Measuring the Quality of Physician Practice by Using Clinical Vignettes: A Prospective Validation Study
- John W. Peabody, MD, PhD;
- Jeff Luck, MBA, PhD;
- Peter Glassman, MBBS, MSc;
- Sharad Jain, MD;
- Joyce Hansen, MD;
- Maureen Spell, MD; and
- Martin Lee, PhD
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From San Francisco Veterans Affairs Medical Center, Institute for Global Health, University of California, San Francisco,
and California Pacific Medical Center, San Francisco, California; University of California, Los Angeles, Veterans Affairs
Greater Los Angeles Healthcare System, and Permanente Medical Group, Los Angeles, California; RAND, Santa Monica, California;
and Veterans Affairs Center for the Study of Healthcare Provider Behavior, Sepulveda, California.
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Figure 1. 1 = simple case; 2 = complex case; COPD = chronic obstructive pulmonary disease; DM = diabetes mellitus; MCO = managed
care organization; MD = medical doctor (physician); SP = standardized patient; VAMC = Veterans Affairs medical center. Planned study design showing sites and physician sample by level of training and clinical case for the 3 quality measurement
methods.
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Figure 2. Scores are expressed as percentage correct; error bars represent upper bound of 95% CIs. Per analysis of variance
model, < 0.001 (overall); > 0.2 for method by disease interaction. COPD = chronic obstructive pulmonary disease. Direct comparison of scores, overall and by disease, using 3 measurement methods: standardized patients, vignettes, and chart
abstraction.PP
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Figure 3. Scores are expressed as percentage correct; error bars represent upper bound of 95% CIs. Per analysis of variance
models, < 0.001 (overall); > 0.2 for method by case complexity interaction; > 0.2 for method by physician training level
interaction. Comparison of vignette scores to standardized patient and chart scores, stratified by case complexity and training level.PPP
-
Figure 4. Boxes represent interquartile range, and stems describe 5th to 95th percentile range. Comparison of variations among and within the 4 sites by measurement method.
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Figure 5. Distribution of unnecessary items ordered by participants while caring for cases depicted by vignettes compared with all tests
and referrals entered directly into the medical record after standardized patient visits.
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Ann Intern Med
November 16, 2004
vol. 141
no. 10
771-780
RSS Feeds
Figure 1. 1 = simple case; 2 = complex case; COPD = chronic obstructive pulmonary disease; DM = diabetes mellitus; MCO = managed care organization; MD = medical doctor (physician); SP = standardized patient; VAMC = Veterans Affairs medical center. Planned study design showing sites and physician sample by level of training and clinical case for the 3 quality measurement methods.
Figure 2. Scores are expressed as percentage correct; error bars represent upper bound of 95% CIs. Per analysis of variance model, < 0.001 (overall); > 0.2 for method by disease interaction. COPD = chronic obstructive pulmonary disease. Direct comparison of scores, overall and by disease, using 3 measurement methods: standardized patients, vignettes, and chart abstraction.PP
Figure 3. Scores are expressed as percentage correct; error bars represent upper bound of 95% CIs. Per analysis of variance models, < 0.001 (overall); > 0.2 for method by case complexity interaction; > 0.2 for method by physician training level interaction. Comparison of vignette scores to standardized patient and chart scores, stratified by case complexity and training level.PPP
Figure 4. Boxes represent interquartile range, and stems describe 5th to 95th percentile range. Comparison of variations among and within the 4 sites by measurement method.
Figure 5. Distribution of unnecessary items ordered by participants while caring for cases depicted by vignettes compared with all tests and referrals entered directly into the medical record after standardized patient visits.
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