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Introduction

“Without continual growth and progress, such words as improvement, achievement, and success have no meaning.”

-Benjamin Franklin

OBJECTIVES

  • Understand continuous learning systems.

  • Appraise the need for continuous learning systems.

  • Understand educational components of continuous learning systems.

  • Apply systems integration learning points in healthcare simulation.

  • Develop simulation-based interprofessional education to achieve continuous learning health systems.

In July of 2006, the Institute of Medicine (IOM) Roundtable on Evidence-Based Medicine convened a workshop titled “The Learning Healthcare System.” This work group sought to “transform the way evidence on clinical effectiveness is generated and used to improve health and healthcare” (IOM, 2007, p. ix). Its work described the development of a learning healthcare system that is “designed to generate and apply the best evidence for the collaborative healthcare choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety, and value in healthcare” (IOM, 2007, p. ix).

To achieve this, the work group developed the initial needs for a learning healthcare system. These needs were as follows (IOM, 2007, pp. 4-6):

  • “Adaptation to the pace of change: continuous learning and a much more dynamic approach to evidence development and application, taking full advantage of developing information technology to match the rate at which new interventions are developed and new insights emerge about individual variation in response to those interventions;

  • Stronger synchrony of efforts: better consistency and coordination of efforts to generate, assess, and advise on the results of new knowledge in a way that does not produce conflict or confusion;

  • Culture of shared responsibility: to enable the evolution of the learning environment as a common cause of patients, providers, and researchers and better engage all in improved communication about the importance of the nature of evidence and its evolution;

  • New clinical research paradigm: drawing clinical research closer to the experience of clinical practice, including the development of new study methodologies adapted to the practice environment and a better understanding of when RCTs are most practical and desirable;

  • Clinical decision support systems: to accommodate the reality that although professional judgment will always be vital to shaping care, the amount of information required for any given decision is moving beyond unassisted human capacity;

  • Universal electronic health records: comprehensive deployment and effective application of the full capabilities available in EHRs as an essential prerequisite for the evolution of the learning healthcare system;

  • Tools for database linkage, mining, and use: advancing the potential for structured, large databases as new sources of evidence, including issues in fostering interoperable platforms and in developing new means of ongoing searching of those databases for patterns and clinical insights;

  • Notion of clinical data as a public good: advancement of the notion of the use of clinical data as a central common resource for advancing knowledge and evidence for effective care—including directly addressing current ...

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