Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Risk-Adjusted Mortality Rates as a Potential Outcome Indicator for Outpatient Quality Assessments

Bibliographic Data

ID9103066
AuthorsAlfredo J Selim (Health Services Research & Development, corresponding author), Dan R Berlowitz (0000-0002-8783-5611, Boston Medical Center, corresponding author), Graeme Fincke (VA Boston Healthcare System, corresponding author), Amy K Rosen (0000-0002-7539-7749, Health Services Research & Development, corresponding author), Xinhua Steve Ren (0000-0003-0412-4134, Health Services Research & Development, corresponding author), Cindy L Christiansen (Health Services Research & Development, corresponding author), Zhongxhiao Cong (Health Services Research & Development, corresponding author), Austin Lee (0000-0003-2811-7385), J Austin Lee (0000-0002-0252-3716, Boston University, corresponding author), Lewis Kazis, Lewis E Kazis (0000-0003-1800-5849, Health Services Research & Development, corresponding author)
Year2002
Volume40
Issue3
Pages237-245
Publication date2002-03-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-200203000-00007
PMID11880796
OpenAlexW1969031746
LanguageEN
Citations received5
References cited45

OBJECTIVE: The quality of outpatient medical care is increasingly recognized as having an important impact on mortality. We examined whether a clinically credible risk adjustment methodology can be developed for outpatient quality assessments. RESEARCH DESIGN: This study used data from the 1998 National Survey of Ambulatory Care Patients, a prospective monitoring system of outcomes of patients receiving ambulatory care in the Veterans Affairs (VA) integrated service networks. SUBJECTS: Thirty-one thousand eight hundred twenty-three patients were followed for 18 months. MEASURES: The main study outcome measures were observed and risk-adjusted mortality rates. RESULTS: Of the 31,823 patients, 1559 (5%) died during the 18-months of follow-up. Observed mortality rates across the 22 VA integrated service networks varied significantly from 3.3% to 6.7% (P <0.001). Age, gender, comorbidities (Charlson Index), physical health, and mental health were significant predictors of dying. The resulting risk-adjusted mortality model performed well in cross-validated tests of discrimination (c-statistic = 0.768; 95% CI, 0.749-0.788) and calibration. Analysis of variance confirmed that the 22 integrated service networks differed in their average level of expected risk (P <0.001). Risk-adjusted rates and ranks of the networks differed considerably from unadjusted ratings. CONCLUSIONS: Risk-adjusted mortality rates may be a useful outcome measure for assessing quality of outpatient care. We have developed a clinically credible risk adjustment model with good performance properties using sociodemographics, diagnoses, and functional status data. The resulting risk adjustment model altered assessments of the performance of the integrated service networks when compared with the unadjusted mortality rates

Ambulatory · Ambulatory care · Health care · Mortality rate · Risk assessment · Veterans Affairs · Demography · Emergency Medicine · Healthcare Policy and Management · Internal Medicine · Medicine · Patient Satisfaction in Healthcare · Primary Care and Health Outcomes

  • Functional status measures for integrating medical and social care

    Open Access•Margaret G Stineman, Richard N Ross et al.•International Journal of…•2005

  • Multimorbidity and mortality in older adults

    Open Access•Bruno Pereira Nunes, Thaynã Ramos Flores et al.•Archives of Gerontology and…•2016

  • Change in health status and mortality as indicators of outcomes

    Open Access•Alfredo J Selim, Lewis E Kazis et al.•Quality of Life Research•2007

  • Risk-Adjusted Mortality as an Indicator of Outcomes

    Alfredo J Selim, Lewis E Kazis et al.•Medical Care•2006

  • Use of Antidepressant Medications

    Alaa Hamed, Austin Lee et al.•Medical Care•2004

  • An Introduction to the Bootstrap

    Bradley Efron, Robert Tibshirani et al.•Introduction to the Bootstrap•1994

  • Human error

    Open Access•James Reason•BMJ•2000

  • Health-Related Quality of Life in Patients Served by the Department of Veterans Affairs

    Lewis E Kazis, Donald R Miller et al.•A.M.A. Archives of Internal…•1998

  • Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases

    Open Access•Richard A Deyo, R DEYO•Journal of Clinical Epidemiology•1992

  • A new method of classifying prognostic comorbidity in longitudinal studies

    Open Access•Mary E Charlson, Peter Pompei et al.•Journal of Chronic Diseases•1987

  • Judging hospitals by severity-adjusted mortality rates

    Lisa I Iezzoni, Arlene S Ash et al.•American Journal of Public Health•1996

  • Seven chronic conditions

    Lois M Verbrugge, Donald L Patrick•American Journal of Public Health•1995

  • Profiling Outcomes of Ambulatory Care

    Dan R Berlowitz, Arlene S Ash et al.•Medical Care•1998

  • The Ratio of Observed-to-Expected Mortality as a Quality of Care Indicator in Non-Surgical VA Patients

    William R Best, Diane C Cowper•Medical Care•1994

  • A State-of-the-Art Conference on Databases Pertaining to Veterans' Health

    Carol M Ashton, Terri J Menke et al.•Medical Care•1996

  • Reinventing VA Health Care

    KENNETH W KIZER, John G Demakis et al.•Medical Care•2000

  • Accuracy of Risk-Adjusted Mortality Rate As a Measure of Hospital Quality of Care

    J W Thomas, Timothy P Hofer•Medical Care•1999

  • Development and Application of a Population-Oriented Measure of Ambulatory Care Case-Mix

    Jonathan P Weiner, Barbara Starfield et al.•Medical Care•1991

  • The Measurement of Hospital Case Mix

    WANDA W YOUNG, Robert B Swinkola et al.•Medical Care•1982

  • Predicting In-Hospital Mortality

    Lisa I Iezzoni, Arlene S Ash et al.•Medical Care•1992

  • What Information Do Consumers Want and How Will They Use It

    John E Ware•Medical Care•1995

  • The MOS Short-form General Health Survey

    Anita L Stewart, Ron D Hays et al.•Medical Care•1988

Unique citing works5
Citations per year0,23
Citation span2004 - 2016 (13)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 4

Tools

Open DOISci-Hub
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae