TY - JOUR
T1 - Computerised advice on drug dosage decisions in childhood leukaemia: A method and a safety strategy
AU - Hurt, Chris
AU - Fox, John
AU - Bury, Jonathan
AU - Saha, Vaskar
PY - 2003
Y1 - 2003
N2 - Currently over 95% of children who are diagnosed with Acute Lymphoblastic Leukaemia in the UK are enrolled into Medical Research Council trials. The trial protocol specifies that following initial treatment there is a 2-3 year maintenance period during which drug dosage decisions are made weekly according to a set of pre-defined rules. These rules are complex, and there is a significant frequency of error in clinical practice, which can lead to patient harm. We have built a web-based decision support system (called LISA) to address this problem. The dose alteration rules from lie MRC protocol were formalised in the PROforma guideline modeling language as a state transition problem, and dose adjustment recommendations are provided into the clinical setting by a PROforma enactment engine. The design and implementation of the decision support module, the safety issues raised and the strategy adopted for resolving them are discussed. System safety is very likely to become a major professional challenge for the medical AI community and it can be addressed, in this case, with relatively straightforward techniques.
AB - Currently over 95% of children who are diagnosed with Acute Lymphoblastic Leukaemia in the UK are enrolled into Medical Research Council trials. The trial protocol specifies that following initial treatment there is a 2-3 year maintenance period during which drug dosage decisions are made weekly according to a set of pre-defined rules. These rules are complex, and there is a significant frequency of error in clinical practice, which can lead to patient harm. We have built a web-based decision support system (called LISA) to address this problem. The dose alteration rules from lie MRC protocol were formalised in the PROforma guideline modeling language as a state transition problem, and dose adjustment recommendations are provided into the clinical setting by a PROforma enactment engine. The design and implementation of the decision support module, the safety issues raised and the strategy adopted for resolving them are discussed. System safety is very likely to become a major professional challenge for the medical AI community and it can be addressed, in this case, with relatively straightforward techniques.
M3 - Article
SN - 0302-9743
VL - 2780
SP - 158
EP - 162
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -