Gerke S, Yeung S, Cohen IG.
Ambient intelligence in hospitals is an emerging form of technology characterized by a constant awareness of activity in designated physical spaces and of the use of that awareness to assist health care workers such as physicians and nurses in delivering quality care. Recently, advances in artificial intelligence (AI) and, in particular, computer vision, the domain of AI focused on machine interpretation of visual data, have propelled broad classes of ambient intelligence applications based on continuous video capture.
One important goal is for computer vision-driven ambient intelligence to serve as a constant and fatigue-free observer at the patient bedside, monitoring for deviations from intended bedside practices, such as reliable hand hygiene and central line insertions. While early studies took place in single patient rooms, more recent work has demonstrated ambient intelligence systems that can detect patient mobilization activities across 7 rooms in an ICU ward and detect hand hygiene activity across 2 wards in 2 hospitals.
As computer vision–driven ambient intelligence accelerates toward a future when its capabilities will most likely be widely adopted in hospitals, it also raises new ethical and legal questions. Although some of these concerns are familiar from other health surveillance technologies, what is distinct about ambient intelligence is that the technology not only captures video data as many surveillance systems do but does so by targeting the physical spaces where sensitive patient care activities take place, and furthermore interprets the video such that the behaviors of patients, health care workers, and visitors may be constantly analyzed. This Viewpoint focuses on 3 specific concerns: (1) privacy and reidentification risk, (2) consent, and (3) liability.
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