The ability for institutions to share data about problems in healthcare has the potential to unlock new ideas in medical care. Yet, such information is often sensitive and protected. This piece explores the ways Data Use Agreements can uphold security, while unlocking new value.
The growing demand for multi-institutional sharing of electronic healthcare record (EHR) data for research combined with the complex and time-consuming process of generating, negotiating, and executing data use agreements (DUAs), remains a significant frustration for researchers and research administrators. We highlight an administrative method of data sharing among healthcare researchers that leverages the “expert pathway” described in the Health Insurance Portability and Accountability Act (HIPAA) rule, which can allow sharing of protected health information (PHI) with a reduction in burdens related to DUAs and Institutional Review Boards (IRB) reviews. Specifically, we describe how data can be held by an infrastructure custodian or data enclave operating under a single DUA contract (versus multiple, project specific DUAs), allowing, with adequate controls, researchers to review private, aggregated results as computational outputs to database search queries. We discuss how this administrative method can reduce complexity in PHI data sharing, uphold reliable patient privacy, and leverage the HIPAA expert (versus safe harbor) pathway.
Key words: HIPAA Privacy Rule; data sharing; data use agreement; protected health information; de-identification, anonymization, differential privacy, statistical disclosure control; data enclave.
Despite the growing demand for multi-institutional sharing of electronic healthcare record (EHR) data for research purposes, the complex and time-consuming process of generating, negotiating, and executing DUAs remains a significant frustration for researchers and research administrators [1,2]. A survey of 17 research organizations by the Administrative Data Research Facilities Network reported that “We heard from almost every organization that setting up the necessary legal infrastructure is a time-consuming, nebulous, and unpredictable process” . A contributor to complexity is discomfort with data privacy protection levels under HIPAA’s safe harbor de-identification methods that has been characterized as “broken promises” because they do not adequately safeguard data subjects from reidentification [4,5,6,7,8]. Some have argued that even privacy protections offered by sophisticated anonymization methods cannot be effective without administrative controls that can narrow conditions of use and thus allow credible estimation of risk [9,10,11]. A panel of the National Academy of Medicine proposed that de-identification is not alone adequate to protect privacy .
Data enclaves are operational units that embody principles arising from legal, informatics, technology, and ethics sources pursued in design of privacy systems. The operational characteristics of data enclaves have been extensively reviewed and they are widely considered the most secure repository for sensitive information [13,14,15,16]. Many exemplary implementations have been described, particularly for government entities and social sciences research. But data enclaves require unique infrastructure and practices that may conflict with the current methods allowed under the HIPAA “safe harbor” rule. Of concern is that an HHS panel concluded that “Despite this increasingly important advantage, Expert Determination is used less frequently than Safe Harbor” and “The lessons from de-identification research are not informing day-to-day practice” . We believe that privacy goals would be advanced if data enclave methods were applied to nearly all multi-institutional data sharing, but such acceptance will require enclaves to become more appealing to researchers. We argue that a specific use of the HIPAA rule “expert pathway” with enclave methods can enable access to PHI without the need for researchers to seek DUA or IRB approvals.
The use of the HIPAA de-identification “expert pathway” can enable analysis of a data set that contains PHI while maintaining the access transaction compliantly de-identified. HIPAA offers two methods of compliant de-identification. The most commonly used is the “safe harbor” method which requires the removal of 18 standard identifiers such as name, address and precise dates. Alternatively, the “expert pathway” allows organizations to share a data set after “a person with appropriate knowledge of and experience with generally accepted statistical and scientific principles and methods for rendering information not individually identifiable” certifies that the risk of re-identification is “very small.” Although this usually involves the use of anonymization methods, the rule does not place restrictions on measures that can be employed to limit the ability of recipients to re-identify individual patients. Updated guidance from HHS in 2012 stated that the expert pathway may “consider the technique of limiting distribution of records through a DUA or restricted access agreement…the specific details of such an agreement are left to the discretion of the expert” . It was also noted that a DUA is not required for researchers to share de-identified data under these administrative controls.
A key step in designing a more efficient sharing process is to recognize the distinction between "access to data" and "possession of data." With appropriate technology enabled, researchers in many cases can address research questions by querying a data set without “physical possession” of the raw data. The data custodian role can be served by a trusted steward who manages the data storage site to ensure effective security and access control while enabling the system to return aggregate results. Researchers can gain remote access to enclave services via virtual machine functionality isolated from users’ computers and using analytic tools that run inside the enclave. Data cannot be downloaded by the researcher’s computer without a DUA that specifies fair use and custody expectations.
Critical to this schema is the ability of the custodian to provide a highly reliable level of privacy protection that can flexibly respond to emerging threats. Enclaves enable this by abandoning sole dependence on de-identification measures and creating a framework with administrative measures in which re-identification risk can be more effectively assessed. These measures include use of statistical control measures that limit access to results with re-identification risk, monitoring of query activity, and policies limiting data access to a population of aligned, trained researchers [10,11,19,20].
While these methods require significant infrastructure and trained staff, they allow for a system in which the primary DUA is no longer the obligation of the researcher but is held by the steward-custodian. The DUA defines the administrative rules the custodian must implement to receive data. Custodians in this schema function as a data keeper extension of the healthcare organization positioned between researchers and data to allow viewing of aggregate results without exposing personally identifiable information. Researchers only have access to aggregate data that is reliably de-identified before they see it. Access is usually restricted to qualified researchers authorized by the custodian organization and its partners. Accessing data by this method eliminates the need for IRB approval and DUAs on the part of the researcher because de-identified data is not subject to HIPAA rules. When the DUA is held by the custodian, access can be administered as “role-based” rather than project or user based. Rather than waiting months for approval of an IRB and negotiation of a multi-institutional DUA, researchers can test a hypothesis at will. Patient privacy protections are in the hands of a data coordinating staff well equipped to maintain and monitor them, a feature that should encourage organizations to share data. One potential schema is detailed in Table 1.
Table 1: Features of a data enclave that can lower DUA/IRB requirements
The administrative and computational method discussed leverages the HIPAA expert pathway to enable broader access to PHI by recognizing the role of custodial and administrative methods in privacy protection. While broadening access to PHI, this method can increase the accountability for privacy since many tasks rest with a committed team that can implement and monitor a system designed to offer best protections and engage emerging threats. While data enclaves have been in existence for some time, they are not commonly promoted to compliantly access PHI by altering the investigator’s relationship with IRB and DUA requirements. With the increasing frequency of requirements that investigators submit data sharing plans with research protocol proposals, it is all the more important to find methods which can induce the transition to safer, more efficient methods of sharing patient information.
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