The inappropriate prescription of antibiotics may cause severe medical outcomes such as antibiotic resistance. To prevent such situations and facilitate appropriate antibiotic prescribing, we designed and developed an asynchronous collaborative visual analytics tool. It visualizes the antibiotics’ coverage spectrum that allows users choose the most appropriate antibiotics. The asynchronous collaboration around visualization mimics the actual collaboration scenarios in clinical settings, and provides supportive information during physician’s decision-making process. Our work contributes to CSCW community by providing a design prototype to support asynchronous collaboration among healthcare professionals, which is crucial but lacks in many of the present clinical decision support systems.
Dr. Adam is a family doctor. He is treating a 32-year-old man with skin infection, whose body temperature is 38.5C. He suspects that the infection is probably caused by Staphylococcus aureus. However, the patient is allergic to penicillin, the most commonly used antibiotic for such infection. Therefore, Dr. Adam uses the system to check if there is any other antibiotic that fits this case. The system visualized 15 antibiotics that can target the suspect bacteria. Dr. Adam notices below the main visualization, in the collaboration part, a previous user dealt with the similar case before, and it chose cefazolin. Inspired by that, Dr. Adam finally makes his treatment decision, and shares his opinion within the community. Dr. Adam also clicks the “thumb up” button, as he adopts the decision opinion from this user.
Jin, W., Gromala, D., Neustaedter, C., & Tong, X. (2017, February). A Collaborative Visualization Tool to Support Doctors’ Shared Decision-Making on Antibiotic Prescription. In Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW), pp. 211-214.
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