Factors contributing to clinical output among general practitioners and family physicians

Abstract

Objectives. The objective of this project was to ascertain and quantify the effects of gender, age, payment method, and practice size on clinical output of GP/FPs. While the identification of these effects has been undertaken previously, this study is the first attempt to quantify the proportion of variance in physician output explained by this group of variables.Background. The question is of vital importance to academics, health professionals, and citizens. The physician population is aging and feminizing while physicians are softening their opposition to fixed remuneration methods and displaying a greater predilection to group practice. Implications exist for the supply of physician services as gender, age, payment method, and practice size have been found to influence physician output, and therefore the availability of primary care services. Methods. The study employed self-reported data obtained from 1006 Canadian general and family practitioners in 2004. Respondents provided their gender, age, payment method, and practice size, as well as the number of patient visits they conducted (both during regular hours and while on call) and the number of hours they worked in an average week. These data were used to measure the effects of the four independent variables on GP/FP output and to quantify their total collective affect. Results. By and large, the analysis confirmed the prevailing view of the literature, as female physicians; physicians in the youngest and oldest age categories; physicians remunerated mainly through fixed payment methods; and physicians in group practice reported lower levels of output than their counterparts. Despite the presence of obvious trends in the data, in some cases the analysis was unable to uncover statistically significant differences in output between groups of physicians.In terms of the contribution made by these four variables to the variance in GP/FP output, significant and parsimonious models contributed 16.2% of the variance in total patient visits, 19.3% of the variance in patient visits during regular hours, 2.5% of the variance in patient visits while on call, 11.1% of variance in hours worked per week, and 8.9% of the variance in patient visits per hour worked. Conclusion. The four factor variables explained less than one fifth of the variance in all output categories. This first attempt to quantify their contribution identifies an important question: what accounts for the remaining variance? If the unidentified factors are measurable, perhaps they can be added to these models in the future in order to increase our understanding of the forces behind GP/FP output of primary care services.