Megh Marathe
Kentaro Toyama
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An understanding of medical diagnosis as it is practiced is essential for those seeking to support it using intelligent systems. Through the case of epilepsy, we show that diagnosis is a situated, relational, and evolving process that accounts for information well beyond the patient's physiology, even for physiological phenomena like seizures. Through observations and interviews with neurologists, we show that the meaning of brainwaves and other physiological data depends upon a range of patient-specific and contextual factors, such as age, comorbidities, and mealtimes. Further, we show that diagnosis is partly determined by social factors such as the activities of caregivers and other clinicians, and environmental factors such as faulty electrical wiring. Additionally, diagnostic classifications can evolve in response to new information: events that were once considered seizures can be reinterpreted as clinically irrelevant and vice versa. We contribute a broader sociotechnical perspective to literature on intelligent decision making in healthcare and discuss implications for the design of decision support systems that can better support the work of medical diagnosis.
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- The Situated, Relational, and Evolving Nature of Epilepsy Diagnosis
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