Supporting implementation of evidence-based behavioral interventions: the role of data liquidity in facilitating translational behavioral medicine

摘要

The advancement of translational behavioral medicine will require that we discover new methods of managing large volumes of data from disparate sources such as disease surveillance systems, public health systems, and health information systems containing patient-centered data informed by behavioral and social sciences. The term “liquidity,” when applied to data, refers to its availability and free flow throughout human/computer interactions. In seeking to achieve liquidity, the focus is not on creating a single, comprehensive database or set of coordinated datasets, nor is it solely on developing the electronic health record as the “one-stop shopping” source of health-related data. Rather, attention is on ensuring the availability of secure data through the various methods of collecting and storing data currently existent or under development—so that these components of the health information infrastructure together support a liquid data system. The value of accessible, interoperable, high-volume, reliable, secure, and contextually appropriate data is becoming apparent in many areas of the healthcare system, and health information liquidity is currently viewed as an important component of a patient-centered healthcare system. The translation from research interventions to behavioral and psychosocial indicators challenges the designers of healthcare systems to include this new set of data in the correct context. With the intention of advancing translational behavioral medicine at the local level, “on the ground” in the clinical office and research institution, this commentary discusses data liquidity from the patient’s and clinician’s perspective, requirements for a liquid healthcare data system, and the ways in which data liquidity can support translational behavioral medicine.