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Community Health Center Efficiency: The Role of Grant Revenues in Health Center Efficiency
Federally qualified health centers (FQHCs) were established to provide accessible, affordable, and high-quality health care for all Americans. We examine the relationship between external environments, organizational characteristics, and technical efficiency in FQHCs. Specifically, we test the relationship between grant revenues and technical efficiency in FQHCs.
Data Sources/Study Design
Secondary data were collected in each year from the Uniform Data System (UDS) on 644 eligible U.S.-based FQHCs between 2005 and 2007. The analysis of technical efficiency is performed in multiple steps. In the first step, technical efficiency is measured using data envelopment analysis models of multiple inputs and outputs. The efficiency scores were then used as the dependent variables in second-stage analyses to understand the determinants of technical efficiency.
The first part of the second stage models the conditional probability (as a function of covariates) that an FQHC is on the efficiency frontier. In our sample, approximately 20 percent of FQHCs were on the frontier. We estimated an instrumental variable probit model to identify the factors that primarily determine whether a health center is on the frontier or not. Instrumental variables were used to account for the potential endogeneity of grant funding. In the second part we investigated the drivers of efficiency for those FQHCs that are not on the efficiency frontier. This was done using a fractional response model, which was estimated using a two-step instrumental variables estimator. This estimator uses the residuals from a linear regression of the endogenous variable on the instruments (and other exogenous variables) as a covariate in a generalized linear model (GLM) for the fractional response (efficiency score). We used 500 bootstrap iterations to calculate standard errors.
Principal Findings
Holding all other factors constant, the percentage of grant revenue of total revenues did not impact the probability of a health center being on the frontier in any of the efficiency models. However, increased grant revenues had a negative association with technical efficiency for health centers that were not fully efficient.
Conclusion
If all health centers were operating efficiently, anywhere from 39 to 45 million patient encounters could have been delivered instead of the actual total of 29 million in 2007. For those health centers that were not fully efficient, an increase in the percentage of grant revenues predicted declines in efficiency. This may be due to the fact that increased grant revenues distort competitive pressure on the health centers and thus allow for increased levels of inefficiency. Policy makers should consider tying grant revenues to performance indicators, and future work is needed to understand the mechanisms through which diseconomies of scale are present in FQHCs.