The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Predicting Mortality and Healthcare Utilization with a Single Question
Open accessAbstract
Objective. 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. Data Source/Study Setting. 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. Study Design. 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. Data Collection/Extraction Methods. 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?” Principal Findings. 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). Conclusions. 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.
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Prediction of coronary heart disease using risk factor categories
Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998) · Circulation · doi:10.1161/01.cir.97.18.1837 · Cited by 9,581
Self-rated health and mortality: a review of twenty-seven community studies.
Idler, E. L., & Benyamini, Y. (1997) · Journal of Health and Social Behavior · doi:10.2307/2955359 · Cited by 8,598
Romano, P. S., Roos, L. L., & Jollis, J. G. (1993) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(93)90103-8 · Cited by 1,717
Miilunpalo, S., Vuori, I., Oja, P., Pasanen, M., & Urponen, H. (1997) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(97)00045-0 · Cited by 1,473
Fan, V. S., Curtis, J. R., Tu, S.-P., McDonell, M. B., & Fihn, S. D. (2002) · Chest · doi:10.1378/chest.122.2.429 · Cited by 240 · cited 3×
“We compared the GSRH to multi-item scales that are calculated from the SF-36 and have been shown to predict mortality and utilization (Hornbrook and Goodman 1996; Fan et al. 2002).”
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Cited by
Huntley, A. L., Johnson, R., Purdy, S., Valderas, J. M., & Salisbury, C. (2012) · The Annals of Family Medicine · doi:10.1370/afm.1363 · Cited by 619
Mahajan, S., Caraballo, C., Lu, Y., Valero-Elizondo, J., Massey, D., Annapureddy, A. R., Roy, B., Riley, C., Murugiah, K., Onuma, O., et al. (2021) · JAMA · doi:10.1001/jama.2021.9907 · Cited by 368
Pickens, C. M., Pierannunzi, C., Garvin, W., & Town, M. (2018) · MMWR. Surveillance Summaries · doi:10.15585/mmwr.ss6709a1 · Cited by 332
Income-Related Inequalities in Health Service Utilisation in 19 OECD Countries, 2008-2009
(2012) · OECD Health Working Papers · doi:10.1787/5k95xd6stnxt-en · Cited by 304
Part II: a qualitative study of social risk screening acceptability in patients and caregivers
Byhoff, E., De Marchis, E. H., Hessler, D., Fichtenberg, C., Adler, N., Cohen, A. J., Doran, K. M., Ettinger de Cuba, S., Fleegler, E. W., Gavin, N., et al. (2019) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2019.07.016 · Cited by 255
Metadata
- Authors
- DeSalvo, K. B., Fan, V. S., McDonell, M. B., & Fihn, S. D.
- Venue
- Health Services Research
- Publisher
- Wiley
- Published
- 2005-04-26
- Volume
- 40
- Issue
- 4
- Pages
- 1234-1246
- ISSN
- 0017-9124 (ISSN-L)
- 1475-6773
- OpenAlex
- W2099590875
- Cited by
- 675
- References
- 5
- FWCI
- 44.43
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.