Which clinical decisions benefit from automation? A task complexity approach.
This paper describes a model for analysing medical decision making tasks and evaluation of their suitability for automation. The overall approach focuses on the assessment of decision complexity and possible reduction of human effort by automated decision support. The approach consists of five subsequent steps: (1) selection of the domain and relevant tasks; (2) evaluation of the knowledge complexity for tasks selected; (3) selection of potentially most cognitively demanding task; (4) assessment of unaided and aided effort requirements for this task accomplishment; and (5) selection of computational tools to achieve this complexity reduction. The model described allows for task automation without lowering of decision quality.
Centre for Health Informatics at the University of New South Wales, Sydney 2056, Australia.
Vitali
V
Sintchenko
Enrico
E
Coiera
D000900:Anti-Bacterial Agents / Q000008:administration & dosage; D001331:Automation; D020000:Decision Support Systems, Clinical; D011307:Drug Prescriptions; D006801:Humans; D007362:Intensive Care Units; D009517:New South Wales; D011014:Pneumonia / Q000188:drug therapy / Q000209:etiology; D012121:Respiration, Artificial / Q000009:adverse effects
D000900:Anti-Bacterial Agents