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      Subjective assessments of comorbidity correlate with quality of life health outcomes: Initial validation of a comorbidity assessment instrument

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          Interventions to improve care for persons with chronic medical conditions often use quality of life (QOL) outcomes. These outcomes may be affected by coexisting (comorbid) chronic conditions as well as the index condition of interest. A subjective measure of comorbidity that incorporates an assessment of disease severity may be particularly useful for assessing comorbidity for these investigations.


          A survey including a list of 25 common chronic conditions was administered to a population of HMO members age 65 or older. Disease burden (comorbidity) was defined as the number of self-identified comorbid conditions weighted by the degree (from 1 to 5) to which each interfered with their daily activities. We calculated sensitivities and specificities relative to chart review for each condition. We correlated self-reported disease burden, relative to two other well-known comorbidity measures (the Charlson Comorbidity Index and the RxRisk score) and chart review, with our primary and secondary QOL outcomes of interest: general health status, physical functioning, depression screen and self-efficacy.


          156 respondents reported an average of 5.9 chronic conditions. Median sensitivity and specificity relative to chart review were 75% and 92% respectively. QOL outcomes correlated most strongly with disease burden, followed by number of conditions by chart review, the Charlson Comorbidity Index and the RxRisk score.


          Self-report appears to provide a reasonable estimate of comorbidity. For certain QOL assessments, self-reported disease burden may provide a more accurate estimate of comorbidity than existing measures that use different methodologies, and that were originally validated against other outcomes. Investigators adjusting for comorbidity in studies using QOL outcomes may wish to consider using subjective comorbidity measures that incorporate disease severity.

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          Most cited references 38

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          Comorbidity measures for use with administrative data.

          This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets. The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other aspects of the patient's condition, development of a comorbidity algorithm, and testing on heterogeneous and homogeneous patient groups. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in California in 1992 (n = 1,779,167). Outcome measures were those commonly available in administrative data: length of stay, hospital charges, and in-hospital death. A comprehensive set of 30 comorbidity measures was developed. The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Several comorbidities are described that are important predictors of outcomes, yet commonly are not measured. These include mental disorders, drug and alcohol abuse, obesity, coagulopathy, weight loss, and fluid and electrolyte disorders. The comorbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently among different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive approach to identifying comorbidities and separates them from the primary reason for hospitalization, resulting in an expanded set of comorbidities that easily is applied without further refinement to administrative data for a wide range of diseases.
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            Cumulative illness rating scale.

             W Linn,  B Linn,  Jasmine Linn (1968)
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              The Self-Administered Comorbidity Questionnaire: a new method to assess comorbidity for clinical and health services research.

              To develop the Self-Administered Comorbidity Questionnaire (SCQ) and assess its psychometric properties, including the predictive validity of the instrument, as reflected by its association with health status and health care utilization after 1 year. A cross-sectional comparison of the SCQ with a standard, chart abstraction-based measure (Charlson Index) was conducted on 170 inpatients from medical and surgical care units. The association of the SCQ with the chart-based comorbidity instrument and health status (short form 36) was evaluated cross sectionally. The association between these measures and health status and resource utilization was assessed after 1 year. The Spearman correlation coefficient for the association between the SCQ and the Charlson Index was 0.32. After restricting each measure to include only comparable items, the correlation between measures was stronger (Spearman r = 0.55). The SCQ had modest associations with measures of resource utilization during the index admission, and with health status and resource utilization after 1 year. The SCQ has modest correlations with a widely used medical record-based comorbidity instrument, and with subsequent health status and utilization. This new measure represents an efficient method to assess comorbid conditions in clinical and health services research. It will be particularly useful in settings where medical records are unavailable.

                Author and article information

                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central (London )
                1 September 2005
                : 3
                : 51
                [1 ]Kaiser Permanente, PO Box 378066, 80237-8066 Denver, CO, USA
                [2 ]Department of Family Medicine, University of Colorado Health Sciences Center, Denver, CO, USA
                [3 ]Colorado Health Outcomes Program, University of Colorado Health Sciences Center, Denver, CO, USA
                Copyright © 2005 Bayliss et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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