collection and use processes are respectful of their efforts, their privacy, and responsive to their needs.

Regulatory reform. Development of mutual understandings of expectations for confidentiality, privacy, and security were highlighted as key to building and maintaining strong stakeholder support in the rapidly evolving environment of social media, increased availability of information online, and the growing integration of genomics into clinical care and diagnostics.

Presentation. Increasing the usefulness of data to patients, and other stakeholders, through the use of user-appropriate data presentation techniques, including visualization, was suggested by several workshop participants.

Health literacy. A few participants cautioned that efforts to improve understanding through raising awareness and targeted strategies at different health literacy levels will be necessary to facilitate these discussions.

Culture of participation. Given this changing environment, the suggestion was made to empower potential data donors (notably patients) with the option and ability to donate their information for use. Along similar lines, the idea of studying the benefits and risks of patient-requested portable identifiers was suggested as a way to make progress on the issue of identity resolution and data linkage, and a first step toward developing a strategy for their development and application.

BUILDING A CLINICAL DATA LEARNING UTILITY

Throughout workshop presentations and discussions, some speakers and participants stressed the need to harness the potential for learning from the digital health data utility. The challenges and opportunities afforded by the increasing scale of data available for learning informed many of these discussions.

Innovative methods. The development of methods using EHRs as a data source and performing observational studies on big data were highlighted as specific needs. In particular, the development, validation, and use of predictive models to inform health-data uses, including risk interpretation by individuals, was singled out as holding great promise. Noting that most digital health data is in unstructured formats, the potential for learning from this data through natural language processing (e.g., IBM’s Watson) was highlighted by several workshop participants. An emphasis on the need for the development and application of reasoning and inference tools was highlighted as a potential priority going forward.

Distributed approaches. Given the importance of privacy and security in the collection and use of patient health data, presentations and discussions frequently touched on the advantages of distributed data approaches



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