Interactive Dissemination: Engaging Stakeholders in the Use of Aggregated Quality Improvement Data for System-Wide Change in Australian Indigenous Primary Health Care - Laycock, Alison; Bailie, Jodie; Matthews, Veronica; Bailie, Ross (Frontiers in Public Health, 2016)
Background Integrating theory when developing complex quality improvement interventions can help to explain clinical and organizational behavior, inform strategy selection, and understand effects. This paper describes a theory-informed interactive dissemination strategy. Using aggregated quality improvement data, the strategy seeks to engage stakeholders in wide-scale data interpretation and knowledge sharing focused on achieving wide-scale improvement in primary health-care quality. Methods An iterative process involving diverse stakeholders in Australian Aboriginal and Torres Strait Islander health-care delivery uses aggregated audit data collected across key areas of care. Phases of reporting and online feedback are used to identify: (1) priority areas for improvement; (2) health center, system, and staff attributes that may be important in addressing the identified priority evidence-practice gaps; and (3) strategies that could be introduced or strengthened to enable improvement. A developmental evaluation is being used to refine engagement processes and reports as the project progresses. Discussion This innovative dissemination approach is being used to encourage wide-scale interpretation and use of service performance data by policy-makers, managers, and other stakeholders, and to document knowledge about how to address barriers to achieving change. Through the developmental evaluation, the project provides opportunities to learn about stakeholders’ needs in relation to the way data and findings are described and distributed, and elements of the dissemination strategy and report design that impact on the useability and uptake of findings. Conclusion The project can contribute to knowledge about how to facilitate interactive wide-scale dissemination and about using data to co-produce knowledge to improve health-care quality.