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Martin, Andrew J.; Stockler, Martin
doi: 10.1177/016327879802100202pmid: 10183342
This article reviews the different ways in which quality-of-life assessment has been applied to and has affected health care research and practice. A schema that describes the steps involved in the ongoing challenge of improving health outcomes is used to structure the review. The role of quality-of-life assessment is addressed with regard to: the identification of health problems, the evaluation of new treatments, the formulation of treatment guidelines and health policies, the delivery of optimal care in practice, and the assessment of outcomes in the wider community. The benefit of quality-of-life assessment has been demonstrated in a number of these areas (e.g., in identifying problems and evaluating treatments). Its role in other applications (e.g., in clinical practice to assess patients' needs) shows great promise and requires additional evaluation.
Gotay, Carolyn Cook; Wilson, Malia
doi: 10.1177/016327879802100203pmid: 10183343
During the past decade, the importance of integrating quality of life with other indicators of efficacy in cancer clinical trials has been emphasized. This article reviews quality-oflife assessment in clinical trial reports. All empirical studies using patient ratings published in the Journal of Clinical Oncologyfrom 1992 to 1996 were identified. Of these, 59 articles (4%) included quality-of-life assessment, mostfrequently measured by selfreport questionnaires. Most articles reported clinical trials of symptom management or treatment. Future research needs to specify relationships between quality of life, toxicity, and survival. Continued development of this field requires more frequent inclusion of quality of life in clinical studies.
Nanda, Upasana; Andresen, Elena M.
doi: 10.1177/016327879802100204pmid: 10183344
The importance of evaluating health care in terms of patients' quality of life has only recently been acknowledged in the context of outcomes research and the measurement of quality of care. Asa health professional, trying to choose the appropriate health status or health-related quality of life (HRQOL) measure can be daunting, as one is faced with a bewildering array of choices. The purpose of this article is to describe the process by which professionals might make a choice about measures in outcomes research. The article includes examples and rationale for using generic or disease-specific HRQOL measures. In addition, examples are provided of HRQOL assessment in two adult chronic disease applications: asthma and congestive heartfailure.
Wolinsky, Fredric D.; Wyrwich, Kathleen W.; Nienaber, Nancy A.; Tierney, William M.
doi: 10.1177/016327879802100205pmid: 10183345
The objectives of this study were to evaluate and compare the psychometric properties of a generic health status measure, the Medical Outcomes Study SF-36, and a disease-specific health status measure, a modified version of the Chronic Heart Failure Questionnaire (CHQ), among outpatients known to have coronary artery disease (CAD) and/or congestive heart failure (CHF). A cross-sectional analysis of baseline data obtained from 670 outpatients participating in a randomized controlled clinical trial in the general medicine clinics of a major academic medical center was performed. The SF-36 was more comprehensive in its coverage of different health status domains. In contrast, the CHQ had fewer problems with floor and ceiling effects, was more internally consistent, had better dimensional reproducibility, and exhibited less factorial complexity. Although both instruments are appropriate for use among outpatients known to have CAD and/or CHF the CHQ has significantly better psychometric properties than does the SF-36.
Andresen, Elena M.; Rothenberg, Barbara M.; Panzer, Robert; Katz, Paul; Mcdermott, Michael P.
doi: 10.1177/016327879802100206pmid: 10183346
Selecting an outcomes assessment instrument requires knowledge of their relative merits, especially head-to-head comparisons. The authors compare health-related quality-of-life (HRQOL) instruments among older adults for theirpsychometric properties and subject burden, specifically the Sickness Impact Profile (SIP) and Medical Outcomes Study Short- Form 36 (SF-36). Subjects were 282 of 373 eligible older adults (75.6% response) ranging in age from 65 to 96. SIP scores demonstrated a strong skew toward low (good health) scores with a mean of 11.1% (SD 11.5) on the Total SIP index score. Similar components of the SIP and SF-36 were moderately to strongly correlated. The SIP suffered from a ceiling (good health) scaling effect, and the SF-36 scales also demonstrated some scaling extremes. These results demonstrate the relative scaling limits, especially the ceiling effect, of the SIP compared to the SF- 36, and in general, the SF-36 is preferredfor use among community-living older adults.
Chan, Kitty S.; Revicki, Dennis A.
doi: 10.1177/016327879802100207pmid: 10183347
Objective: To evaluate the relationship between laboratory markers of HIV, AIDS- defining events, study discontinuation, and summaryscoresftom theMOS-HWVHealthSurvey. Methods: Secondary analysis of data from a clinical trial of antiretroviral therapies in advanced HIV-infected patients (N = 940). Clinical and health-related quality-of-life data were collected over 48 weeks. Linear regression, logistic regression and survival analyses were performed to evaluate the relationships between MOS-HlVsummary scores, clinical events, and laboratory markers. Results: Each point increase in PHS resulted in a 3.0% decrease in the likelihood of developing an AIDS-defining event (p<.05) and a 2.7% decrease in likelihood of study discontinuation (p<.05). MHS did not significantly predict clinical events, but did predict study discontinuation (p<.05). From the linear regression analyses, the change in CD4 counts was a significant predictor of the change in MHS (p<.01).Conclusion: The MOS-HIV summary scores predict clinical events and study discontinuation in advanced HIV-infected patients.
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