Comparing physician-specific two-year patient outcomes after coronary angiography: methodologic issues and results

We sought to evaluate methodologies to compare physician-related long-term patient outcomes appropriately.

Evaluation of physicians on the basis of short-term patient outcome is becoming widely practiced. These analyses fail to consider the importance of long-term outcome, and methods appropriate to such an analysis are poorly defined.

All patients undergoing coronary angiography between 1992 and 1994 who received all of their cardiac care at our institution were followed for 27+/-13 months (mean+/-SD). Patients (n = 754) were cared for by one or more of 17 staff physicians. Risk-adjusted models were developed for four candidate clinical end points and cost. Physicians were then evaluated for each outcome measure.

Of the clinical end points, death could be modeled most accurately (c-statistic = 0.83). The c-statistics for other end points ranged from 0.63 to 0.70. Physicians with outcomes statistically different (p < 0.05) from other physicians were identified more commonly than would be expected from the play of chance (p = 0.005). However, improvement in the c-statistics by the addition of physician identifiers was very modest. Physician's evaluations by the four measures of clinical outcome were variably correlated (r = .00 to .85). Graphic display of clinical and cost results for each physician did identify certain physicians who might be judged to provide more cost-effective care than others.

Although comparisons of groups of physicians on the basis of long-term patient outcomes may have merit, individual physician-to-physician comparisons will be more difficult, owing to 1) multiple physicians contributing care to individual patients; 2) the poor predictive capacity of models other than that for survival; and 3) the modest apparent impact of differences in physician providers on long-term patient outcome. With these caveats in mind, modeling to compare patient outcomes of individual physicians with homogeneous patient populations or to identify gross outliers (good or bad) may be practicable in some patient-care systems, but may be inappropriate in others.