Abstract

Context: The practice of policy surveillance, defined as the systematic scientific tracking of laws of public health importance, supports public health research and practice in several ways: it produces legal data for evaluation research; it increases public and practitioner awareness of the state of, and trends in, important public health laws; it supports advocacy for the wider adoption of evidence-backed legal reforms; and in all these ways it increases awareness and salience of law in public health. Funding from major public health organizations, and advances in information technology, have made policy surveillance more feasible for researchers and practitioners across public health topics. Under a grant from the National Institute on Drug Abuse (NIDA), the Policy Surveillance Program (PSP) at the Center for Public Health Law Research at Temple University, advised by leaders at the Alcohol Policy Information System and the Centers for Disease Control and Prevention, convened a meeting of policy surveillance and legal mapping practitioners to discuss needs and identify next steps for improving quality and value in policy surveillance, and strengthening the field. Convening: Fifty people from a diverse set of organizations met over two days to discuss the state of the field, and to work in small groups to define needs and next steps. Working groups were devised by the participants and included Field-building, Research Methods, Implementation, Local Policy Surveillance, International Policy Surveillance, Data Standards, and Funding. Results: There was consensus that the value of policy surveillance lies in the credibility and utility of the data it produces. These value elements are thus crucial guides for building the field on a sustainable basis. Building the field requires a strong network of practitioners working together to develop and maintain appropriate standards of scientific research and data accessibility. Sustainability depends on several key activities: continued innovation, training, technological advances (such as machine-assisted research), enhanced access to existing data and curation of data over time, funding, and a professional organization or other mechanism to continue the development of a cohesive set of practitioners.

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