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Physician-estimated Disease Severity in Patients with Chronic Heart or Lung Disease: a Cross-sectional Analysis

Overview
Publisher Biomed Central
Specialty Public Health
Date 2006 Sep 15
PMID 16970808
Citations 7
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Abstract

Background: We evaluated how well physicians' global estimates of disease severity correspond to more specific physician-rated disease variables as well as patients' self-rated health and other patient variables.

Methods: We analyzed baseline data from 1662 primary care patients with chronic cardiac or pulmonary disease who were enrolled in a longitudinal study of health-related quality of life (HRQoL). Each patient's primary physician rated overall disease severity, estimated the two-year risk of hospitalization and mortality, and reported the use of disease-specific medications, tests, and subspecialty referrals. Patient variables included sociodemographic characteristics, psychosocial factors, self-rated health, and both generic and disease-specific HRQoL.

Results: Physicians rated 40% of their patients "about average", 30% "worse", and 30% "better" than the typical patient seen with the specific target disorder. The physician's global estimate of disease severity was strongly associated (P < 0.001) with each of the five more specific elements of physician-rated disease severity, but only marginally associated with patient self-rated health. Multivariable regression identified a set of patient variables that explained 16.4% of the variance in physician-rated disease severity.

Conclusion: Physicians' global ratings may provide disease severity and prognostic information unique from and complementary to patient self-rated health and HRQoL measures. The elements influencing physician-rated disease severity and its predictive validity for clinical outcomes warrant prospective investigation.

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References
1.
Vigano A, DORGAN M, Buckingham J, Bruera E, Suarez-Almazor M . Survival prediction in terminal cancer patients: a systematic review of the medical literature. Palliat Med. 2000; 14(5):363-74. DOI: 10.1191/026921600701536192. View

2.
Wolinsky F, Wyrwich K, Nienaber N, Tierney W . Generic versus disease-specific health status measures. An example using coronary artery disease and congestive heart failure patients. Eval Health Prof. 1998; 21(2):216-43. DOI: 10.1177/016327879802100205. View

3.
Idler E, Benyamini Y . Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997; 38(1):21-37. View

4.
Tierney W, Martin D, Hui S, McDonald C . Using clinical data to predict abnormal serum electrolytes and blood cell profiles. J Gen Intern Med. 1989; 4(5):375-83. DOI: 10.1007/BF02599685. View

5.
Kong D, Lee K, Harrell Jr F, Boswick J, Mark D, Hlatky M . Clinical experience and predicting survival in coronary disease. Arch Intern Med. 1989; 149(5):1177-81. View