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Opt-In Consent Policies: Potential Barriers to Hospital Health Information Exchange
Nate C. Apathy, BS; and A. Jay Holmgren, MHI

Opt-In Consent Policies: Potential Barriers to Hospital Health Information Exchange

Nate C. Apathy, BS; and A. Jay Holmgren, MHI
Opt-in patient consent requirements for health information exchange correlate with more reported regulatory barriers, especially among less technologically advanced hospitals.
RESULTS

State Consent Laws

In the legal data collected by Schmit et al, 34 states had HIE consent policies defined as either opt-in, opt-out, or other.11 The remaining states and the District of Columbia are classified as missing in our data set. In 2016, 7 states had opt-in HIE consent policies, 15 had opt-out policies, and 12 were classified as having other approaches (Figure 1). In our primary regression model, there were 2023 hospitals with complete data from these 34 states. Of these hospitals, 478 were from opt-in states, 783 from opt-out states, and 762 from states classified as other.

Barriers to HIE

On average, 13% of hospitals reported regulatory barriers to HIE in 2016. In our bivariate analysis, 20% of hospitals in states with opt-in consent policies reported regulatory barriers to HIE compared with 13% of hospitals in states with opt-out, ambiguous, or voluntary policies (Figure 2), a statistically significant difference (P <.001). Hospitals also differed across consent policy types with respect to their RHIO participation, ownership, size, region, medical home status, critical access status, participation in ACOs and bundled payment programs, and location in urban or rural areas (Table 1). A complete table of descriptive statistics across all covariates can be found in eAppendix Table 1 (eAppendix available at ajmc.com).

In our logistic regression, hospitals in states with opt-in consent policies had a 7.8 percentage point higher probability of reporting regulatory barriers to HIE compared with hospitals in states with opt-out policies (average marginal effect [AME], 0.087; P = .034) (Table 2). In a second model using other consent policies as the reference, neither opt-in nor opt-out policies illustrated a relationship with reporting regulatory barriers. Full regression results for our first aim, with both opt-out and other policies as the reference policy, are available in eAppendix Tables 2 and 3.

In our subgroup analyses stratifying hospitals by MU2 attestation for HIE level, we found no evidence of a relationship between opt-in consent policies and reported regulatory barriers for hospitals that reported MU2 attestation (AME, 0.08; P = .13) (Table 2). However, the finding that opt-in consent laws were associated with perceived legal barriers to HIE held among the subsample of hospitals not attesting to MU2 (AME, 0.077; P = .019) (Table 2), which may suggest that the burden of opt-in policies falls primarily on less technologically advanced hospitals. The full results of our subgroup analyses can be found in eAppendix Tables 4 and 5.

Finally, in our robustness check that included hospital HIE capabilities as potential collider variables, our primary aim 1 finding held in direction, magnitude, and significance (eAppendix Table 6). HIE capabilities of finding, sending, receiving, and using electronic patient health information were excluded from our main regression models examining consent policies and hospital-reported regulatory barriers to avoid collider bias, but these findings do not suggest that these variables constitute colliders in this analysis.

Volume of HIE

Among hospitals reporting to MU2, on average, hospitals reported that 43% of patient transfers were sent with an eSCR (Table 1). In bivariate analyses of our second research aim, hospital HIE volume differed across state HIE consent policies, with hospitals in opt-in states reporting an average of 42% of transfers sent with eSCR compared with 45% and 41% of transfers in opt-out and other policy states, respectively (P = .016). However, in multivariate linear regression adjusting for hospital EHR adoption, demographics, and regional characteristics, we found no evidence of a relationship between opt-in state HIE consent policies and volume of HIE usage compared with opt-out policies (β = 0.560; P = .763) (Table 2). Full regression results for the second aim can be found in eAppendix Table 7. Additionally, given the lower levels of HIE volume in opt-in states and the attenuation of that relationship in the adjusted model, we suspected that opt-in consent policies may be related to EHR adoption, which then would affect HIE volume. To test this, we conducted a multinomial logistic regression with consent policy type as the independent variable and EHR adoption level as the dependent variable. This test showed no significant relationship between these variables (eAppendix Figure).

DISCUSSION

Our study is the first to directly compare opt-in and opt-out HIE consent policies across states. We found that, on average, hospitals in states with opt-in consent policies for HIE were more likely to report regulatory barriers to HIE compared with hospitals in states with opt-out consent policies, even when adjusting for a variety of hospital IT, organizational, and market characteristics. This finding suggests that opt-in policies may uniquely contribute to hospital barriers to HIE compared with opt-out policies. Given the administrative burden that opt-in consent policies introduce,19 our findings are consistent with a larger body of work supporting the claim that opt-in policies are more burdensome to implement. However, policies requiring explicit consent such as these may serve an important protective role in the use of patient health information.

Our subgroup analyses found that the relationship between opt-in consent policies and reported regulatory barriers held only for hospitals not attesting to MU2 in 2016. Hospitals subject to opt-in consent but having some degree of interoperable HIE capabilities were not more likely to report regulatory barriers. This finding supports the interpretation that regulatory barriers may be borne primarily by hospitals that lag in technological sophistication and HIE capabilities in particular or that opt-in consent policies discourage HIE on the extensive margin only. Opt-in consent policies may in turn further delay these hospitals in achieving interoperable HIE.

Despite hospitals’ increased likelihood of reporting regulatory barriers to HIE in the presence of opt-in policies, we found no evidence of a relationship between opt-in consent policies and volume of HIE usage. This finding suggests that consent policy type does not directly influence the amount of HIE in which a hospital engages, although this analysis is limited only to the subgroup of hospitals attesting to MU2 and, as noted previously, no more likely to report regulatory barriers to HIE. Additionally, given the cross-sectional nature of our data, we are unable to observe hospitals’ reported regulatory barriers to HIE in prior years. Regulatory barriers to HIE, including opt-in consent policies, may have been more salient in previous years as hospitals were establishing HIE capabilities, and by 2016, these barriers may have been largely overcome.


 
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