Objective: Identify structure and process variables that significantly contributed to dentist productivity across VA Dental Service clinics using multiple VA national datasets from fiscal year 2010.
Methods: A retrospective, longitudinal analysis with the primary outcome of care provided, as measured by relative value units per clinically mapped full-time employee equivalent dentist, per year. Predictor variables included physical plant variables, staffing variables, complexity of the patient population, workplace climate, and environment of care. Predictor variables were initially assessed in a bivariate analysis with the primary outcome and those significant at P < 0.2 were entered into an ordinary least squares regression model.
Results: Dentist productivity and several predictor variables were significantly different between sites with and without resident training programs; therefore, two explanatory models were constructed. In both models, increasing the assistant-to-dentist ratio was the most important driver for increasing productivity. Additional drivers include the resident-to-dentist ratio, use of technology, and connectedness and engagement with the medical center as demonstrated by participation in various committees and/or boards. Final models explained over 50 percent of the variance in productivity.
Conclusions: In multiprovider settings, predictors of dentist clinical productivity differ for sites with and without residency training programs. Although the assistant-to-dentist ratio is the most explanatory for each type of setting, other variables such as the resident-to-dentist ratio, use of technology, and connectedness/engagement with the medical center are uniquely significant to the two types of service sites and should also be considered to maximize productivity.
Keywords: dental care delivery; dental staff; productivity; relative value scale.
Published 2013. This article is a U.S. Government work and is in the public domain in the USA.