Table 3.

Regression results for medical DRGs with one year preceding and lagged IT investment (unit of analysis: admission)

Variables		Coefficient	Coefficient
		(std. err)	(std. err)
Age (years)	Ref (1-17)
	18 to 34	−0.011	−0.006
		(0.007)	(0.0060
	35 to 64	0.049***	0.051***
		(0.006)	(0.006)
	65 and older	0.092***	0.094***
		(0.007)	(0.006)
Sex	Ref (Female)
	Male	−0.021***	−0.018***
		(0.001)	(0.001)
Payment source	Ref (Medicare)
	Medical1	0.028***	0.028***
		(0.002)	(0.002)
	Private	−0.117***	−0.116***
		(0.002)	(0.002)
	Self	−0.107***	−0.10***7
		(0.004)	(0.004)
	Other	−0.045***	−0.046***
		(0.004)	(0.003)
DRG weight		0.183***	0.173***
		(0.001)	(0.001)
Health IT (t + 1)		−0.003
		(0.002)
Health IT (t-1)			−0.004***
			(0.002)
Race	Non-White	0.000	0.001
		(0.002)	(0.002)
Ownership	Ref (Profit)
	Not-for-profit	−0.062***	−0.045***
		(0.010)	(0.010)
	Government	−0.068***	−0.050***
		(0.014)	(0.013)
Teaching status		−0.024	−0.029
		(0.019)	(0.018)
Network hospital		−0.008	−0.004
		(0.011)	(0.010)
Licensed beds		0.0001***	0.0001***
		(0.000)	(0.000)
Rural hospital		−0.085***	−0.084***
		(0.015)	(0.014)
Constant		0.535***	0.547***
		(0.031)	(0.027)

***p < 0.01, **p < 0.05, *p < 0.1, ¹Medicaid is known as MediCal in California.

This regression examined the effect of IT investment on waiting time after controlling for other independent variables.