Table 2.

Regression estimates of the relationship between consent and placebo policies and hospital-reported regulatory barriers to exchange and level of HIE use^a,d,h,i

	Aim One Main Analysisb		Aim One: Subgroup Analysisb				Aim Two Main Analysisc
	All Hospitals		MU2-Attesting Hospitalse		Non-MU Attesting Hospitalsf		MU2-Attesting Hospitalse
	Regulatory Barriers		Regulatory Barriers		Regulatory Barriers		HIE Level (MU eSCR%)
State HIE Policy	AME [95%CI]	p-value	AME [95%CI]	p-value	AME [95%CI]	p-value	Beta [95%CI]	p-value
Patient Consent Policy	n=2,023g		n=1,336		n=687		n=1,127
Opt-Out (ref)	--	--	--	--	--	--	--	--
Opt-In	0.078* [0.006, 0.151]	0.034	0.08 [−0.024, 0.183]	0.131	0.077 [0.013, 0.142]	0.019	0.56 [−3.1, 4.23]	0.763
Other	0.024 [−0.054, 0.103]	0.539	0.025 [−0.093, 0.143]	0.677	0.047 [0.004, 0.091]	0.034	−3.93 [−7.77, −0.1]	0.045

^aEstimates of key independent variables from four regression models.

^bMultiple logistic regression was used to estimate the marginal effects for state policy variables with hospitals’ reported regulatory barriers to HIE.

^cMultiple linear regression was used to estimate the relationship between state policy variables and hospital reported HIE level, as measured by percentage of transfers sent with electronic summaries of care (eSCR) in 2016. This outcome variable is measured from 10–100 reflecting the hospital reported percentage.

^dAll regression models controlled for hospital EHR adoption level, EHR vendor, use of dominant EHR vendor in HRR, year in MU2 program (aim two only), RHIO participation, ownership type, size, system membership, specialty status, teaching status, critical access status, bundled payment participation, accountable care organization participation, Medicare percentage of inpatient days, Medicaid percentage of inpatient days, hospital referral region concentration classification (HHI), core-based statistical area (Metro, Micro, or Rural), and US Census region. All models used clustered standard errors at the state level.

^eMU-attesting hospitals are those that reported a performance measure to CMS for percentage of transfers sent with electronic summaries of care in 2016

^fNon-MU attesting hospitals were those that did not report this measure to CMS in 2016 but were in our sample of AHA IT Survey respondents.

^gSample sizes are reported for each regression model. For example, for our primary analysis of the relationship between opt-in consent policies and regulatory barriers to HIE, the sample size was 2,023 hospitals.

^hFull regression results can be found in eAppendix Tables 2, 4, 5, & 6.

ⁱSignificance Levels:

^*p<0.05

^**p<0.01

^***p<0.001