Abstract
Empirical antibiotic treatment with broad-spectrum antibiotics provides a high probability of covering treatment, but is associated with unnecessary costs as high drug prices, side-effects, and facilitated development of antibiotic resistance. A decision support system (DSS) based upon a causal probabilistic network (CPN) was constructed from a database with 491 cases (1992–94) of urosepticaemia and validated on 426 cases (1995–96). The CPN uses decision theory to balance the gain in life-years due to therapy against the costs of the antibiotic therapy, i.e. price, side-effects and ecological cost. The DSS selected antibiotics of an overall lower price, higher coverage and less ecological cost than the antibiotics actually chosen for empirical treatment. Thus, a DSS incorporating the CPN could achieve a desirable antibiotic policy, and it holds promise for improving empirical antibiotic therapy.
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Andreassen, S. et al. (1999). A Decision Theoretic Approach to Empirical Treatment of Bacteraemia Originating from the Urinary Tract. In: Horn, W., Shahar, Y., Lindberg, G., Andreassen, S., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIMDM 1999. Lecture Notes in Computer Science(), vol 1620. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48720-4_21
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DOI: https://doi.org/10.1007/3-540-48720-4_21
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