Do physicians employ aides efficiently?: Some new evidence on solo practitioners

Measuring individual physician clinical productivity in an era of consolidated group practices

BACKGROUND

As physician groups consolidate and value-based payment replaces traditional fee-for-service systems, physician practices have greater need to accurately measure individual physician clinical productivity within team-based systems. We compared methodologies to measure individual physician outpatient clinical productivity after adjustment for shared practice resources.

METHODS

For cardiologists at our hospital between January 2015 and June 2016, we assessed productivity by examining completed patient visits per clinical session per week. Using mixed-effects models, we sequentially accounted for shared practice resources and underlying baseline characteristics. We compared mixed-effects and Generalized Estimating Equations (GEE) models using K-fold cross validation, and compared mixed-effect, GEE, and Data Envelopment Analysis (DEA) models based on ranking of physicians by productivity.

RESULTS

A mixed-effects model adjusting for shared practice resources reduced variation in productivity among providers by 63% compared to an unadjusted model. Mixed-effects productivity rankings correlated strongly with GEE rankings (Spearman 0.99), but outperformed GEE on K-fold cross validation (root mean squared error 2.66 vs 3.02; mean absolute error 1.89 vs 2.20, respectively). Mixed-effects model rankings had moderate correlation with DEA model rankings (Spearman 0.692), though this improved upon exclusion of outliers (Spearman 0.755).

CONCLUSIONS

Mixed-effects modeling accounts for significant variation in productivity secondary to shared practice resources, outperforms GEE in predictive power, and is less vulnerable to outliers than DEA.

IMPLICATIONS

With mixed-effects regression analysis using otherwise easily accessible administrative data, practices can evaluate physician clinical productivity more fairly and make more informed management decisions on physician compensation and resource allocation.

What factors affect the productivity and efficiency of physician practices?

BACKGROUND

Increasing the productivity and efficiency of physician practices could help relieve the rapid growth of US healthcare costs and the expected physician shortage. Radiology practices are an attractive specific focus for research on practices' productivity and efficiency because they are home to many purportedly productivity-enhancing operational technologies. This affords an opportunity to study the effect of production technology on physicians' output. As well, radiology is a leader in the general movement of physicians out of very small practices. And imaging is by the fastest-growing category of physician expenditure.

RESEARCH DESIGN

Using data from 2003 to 2007 surveys of radiologists, we estimate a stochastic frontier model to study the effects of practice characteristics, such as work hours, practice size, and output mix, and technologies used in work production, on practices' productivity and efficiency.

RESULTS

At the mean, the elasticities of output with respect to practice size and annual hours worked per full-time physician were 0.73 and 0.51, respectively. Some production technologies increase productivity by 15% to 20%; others generate no increase. Using "nighthawks"--ie, contracting out after-hours work to external firms that consolidate workflow--significantly increases practice efficiency.

CONCLUSIONS

The general US trend toward larger practice size is unlikely to relieve cost or physician shortage pressures. The actual effect of purportedly productivity-enhancing operational technologies needs to be carefully evaluated before they are widely adopted. As the recently-developed innovations of nighthawks and hospitalists show, practices should give more attention to a possible choice to "buy," rather than "make," part of their output.

Scope and scale inefficiencies in physician practices

Using a national data set, this paper looks at the efficiency of physician practices, focusing on scopes of service by comparing single specialty groups and multispecialty groups. An analysis of efficiency using DEA indicates that there are scope inefficiencies from combining different types of providers into a single practice. Most of the inefficiency is due to technical rather than allocative reasons. In addition, we find that larger practices are able to capture efficiencies of scope, but incur inefficiencies of scale.