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At the Intersection of Health Information Technology and Decision Support: Measurement Feedback Systems... and Beyond
Bruce F Chorpita1, Eric L Daleiden2, Adam D Bernstein2
1UCLA Department of Psychology, University of California, Los Angeles, Franz Hall 3227, Los Angeles, CA, 90095, USA. chorpita@ucla.edu.
Abstract:
We select and comment on concepts and examples from the target articles in this special issue on measurement feedback systems, placing them in the context of some of our own insights and ideas about measurement feedback systems, and where those systems lie at the intersection of technology and decision making. We contend that, connected to the many implementation challenges relevant to many new technologies, there are fundamental design challenges that await a more elaborate specification of the clinical information and decision models that underlie these systems. Candidate features of such models are discussed, which include referencing multiple evidence bases, facilitating observed and expected value comparisons, fostering collaboration, and allowing translation across multiple ontological systems. We call for a new metaphor for these technologies that goes beyond measurement feedback and encourages a deeper consideration of the increasingly complex clinical decision models needed to manage the uncertainty of delivering clinical care.
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