TY - JOUR
T1 - Balancing the benefits and costs of antibiotic drugs
T2 - The TREAT model
AU - Leibovici, L.
AU - Paul, M.
AU - Andreassen, S.
PY - 2010/12
Y1 - 2010/12
N2 - TREAT is a computerized decision support system aimed at improving empirical antibiotic treatment of inpatients with suspected bacterial infections. It contains a model that balances, for each antibiotic choice (including 'no antibiotics'), expected benefit and expected costs. The main benefit afforded by appropriate, empirical, early antibiotic treatment in moderate to severe infections is a better chance of survival. Each antibiotic drug was consigned three cost components: cost of the drug and administration; cost of side effects; and costs of future resistance. 'No treatment' incurs no costs. The model worked well for decision support. Its analysis showed, yet again, that for moderate to severe infections, a model that does not include costs of resistance to future patients will always return maximum antibiotic treatment. Two major moral decisions are hidden in the model: how to take into account the limited life-expectancy and limited quality of life of old or very sick patients; and how to assign a value for a life-year of a future, unnamed patient vs. the present, individual patient.
AB - TREAT is a computerized decision support system aimed at improving empirical antibiotic treatment of inpatients with suspected bacterial infections. It contains a model that balances, for each antibiotic choice (including 'no antibiotics'), expected benefit and expected costs. The main benefit afforded by appropriate, empirical, early antibiotic treatment in moderate to severe infections is a better chance of survival. Each antibiotic drug was consigned three cost components: cost of the drug and administration; cost of side effects; and costs of future resistance. 'No treatment' incurs no costs. The model worked well for decision support. Its analysis showed, yet again, that for moderate to severe infections, a model that does not include costs of resistance to future patients will always return maximum antibiotic treatment. Two major moral decisions are hidden in the model: how to take into account the limited life-expectancy and limited quality of life of old or very sick patients; and how to assign a value for a life-year of a future, unnamed patient vs. the present, individual patient.
KW - Antibiotic drugs
KW - Cost-benefit
KW - Decision support
KW - Resistance
KW - Review
KW - Survival
UR - http://www.scopus.com/inward/record.url?scp=78349241042&partnerID=8YFLogxK
U2 - 10.1111/j.1469-0691.2010.03330.x
DO - 10.1111/j.1469-0691.2010.03330.x
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C2 - 20673259
AN - SCOPUS:78349241042
SN - 1198-743X
VL - 16
SP - 1736
EP - 1739
JO - Clinical Microbiology and Infection
JF - Clinical Microbiology and Infection
IS - 12
ER -