Table 2 Regression results for medical DRGs (unit of analysis: admission)
From: The impact of health information technology on disparity of process of care
Variables | Coefficient | |
|---|---|---|
(std. err) | ||
Age (years) | Ref (1-17) | |
18 to 34 | −0.007 | |
(0.006) | ||
35 to 64 | 0.050*** | |
(0.006) | ||
65 and older | 0.094*** | |
(0.006) | ||
Sex | Ref (Female) | |
Male | −0.019*** | |
(0.001) | ||
Payment Source | Ref (Medicare) | |
Medical1 | 0.027*** | |
(0.002) | ||
Private | −0.116*** | |
(0.002) | ||
Self | −0.107*** | |
(0.004) | ||
Other | −0.046*** | |
(0.003) | ||
DRG weight | 0.173*** | |
(0.001) | ||
Health IT | −0.009*** | |
(0.002) | ||
Race | Non-White | 0.037* |
(0.021) | ||
Non-White × Health IT | −0.002* | |
(0.001) | ||
Ownership | Ref (Profit) | |
Not-for-profit | −0.041*** | |
(0.009) | ||
Government | −0.050*** | |
(0.013) | ||
Teaching status | −0.025 | |
(0.018) | ||
Network hospital | −0.004 | |
(0.010) | ||
Licensed beds | 0.0001*** | |
(0.000) | ||
Rural hospital | −0.088*** | |
(0.014) | ||
Constant | 0.625*** | |
(0.031) | ||