Background Improvement science has supported the methodological foundations for the application of quality improvement (QI) ...
This workshop will provide an introduction to the types of theories, models, and frameworks (TMFs) commonly used in dissemination and implementation science, including pros and cons and application of ...
Software engineers developing artificial intelligence (AI) models using standard frameworks such as Keras, PyTorch, and TensorFlow are usually not well-equipped to translate those models into ...
New technologies are often so brimming with potential that they're difficult to define. In turn, that makes them harder to implement as part of an overarching digital transformation strategy. Many ...
Over the past decade, health researchers have sought to apply the fundamental principles of implementation science as a systematic and comprehensive approach to improving health care practice, ...
Similar to how we synthesized a framework for value-based payment (VBP)-specific design considerations in previous Health Affairs Forefront work, we present here a brief framework for categorizing the ...
Effective pre-implementation planning is critical for successful adoption of intelligent process automation (IPA). The comprehensive IPA pre-implementation framework outlined in this document provides ...
As organizations invest billions of dollars in artificial intelligence, most still struggle to translate those investments into measurable results. Researchers at Carnegie Mellon University’s Software ...
The African Centre for Leadership, Strategy and Development (Centre LSD), alongside political economists and development specialists, has commended President Bola Ahmed Tinubu for proposing the ...
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