Our study assumed that drug usage may have the chance to cause ADRs one week later. In practice, however, the time from using a drug to an attack of an adverse event may be much longer. Although our results showed that there was no significant effect between different lengths of aggregated period in the detection performance, time factor is still an important issue when detecting ADRs in health databases. For instance, we can consider two nonadjacent patient weeks when building the precedence relationship between drugs and diagnoses to represent the deferred effect of drugs.
Moreover, our dataset covers near 1.5 million drug-diagnosis pairs (the combina-tion of 1,125 diagnoses and 1,326 drugs); however, ADRs form a relatively small part of all the diagnoses in NHIRD. This data imbalance problem may bring difficulties when screening drug-ADR pairs in all drug-diagnosis pairs.
Finally, detection performance may be further improved by bringing more proper-ties, e.g., dosage of the drug, to the aggregated patient weeks. Other scores introduced in Chapter 2, e.g., information component, may be added to the combined detecting scores.
However, we should consider the impact of feature expansion on time efficiency (in our study, it took less than four hours to calculate scores for 7.5 million patient weeks by a computer equipped with an Intel Core-i7 3.2Ghz CPU).
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