Inaccurate, untimely, and miscommunicated medical diagnoses represent a wicked problem requiring comprehensive and coordinated approaches, such as those demonstrated in the characteristics of learning health systems (LHSs). To appreciate a vision for how LHS methods can optimize processes and outcomes in medical diagnosis (diagnostic excellence), we interviewed 32 individuals with relevant expertise: 18 who have studied diagnostic processes using traditional behavioral science and health services research methods, six focused on machine learning (ML) and artificial intelligence (AI) approaches, and eight multidisciplinary researchers experienced in advocating for and incorporating LHS methods, ie, scalable continuous learning in health care. We report on barriers and facilitators, identified by these subjects, to applying their methods toward optimizing medical diagnosis. We then employ their insights to envision the emergence of a learning ecosystem that leverages the tools of each of the three research groups to advance diagnostic excellence. We found that these communities represent a natural fit forward, in which together, they can better measure diagnostic processes and close the loop of putting insights into practice. Members of the three academic communities will need to network and bring in additional stakeholders before they can design and implement the necessary infrastructure that would support ongoing learning of diagnostic processes at an economy of scale and scope. KEYWORDS diagnostic error, learning community, learning health systems, machine learning, medical diagnosis, multidisciplinary
Although trauma-informed approaches guide services to families experiencing homelessness, more emphasis is placed on securing housing than addressing underlying trauma contributing to housing instability. Examining the stories of 29 homeless and/or unstably housed mothers within the broader literature on family trauma and violence, chronic illness, and cultural aspects of family functioning, we define the process of trauma normativeness and normalization that may occur with repeated trauma experiences and argue that rehousing efforts must include concomitant attention to trauma and to understanding how individual, family, community, and cultural factors influence help-seeking behaviors in this vulnerable and growing population.
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