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Patient Safety, Quality Improvement, & Complex Systems

Provides resources for students, clinicians, researchers, & administrators on patient safety, quality improvement, & complex healthcare systems.

Michigan Medicine/Ann Arbor VA Resources

Michigan Medicine has been a national leader in patient safety for years.  Below are some links to important patient safety resources from Michigan Medicine and the Ann Arbor VA Hospital.

New Tools

Infographic of Diagnositic Safety

Measure Dx: A Resource To Identify, Analyze, and Learn From Diagnostic Safety Events.

It includes 4 sections that outline a series of steps to begin and sustain measurement of diagnostic safety.

  • Part I outlines ways to engage people in the organization to ensure adequate resources to implement measurement and learning activities.
  • Part II contains a self-assessment checklist to gauge readiness for implementation, as well as guidance for choosing a measurement strategy that fits with your organization's resources.
  • Part III describes four different strategies (systematic approaches to measurement) based on different types of data sources.
  • Part IV provides recommendations for systematically reviewing and analyzing case data and translating findings into useful insights for learning and improvement.

Resource Focus

Studying complexity in health services research: desperately seeking an overdue paradigm shift. 

Trisha Greenhalgh and Chrysanthi Papoutsi, BMC Medicine 2018; 16:95


Complexity is much talked about but sub-optimally studied in health services research. Although the significance of the complex system as an analytic lens is increasingly recognised, many researchers are still using methods that assume a closed system in which predictive studies in general, and controlled experiments in particular, are possible and preferred. We argue that in open systems characterised by dynamically changing inter-relationships and tensions, conventional research designs predicated on linearity and predictability must be augmented by the study of how we can best deal with uncertainty, unpredictability and emergent causality. . . . Each of the initial five papers in this collection illustrates, in different ways, the value of theoretically grounded, methodologically pluralistic, flexible and adaptive study designs. We propose an agenda for future research and invite researchers to contribute to this on-going series.

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