Table 3.

Ordinary least squares (OLS) estimates for linear-in-parameter regressions capturing the impact of health information technology (HIT) and electronic health record (EHR) on emergency care clinical outcomes.

Dependent variable		lna (O/E ratio emergency care)b
		Model I (HIT)			Model II (EHR adoption)			Model III (EHR user value)
		β (SE)	P value	β (SE)		P value	β (SE)		P value
Intercept		.557 (0.506)	.27	.479 (0.65)		.46	−.563 (1.007)		.58
HIT adoptionc		−.001 (0.001)	.54	N/Ad		N/A	N/A		N/A
HIT user-valuee		−.032 (0.016)	.04	N/A		N/A	N/A		N/A
EHR adoptionf		N/A	N/A	.053 (0.034)		.11	N/A		N/A
EHR user-valuee		N/A	N/A	N/A		N/A	−.018 (0.022)		.42
#beds
	<150	.037 (0.087)	.67	−.082 (0.108)		.45	−.087 (0.147)		.55
	150-300	.027 (0.046)	.56	−.002 (0.061)		.97	.033 (0.077)		.66
	301-600	−.035 (0.049)	.47	−.002 (0.064)		.97	.065 (0.082)		.43
	>600	−.028 (0.086)	.74	.087 (0.114)		.45	−.01 (0.14)		.94
ln(#total cases)		.102 (0.051)	.04	.026 (0.068)		.70	.134 (0.086)		.12
ln(#emergency cases)		−.559 (0.167)	<.001	−.288 (0.214)		.18	−.203 (0.286)		.48
ln(#emergency cases)^2g		.058 (0.019)	.004	.027 (0.025)		.28	.018 (0.033)		.58
Teaching(yes)		−.036 (0.032)	.26	−.015 (0.214)		.72	−.022 (0.054)		.68
Private(yes)		.007 (0.037)	.83	.017 (0.046)		.72	.059 (0.060)		.33
Subsample size		261			174			82
R 2		0.098			0.047			0.117
F value		2.727	.003	0.905		.52	1.061		.40

^aln implies natural logarithm.

^bO/E (observed-over-expected) ratio implies better performance with lower values.

^cOn a 0-to-415 scale from worst to best.

^dN/A: not applicable.

^eOn a 1-to-10 scale from worst to best.

^fAdoption of EHR.

^gTests for an inverse U–shaped relationship between case volumes and outcomes for emergency care.