How Dissemination and Implementation Science Can Contribute to the Advancement of Learning Health Systems
Bibliographic Data
Many health systems are working to become learning health systems (LHSs), which aim to improve the value of health care by rapidly, continuously generating evidence to apply to practice. However, challenges remain to advance toward the aspirational goal of becoming a fully mature LHS. While some important challenges have been well described (i.e., building system-level supporting infrastructure and the accessibility of inclusive, integrated, and actionable data), other key challenges are underrecognized, including balancing evaluation rapidity with rigor, applying principles of health equity and classic ethics, focusing on external validity and reproducibility (generalizability), and designing for sustainability. Many LHSs focus on continuous learning cycles, but with limited consideration of issues related to the rapidity of these learning cycles, as well as the sustainability or generalizability of solutions. Some types of data have been consistently underrepresented, including patient-reported outcomes and preferences, social determinants, and behavioral and environmental data, the absence of which can exacerbate health disparities. A promising approach to addressing many challenges that LHSs face may be found in dissemination and implementation (D&I) science. With an emphasis on multilevel dynamic contextual factors, representation of implementation partner engagement, pragmatic research, sustainability, and generalizability, D&I science methods can assist in overcoming many of the challenges facing LHSs. In this article, the authors describe the current state of LHSs and challenges to becoming a mature LHS, propose solutions to current challenges, focusing on the contributions of D&I science with other methods, and propose key components and characteristics of a mature LHS model that others can use to plan and develop their LHSs
Data science · Generalizability theory · Health care · Knowledge management · Management science · Political science · Sustainability · Computer Science · Engineering · Health Policy Implementation Science · Health Systems, Economic Evaluations, Quality of Life · Interprofessional Education and Collaboration · Psychology
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Making sense of implementation theories, models and frameworks
The Science of Improvement
The FRAME
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RE-AIM Planning and Evaluation Framework
The PRECIS-2 tool
“Scaling-out” evidence-based interventions to new populations or new health care delivery systems
The dynamic sustainability framework
Making Implementation Science More Rapid
Planning for Implementation Success Using RE-AIM and CFIR Frameworks
An Extension of RE-AIM to Enhance Sustainability
Learning From What We Do, and Doing What We Learn
Community-Engaged Research
Learning health systems from an academic perspective
The Adaptome
Designing for Dissemination Among Public Health Researchers
Quality Enhancement Research Initiative Implementation Roadmap
Accelerating Research Impact in a Learning Health Care System
Social Ecological Approaches to Individuals and Their Contexts
Implementing, Embedding, and Integrating Practices
| Unique citing works | 6 |
|---|---|
| Citations per year | 1,5 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 6 |