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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.
Taken together, these findings illustrate that although opt-in consent regimes are related to barriers to HIE for hospitals, relatively technologically sophisticated hospitals use HIE at the same rate regardless of their state’s consent policy. That is to say that although opt-in consent policies may contribute to a variety of administrative or technical barriers, organizations are able to overcome these barriers if and when interoperable data exchange becomes an important institutional goal. Our findings fit with other work finding that both incentives and hospital technical capabilities relate to HIE volume.7,25

Although we find that opt-in consent policies are related to higher reported rates of regulatory barriers to HIE among hospitals, opt-out policies may not be strictly superior. Opt-out policies raise concerns among patients of violating rights to informed choice.34 Although opt-out consent policies are generally less burdensome for clinicians and administrators and are fully within the law under the Health Insurance Portability and Accountability Act, some evidence shows that patients may prefer opt-in systems for HIE consent.35 Opt-in consent policies are often motivated by these twin forces that prioritize privacy and patient preference, despite the administrative burdens they may bring.34 Policy makers should carefully consider these trade-offs going forward in deciding how laws pertaining to HIE should be crafted.

Future studies should consider directly examining variation in consent laws across jurisdictions or hospitals in different jurisdictions that share substantial numbers of patients, as the regulatory differences specific to patient consent in these settings are likely to be highly salient to hospitals. Furthermore, studies should examine the extent to which the volume of HIE is associated with the ultimate goals of interoperable HIE­—namely, improving efficiency, quality of care, and eventually health outcomes.


Our study has several limitations. First, the analysis is cross-sectional in nature and representative only of hospitals and state policies in 2016. Furthermore, we can draw no causal conclusions given the cross-sectional data and lack of exogenous variation. Given that both the database of state HIE laws and MU2 performance reporting are as of 2016, we were limited in our ability to analyze the effects of laws over time. States passed HIE laws over a number of years, further limiting longitudinal analysis. For example, the effective dates of consent laws range from June 2008 to March 2016, with two-thirds going into effect after 2011. Second, some states in the legal database contained missing values for certain laws—in particular, consent policies. Despite the listwise deletion of hospital observations in states with missing values for HIE policies, our sample sizes remained relatively robust from the states that were included in the analysis. However, this limits the generalizability of our findings outside of states included in the analysis and prevents us from drawing conclusions at the national level. Third, in the analysis for our second research aim, it is possible that our estimates are affected by selection bias. We observe only hospitals that successfully attested to MU2, a sample that may exclude hospitals with systematically lower levels of health IT sophistication from those analyses. This may be especially pronounced in analyses of HIE volume due to the volume threshold required for MU2 attestation. However, previous work has found limited evidence of selection bias in this sample of hospitals.7 In this work, authors Lin et al used a Heckman selection model to identify if hospitals that did not attest to MU2 had lower predicted HIE volume compared with those that did. They found that the Heckman model estimates were essentially the same as multiple linear regression, indicating that using only MU2-attesting hospitals was unlikely to bias the findings. Furthermore, our measure of HIE usage—percentage of patient transfers sent with eSCRs—has limitations in that it may not be perfectly sensitive to state consent policies, given that eSCR transitions have low administrative costs once exchange capabilities are in place. Nevertheless, we do find variation in this variable across hospitals, suggesting that rates of eSCR are not uniformly distributed.


Any policies that states implement for HIE will have trade-offs. In the case of opt-in consent policies, states may choose to prioritize patient privacy, right to consent, and patient preferences at the cost of added administrative burden and regulatory hurdles for hospitals and providers. Policy makers should consider the existing legal structures related to HIE in their regions and the technical capabilities of hospitals in their states to anticipate the burden that opt-in consent policies are likely to bring. Furthermore, federal policy makers tasked with reducing administrative burdens related to the use of EHRs—a specific provision of the 21st Century Cures Act—should consider that hospitals at varying levels of technological sophistication may experience different administrative burdens.


We compared opt-in state HIE consent policies with opt-out policies in 2016 and found that hospitals in states with opt-in consent policies were 7.8 percentage points more likely to report experiencing regulatory barriers to HIE. However, hospitals attesting to MU2 in these states did not systematically engage in less HIE, suggesting that these barriers are not borne by more technologically advanced hospitals. Our results fit with previous literature emphasizing the added administrative burden of opt-in consent policies compared with opt-out policies, especially for less technologically advanced hospitals. Policy makers should consider the complexity of regional differences in consent policies and the incidence of regulatory burdens when crafting HIE consent policies or guidance to hospitals for policy compliance.

Author Affiliations: Richard M. Fairbanks School of Public Health, Indiana University (NCA), Indianapolis, IN; Regenstrief Institute (NCA), Indianapolis, IN; Harvard Business School (AJH), Cambridge, MA.

Source of Funding: Research reported herein was supported in part by the National Library of Medicine of the National Institutes of Health under award number T15LM012502.

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (NCA, AJH); acquisition of data (NCA, AJH); analysis and interpretation of data (NCA, AJH); drafting of the manuscript (NCA, AJH); critical revision of the manuscript for important intellectual content (NCA, AJH); and statistical analysis (NCA, AJH).

Address Correspondence to: Nate C. Apathy, BS, Richard M. Fairbanks School of Public Health, Indiana University, 1050 Wishard Blvd, Indianapolis, IN 46202. Email:

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