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The Connections Matter: Bi-Directional Learning in Program Evaluation and Practice-Oriented Research
Susan Douglas1, Andrew C Page2, Christian Moltu3,4
1Department of Leadership, Policy and Organizations, Vanderbilt University, Peabody College, 230 Appleton Place PMB #414, Nashville, TN, 37203-5721, USA. susan.douglas@vanderbilt.edu.
Embedded program evaluation, using a human-centered systems lens, enhances practice-oriented research. This approach fosters evaluator-practitioner partnerships for improved evidence-based practice and patient outcomes.
Area of Science:
- Health Services Research
- Program Evaluation
- Systems Science
Background:
- Practice-oriented research requires systematic evaluation integrated into clinical workflows.
- Existing evaluation methods may not fully capture the complexity of healthcare settings.
- A need exists for frameworks that bridge practice-based evidence and evidence-based practice.
Purpose of the Study:
- To propose a novel conceptual framework for embedded program evaluation in clinical settings.
- To leverage a human-centered systems lens to guide evaluation practices.
- To enhance the partnership between evaluators and practitioners for bi-directional learning.
Main Methods:
- Utilizing a human-centered systems lens, incorporating design thinking and systems thinking principles.
- Emphasizing evaluator-practitioner collaboration and mutual learning.
- Recommending tools such as systems mapping, program theory development, and logic models.
Main Results:
- The proposed framework facilitates the integration of evaluation into clinical routine.
- It promotes awareness of individual and systemic biases within healthcare institutions.
- Case examples from routine outcome monitoring and progress feedback illustrate the framework's application.
Conclusions:
- Embedded program evaluation, guided by a human-centered systems lens, is well-suited for practice-oriented research.
- Strengthening the evaluator-practitioner partnership is crucial for local and system-level healthcare improvement.
- Further research is needed to refine collaborative models and enhance evaluation's impact.
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