for mental health, alcohol, and other drug abuse disorders: estimates from Medicare, Medicaid, and Private Health Plans. Center for Mental Health Services. In: Mandersheid RW, Henderson MJ, eds.Mental Health, United States, 1998. Washington, DC: Supt. of Docs., US Government Printing Office; 1998:124–141. DHHS Publication No. (SMA)99-3285.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Washington Institute for Mental Illness Research and Training, Washington State University, 310 N. Riverpoint Blvd., P. O. Box 1495, 99210, Spokane, WA

    Michael S. Hendryx PhD (Assistant Director), Bruce Stegner PhD (Senior Research Associate) & Dennis G. Dyck PhD (Professor and Director)

  2. Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle

    Joan E. Russo PhD (Research Associate Professor), Richard K. Ries MD (Professor, Director) & Peter Roy-Byrne MD (Professor and Vice Chair, Chief)

  3. Outcomes Assessment and Quality Assurance, Harborview Medical Center, Seattle, Washington

    Joan E. Russo PhD (Research Associate Professor) & Peter Roy-Byrne MD (Professor and Vice Chair, Chief)

  4. Mental Health Division in Department of Social and Health Services, Olympia, Washington

    Bruce Stegner PhD (Senior Research Associate)

  5. Outpatient Psychiatry and Addiction Services, Harborview Medical Center, Seattle, Washington

    Richard K. Ries MD (Professor, Director)

Authors
  1. Michael S. Hendryx PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joan E. Russo PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bruce Stegner PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dennis G. Dyck PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Richard K. Ries MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Peter Roy-Byrne MD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael S. Hendryx PhD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hendryx, M.S., Russo, J.E., Stegner, B. et al. Predicting rehospitalization and outpatient services from administration and clinical databases. The Journal of Behavioral Health Services & Research 30, 342–351 (2003). https://doi.org/10.1007/BF02287322

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02287322

Keywords

Search

Navigation