Factors associated with high-severity disciplinary action by a state medical board: a Texas study of medical license revocation

Journal Name: 
J.Am.Osteopath.Assoc.
Authors: 
Cardarelli,R.
Licciardone,J.C.
Abstract: 
CONTEXT: There has been an increase in research evaluating factors associated with disciplinary action of physicians by state medical boards. However, factors related to the severity of disciplinary action are lacking. By investigating these factors while controlling for the type of violation, the authors sought to determine whether physician characteristics influenced the process of disciplinary action by state medical boards. METHODS: Physicians disciplined by the Texas Medical Board between January 1, 1989, and December 31, 1998, were included in this case-controlled study (N=1129). Multivariate logistic regression analysis was used to compute odds ratios (ORs) and 95% confidence intervals (CIs) for factors associated with license revocation, the most severe disciplinary action, compared with all other forms of disciplinary action combined. RESULTS: Anesthesiologists (OR, 2.45; 95% CI, 1.05-5.74), general practitioners (OR, 1.80; 95% CI, 1.01-3.19), and psychiatrists (OR, 2.68; 95% CI, 1.41-5.13), as well as those with multiple disciplinary actions (OR, 1.91; 95% CI, 1.29-2.83) were most susceptible to license revocation. The more years a disciplined physician was in practice, the greater risk he or she had of license revocation (OR, 1.05; 95% CI, 1.04-1.07). CONCLUSIONS: Factors associated with a greater likelihood of license revocation for physicians are: primary medical specialty, number of years in practice, and a history of multiple disciplinary actions
3
2006
Volume: 
106
Pages: 
153-156
Keywords: 
Adult, analysis, Comparative Study, Confidence Intervals, education, Employee Discipline, factors, Family, Female, Government Regulation, Health, history, Humans, Licensure,Medical, Male, medical, Medicine, Methods, Middle Aged, Odds Ratio, Osteopathic Medicine, Physicians, Professional Misconduct, regression, Regression Analysis, Research, Retrospective Studies, Risk, Risk Factors, statistics & numerical data, Texas, Universities