Physician Styles of Patient Management as a Potential Source of Disparities: Cluster Analysis from a Factorial Experiment
Article first published online: 22 OCT 2012
© Health Research and Educational Trust
Health Services Research
Volume 48, Issue 3, pages 1116–1134, June 2013
How to Cite
Lutfey, K. E., Gerstenberger, E. and McKinlay, J. B. (2013), Physician Styles of Patient Management as a Potential Source of Disparities: Cluster Analysis from a Factorial Experiment. Health Services Research, 48: 1116–1134. doi: 10.1111/1475-6773.12005
- Issue published online: 9 MAY 2013
- Article first published online: 22 OCT 2012
- NHLBI. Grant Number: HL079174
- Medical decision making;
- medical practice variation;
- cluster analysis;
- coronary heart disease
To identify styles of physician decision making (as opposed to singular clinical actions) and to analyze their association with variations in the management of a vignette presentation of coronary heart disease (CHD).
Primary data were collected from primary care physicians in North and South Carolina.
In a balanced factorial experimental design, primary care physicians viewed one of 16 (24) video vignette presentations of CHD and provided detailed information about how they would manage the case.
Data Collection Method
256 MD primary care physicians were interviewed face-to-face in North and South Carolina.
We identify three clusters depicting unique styles of CHD management that are robust to controls for physician (gender and level of experience) and patient characteristics (age, gender, socioeconomic status, and race) as well as key organizational features of physicians' work settings. Physicians in Cluster 1 “Cardiac” (N = 92) were more likely to focus on cardiac issues compared with their counterparts; physicians in Cluster 2 “Talkers” (N = 93) were more likely to give advice and take additional medical history; whereas physicians in Cluster 3 “Minimalists” (N = 71) were less likely than their counterparts to take action on any of the types of management behavior.
Variations in styles of decision making, which encompass multiple outcome variables and extend beyond individual-level demographic predictors, may add to our understanding of disparities in health quality and outcomes.