Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework

BMJ Qual Saf. 2015 Feb;24(2):103-10. doi: 10.1136/bmjqs-2014-003675. Epub 2015 Jan 14.


Diagnostic errors are major contributors to harmful patient outcomes, yet they remain a relatively understudied and unmeasured area of patient safety. Although they are estimated to affect about 12 million Americans each year in ambulatory care settings alone, both the conceptual and pragmatic scientific foundation for their measurement is under-developed. Health care organizations do not have the tools and strategies to measure diagnostic safety and most have not integrated diagnostic error into their existing patient safety programs. Further progress toward reducing diagnostic errors will hinge on our ability to overcome measurement-related challenges. In order to lay a robust groundwork for measurement and monitoring techniques to ensure diagnostic safety, we recently developed a multifaceted framework to advance the science of measuring diagnostic errors (The Safer Dx framework). In this paper, we describe how the framework serves as a conceptual foundation for system-wide safety measurement, monitoring and improvement of diagnostic error. The framework accounts for the complex adaptive sociotechnical system in which diagnosis takes place (the structure), the distributed process dimensions in which diagnoses evolve beyond the doctor's visit (the process) and the outcomes of a correct and timely "safe diagnosis" as well as patient and health care outcomes (the outcomes). We posit that the Safer Dx framework can be used by a variety of stakeholders including researchers, clinicians, health care organizations and policymakers, to stimulate both retrospective and more proactive measurement of diagnostic errors. The feedback and learning that would result will help develop subsequent interventions that lead to safer diagnosis, improved value of health care delivery and improved patient outcomes.

Keywords: Diagnostic errors; Health services research; Information technology; Medical error, measurement/epidemiology; Quality measurement.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Diagnostic Errors / prevention & control
  • Diagnostic Errors / statistics & numerical data*
  • Humans
  • Models, Organizational
  • Patient Safety / statistics & numerical data
  • Quality Improvement / organization & administration
  • Quality of Health Care / organization & administration
  • Quality of Health Care / standards