![]() 4, 5įor the best results, the project team suggests having multiple reviewers complete the assessment and discuss findings. ![]() Since the release of the revised iteration of the tool (i.e., the Revised Safer Dx Instrument), use of condition-specific adaptations of the tool (e.g., Safer Stroke Dx) have found it to yield accurate results. ![]() 3 The project team made minor revisions to the original tool to address feedback from the pilot studies, as well as from several national experts. 2 A study published in 2017 on use of the tool in a pediatric intensive care unit found the tool had inter-rater agreement of 93.6% ( k, 0.72). In this study, the instrument yielded overall accuracy of 84%. The original tool, the Safer Dx Instrument, was validated in a primary care setting, and results were published in 2016. If the assessment indicates there was a likely diagnostic error (defined as a missed opportunity in diagnosis), users have the option to complete an additional process breakdown assessment as a guide designed to help identify factors contributing to the potential missed opportunity. 1 To answer the questions, the evaluator collects data from comprehensive electronic health records including information on a patient’s medical history, examination information, diagnostic test interpretation, and follow-up testing and diagnostic assessment. The instrument consists of a series of questions that address five aspects of the diagnostic process: (1) the patient-provider encounter (history, physical examination, ordering tests/referrals based on assessment) (2) performance and interpretation of diagnostic tests (3) follow-up and tracking of diagnostic information over time (4) subspecialty and referral-specific factors and (5) patient-related factors. ![]() Results of the assessment are intended for use in system-level safety improvement efforts, clinician feedback, and patient safety research. The Revised Safer Dx Instrument provides a standardized list of questions to help users retrospectively identify and assess the likelihood of a missed diagnosis in a healthcare episode.
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