The following equation (Equation (1)) shows the econometric model to identify the effect of Medicare PCIP program on the magnitude of primary care E&M services:
We let be the volume of eligible E&M services provided by provider i in period t; is an indicator for treatment group that takes the value 1 if the provider is a PCP, and zero otherwise; the variable Posttis an indicator variable taking the value of 1 in the years when the PCIP policy is likely to impact the behavior of the providers and 0 otherwise; the vector includes provider characteristics, such as age and gender etc. The term represents random unobserved factors affecting E&M services.
The DID methodology that we use here to identify the unbiased effect of PCIP policy on the volume of primary care E&M services is illustrated by considering two time periods: pre-PCIP (pre) and post-PCIP (post) periods with the latter being the years when the PCIP policy is likely to impact the behavior of the providers. Equation (2) below shows the change in the volume of E&M services provided by PCPs between pre-PCIP and post-PCIP periods, holding other things constant.
Similarly, equation (3) below shows the change in the volume of E&M services provided by non-PCPs between pre-PCIP and post-PCIP periods.
Holding other provider characteristics (embedded in Xs) constant and assuming the changes in random shocks are zero in the limit for both the groups, equation (4) below shows that the change in the magnitude of the primary care E&M services provided by PCPs due to the introduction of the Medicare PCIP program is .
Thus the coefficient from equation (1) represents an unbiased estimate of the effect of the Medicare PCIP policy on the volume of primary care E&M services. Similar methodology can also be applied to estimate the effect of the PCIP policy on other outcomes of interest.