Methodologies for evaluating strategies to reduce diagnostic error: report from the research summit at the 7th International Diagnostic Error in Medicine Conference

Abstract

Abstract In this article we review current evidence on strategies to evaluate diagnostic error solutions, discuss the methodological challenges that exist in investigating the value of these strategies in patient care, and provide recommendations for methods that can be applied in investigating potential solutions to diagnostic errors. These recommendations were developed iteratively by the authors based upon initial discussions held during the Research Summit of the 7th Annual Diagnostic Error in Medicine Conference in September 2014. The recommendations include the following elements for designing studies of diagnostic research solutions: (1) Select direct and indirect outcomes measures of importance to patients, while also practical for the particular solution; (2) Develop a clearly-stated logic model for the solution to be tested; (3) Use rapid, iterative prototyping in the early phases of solution testing; (4) Use cluster-randomized clinical trials where feasible; (5) Avoid simple pre-post designs, in favor of stepped wedge and interrupted time series; (6) Leverage best practices for patient safety research and engage experts from relevant domains; and (7) Consider sources of bias and design studies and their analyses to minimize selection and information bias and control for confounding. Areas of diagnostic error mitigation research identified for further attention include: role of competing diagnoses, understanding the impacts of organizational culture, timing of diagnosis, and sequencing of research studies. Future research will likely require novel clinical, health services, and qualitative research methods to address the age-old problem of arriving at an accurate diagnosis.