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Objective: Evaluate the reliability and validity of the Kidney Disease Quality of Life Short Form 36 (KDQOL-36) in Hispanics with mild-to-moderate chronic kidney disease (CKD)., Design: Cross-sectional, Setting: Chronic Renal Insufficiency Cohort Study, Participants: 420 Hispanic (150 English- and 270 Spanish-speakers), and 409 non-Hispanic White individuals, matched by age (mean 57 years), sex (60% male), kidney function (mean estimated glomerular filtration rate 36ml/min/1.73m2), and diabetes (70%)., Methods: To measure construct validity, we selected instruments, comorbidities, and laboratory tests related to at least one KDQOL-36 subscale. Reliability was determined by calculating Cronbach's alpha., Results: Reliability of each KDQOL-36 subscale [SF-12 Physical Component Summary (PCS) and Mental Component Summary (MCS), Symptoms/Problems, Burden of Kidney Disease and Effects of Kidney Disease] was very good (Cronbach's alpha >0.8). Construct validity was supported by expected negative correlation between MCS scores and the Beck Depression Inventory in all three subgroups (r=-0.56 to -0.61, P<.0001). There was inverse correlation between the Symptoms/ Problems subscale and the Patient Symptom Form (r= -0.70 to -0.77, P<.0001). We also found significant, positive correlation between the PCS score and a physical activity survey (r=+0.29 to +0.38, P< or =.003); and between the PCS and MCS scores and the Kansas City Questionnaire (r= +0.31 to +0.64, P<.0001). Reliability and validity were similar across all racial/ethnic groups analyzed separately., Conclusion: Our findings support the use of the KDQOL-36 as a measure of HRQOL in this cohort of US Hispanics with CKD.

OBJECTIVE: Health planners and policy makers are increasingly asking for a feasible method to identify vulnerable persons with the greatest health needs. We conducted a systematic review of the association between a single item assessing general self-rated health (GSRH) and mortality. DATA SOURCES: Systematic MEDLINE and EMBASE database searches for studies published from January 1966 to September 2003. REVIEW METHODS: Two investigators independently searched English language prospective, community-based cohort studies that reported (1) all-cause mortality, (2) a question assessing GSRH; and (3) an adjusted relative risk or equivalent. The investigators searched the citations to determine inclusion eligibility and abstracted data by following a standarized protocol. Of the 163 relevant studies identified, 22 cohorts met the inclusion criteria. Using a random effects model, compared with persons reporting ‘excellent’ health status, the relative risk (95% confidence interval) for all-cause mortality was 1.23 [1.09, 1.391, 1.44 [1.21, 1.71], and 1.92 [1.64, 2.25] for those reporting ‘good,’ ‘fair,’ and ‘poor’ health status, respectively. This relationship was robust in sensitivity analyses, limited to studies that adjusted for co-morbid illness, functional status, cognitive status, and depression, and across subgroups defined by gender and country of origin. CONCLUSIONS: Persons with ‘poor’ self-rated health had a 2-fold higher mortality risk compared with persons with ‘excellent’ self-rated health. Subjects' responses to a simple, single-item GSRH question maintained a strong association with mortality even after adjustment for key covariates such as functional status, depression, and co-morbidity. [ABSTRACT FROM AUTHOR]

We compared single- and multi-item measures of general self-rated health (GSRH) to predict mortality and clinical events a large population of veteran patients. We analyzed prospective cohort data collected from 21,732 patients as part of the Veterans Affairs Ambulatory Care Quality Improvement Project (ACQUIP), a randomized controlled trial investigating quality-of-care interventions. We created an age-adjusted, logistic regression model for each predictor and outcome combination, and estimated the odds of events by response category of the GSRH question and compared the discriminative ability of the predictors by developing receiver operator characteristic curves and comparing the associated area under the curve (AUC)/ c-statistic for the single- and multi-item measures. All patients were sent a baseline assessment that included a multi-item measure of general health, the 36-item Medical Outcomes Study Short Form (SF-36), and an inventory of comorbid conditions. We compared the predictive and discriminative ability of the GSRH to the SF-36 physical component score (PCS), the mental component score (MCS), and the Seattle index of comorbidity (SIC). The GSRH is an item included in the SF-36, with the wording: “In general, would you say your health is: Excellent, Very Good, Good, Fair, Poor?” The GSRH, PCS, and SIC had comparable AUC for predicting mortality (AUC 0.74, 0.73, and 0.73, respectively); hospitalization (AUC 0.63, 0.64, and 0.60, respectively); and high outpatient use (AUC 0.61, 0.61, and 0.60, respectively). The MCS had statistically poorer discriminatory performance for mortality and hospitalization than any other other predictors ( p<.001). The GSRH response categories can be used to stratify patients with varying risks for adverse outcomes. Patients reporting “poor” health are at significantly greater odds of dying or requiring health care resources compared with their peers. The GSRH, collectable at the point of care, is comparable with longer instruments. [ABSTRACT FROM AUTHOR]

The article focuses on the principles for data collaboration and system organizational design organized by the U.S. federal agencies and private sector, to create evidence to support health and health care decisions. The closing of evidence gap which reduce the development of quality-of-care improvements, the collaboration on the focused development of infrastructure of the generation of evidence and a table depicting key principles and elements for evidence-generation system are mentioned.