Diagnostic errors often involve problems in data gathering and synthesis, including in the use of diagnostic testing.1,2 In several comprehensive analyses of diagnostic errors, problems with the testing process (including test selection and ordering, specimen collection, interpretation, and followup) are among the most prominent contributing factors.1,3-5
In contrast to clinical reasoning errors (e.g., failure to consider alternative hypotheses),1-4,6,7 testing process issues are relatively more amenable to interventions. Such interventions can be supported by bringing the clinical laboratory into a broader strategy to advance accurate and timely diagnoses and reduce diagnostic errors.8 A variety of actionable approaches are available to ensure that diagnostic tests are used appropriately, described collectively as diagnostic stewardship.9,10
Diagnostic stewardship refers to “ordering the right tests for the right patient at the right time to provide information necessary to optimize clinical care.”11 However, the concept of diagnostic stewardship extends beyond test selection and ordering and also includes, for instance, reporting results in ways that maximize the usefulness of tests and guide best clinical actions.10,12,13
Applying diagnostic stewardship beyond infectious disease testing is a recent advance that focuses on applying a multidisciplinary, data-driven approach to the broader scope of diagnostic testing to optimize clinical care for patients.9,10,14 Partnerships between clinicians and clinical laboratory professionals are essential to the success of diagnostic stewardship initiatives.8,15
This issue brief is a call to action for healthcare organization leaders and policymakers to bridge clinical laboratory expertise and routine clinical decision making through diagnostic stewardship. We review existing models and strategies to implement diagnostic stewardship practices and identify how these practices can enhance diagnostic safety. We also discuss measuring implementation of diagnostic stewardship and policy implications.