The Role of Psychometric Data in Predicting Inpatient Mental Health Service Utilization

The Role of Psychometric Data in Predicting Inpatient Mental Health Service Utilization Inpatient mental health readmission rates have increased dramatically in recent years, with a subset of consumers referred to as revolving-door patients. In an effort to reduce the financial burden associated with these patients and increase treatment efficacy, researchers have begun to explore factors associated with increased service utilization. To date, predictors of increased service usage are remarkably discrepant across studies. Further exploration, therefore, is needed to better explicate the relevance of “traditional” predictors and also to identify alternate strategies that may assist in predicting rehospitalization. One method that may be helpful in identifying patients at high risk is the development of a psychometric screening procedure. As a means to this end, the present study was designed to assess the potential usefulness of psychometric data in predicting mental health service utilization. The sample consisted of 131 patients hospitalized during an index period of 8 months at an acute-care psychiatric hospital. Number of readmissions was recorded in a 9 month post-index period. Measures completed during the index admission included the Brief Psychiatric Rating Scale-Anchored (BPRS-A), Symptom Checklist-90-Revised (SCL-90-R), Kaufman Brief Intelligence Test (K-BIT), and the Beck Depression Inventory (BDI). Results indicated that psychometric data accounted for significant variance in predicting past, present and future mental health service utilization. The BPRS-A, SCL-90-R, and BDI show particular promise as time efficient psychometric screening instruments that may better enable practitioners to identify patients proactively who are at increased risk for rehospitalization. Implications are discussed with regard to patient-treatment matching and discharge planning. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Psychiatric Quarterly Springer Journals

The Role of Psychometric Data in Predicting Inpatient Mental Health Service Utilization

Loading next page...
 
/lp/springer_journal/the-role-of-psychometric-data-in-predicting-inpatient-mental-health-YWZpKFktdK
Publisher
Kluwer Academic Publishers-Plenum Publishers
Copyright
Copyright © 2001 by Human Sciences Press, Inc.
Subject
Medicine & Public Health; Psychiatry; Public Health; Sociology, general
ISSN
0033-2720
eISSN
1573-6709
D.O.I.
10.1023/A:1010396831037
Publisher site
See Article on Publisher Site

Abstract

Inpatient mental health readmission rates have increased dramatically in recent years, with a subset of consumers referred to as revolving-door patients. In an effort to reduce the financial burden associated with these patients and increase treatment efficacy, researchers have begun to explore factors associated with increased service utilization. To date, predictors of increased service usage are remarkably discrepant across studies. Further exploration, therefore, is needed to better explicate the relevance of “traditional” predictors and also to identify alternate strategies that may assist in predicting rehospitalization. One method that may be helpful in identifying patients at high risk is the development of a psychometric screening procedure. As a means to this end, the present study was designed to assess the potential usefulness of psychometric data in predicting mental health service utilization. The sample consisted of 131 patients hospitalized during an index period of 8 months at an acute-care psychiatric hospital. Number of readmissions was recorded in a 9 month post-index period. Measures completed during the index admission included the Brief Psychiatric Rating Scale-Anchored (BPRS-A), Symptom Checklist-90-Revised (SCL-90-R), Kaufman Brief Intelligence Test (K-BIT), and the Beck Depression Inventory (BDI). Results indicated that psychometric data accounted for significant variance in predicting past, present and future mental health service utilization. The BPRS-A, SCL-90-R, and BDI show particular promise as time efficient psychometric screening instruments that may better enable practitioners to identify patients proactively who are at increased risk for rehospitalization. Implications are discussed with regard to patient-treatment matching and discharge planning.

Journal

Psychiatric QuarterlySpringer Journals

Published: Oct 3, 2004

References

  • Factors affecting relapse in patients discharged from a public hospital: Results from a survival analysis
    Mojtabai, R; Nicholson, RA; Neesmith, DH
  • Rehospitalization of older psychiatric inpatients: An investigation of predictors
    Mercer, GT; Molinari, V; Kunik, ME

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off