Table 2.
Pneumonia | Surgical Infection Prevention | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Fixed Effects | Difficulty Index | Hospital-Specific Trends | GEE | MassHealth Effect | N | N Hospitals | MassHealth Effect | N | N Hospitals | |
Model 1 | X | 0.70* | 19,627 | 3,385 | −3.45*** | 13,804 | 3,213 | |||
(0.42) | (0.87) | |||||||||
Model 2 | X | X | −0.31 | 19,627 | 3,385 | −2.92*** | 13,804 | 3,213 | ||
(0.43) | (0.86) | |||||||||
Model 3 | X | X | 3.42*** | 19,569 | 3,356 | −1.89** | 13,678 | 3,150 | ||
(0.05) | (0.75) | |||||||||
Model 4 | X | X | X | −0.67 | 19,569 | 3,356 | −0.12 | 13,678 | 3,150 | |
(0.51) | (0.77) | |||||||||
Model 5 | X | X | 0.45 | 19,252 | 3,303 | 0.15 | 13,552 | 3,172 | ||
(0.54) | (1.04) |
Notes. Standard errors are displayed in parentheses. Models 1–4 show cluster robust (at the hospital level) standard errors while Model 5 shows standard errors that are robust to arbitrary heteroskedasticity.
GEE models include hospital controls (ownership, size, urbanicity, teaching status, Medicare share, Medicaid share) that are excluded from other specifications given that the controls are time invariant. Also, in GEE models, hospital-specific trends are not specified, although controls are interacted with the quadratic time trends.
For GEE models, average marginal effects are presented.
Trends are quadratic hospital-specific time trends.
GEE, generalized estimating equation; P4P, pay for performance.
p<.01
p<.05
p<.10.