Issues related to CDS

Content:

This week's BMI 502 focused on the clinical decision support system by Dr Green. He definitly is one of the founder in the development of clinical decision support system, and his introduction in class give us a full coverage of this field from different perspectives, including technology, fundamental principles, and challenge and problems related to the application of CDSS in clinical practice. The technologies in CDSS discussed in class mainly includes the rule based classification, artificial intelligence, Bayes rules, and the advantage and disadvantage of CDSS in clinical application were also discussed.

With Dr Green's introduction on the rule based clinical decision support system. The first thought in my mind is the decision tree model introduced in Data mining class. They are two really similar mechanims that dealed by computer to give the final unkonwn decision based on the known information or predictor. But one important difference between the decision tree model and rule based clinical decision support system is that the rule based clinical decision support system use the previously setted rules, based on clinical knowledge, to build the ensemble of rules, not as the decision tree which use the unkown trainning data to train the computers to learn the rule by computers themselves. So the rule based clinical decision support system more rely on the knowledge based rule, just as a model which abstracts the clinical diagnostic standards and transfer these standards to computer understandable concepts. Therefore, based on this point, the clinical decision support system is no more than a semi-artificial intelligence system, and what it can do is to efficiently remind the clinicians to notice something and increase the working efficiency and reduce the working pressure of physicians. Also by this way, the medical error can be reduced and the higher quality of health service would be offered to patients. However, whether the CDSS will develop towards to smarter level, which can self learn from the previous patient cases to conclude new rules to fit into new patient case and provide the decisioin advice for physicians.

Dr Green's also discuss one imporant issue about the application off CDSS in clinical practice, and the response of physician to CDSS. From his introduction, I think the resistance for physicians' acceptance of CDSS system is a real complex issue. One of the most imporant issue is the trustable of the CDSS system, which I think is one concern of physician. Although Dr Green mentioned that the aim of CDSS is not to make decision instead of physicians and the physicians still need to based own their own analysis to make the final decision, the reliability and error of CDSS are still a big challenge for widely acceptance by physicians. Because if the CDSS gives the error or wrong decision advice to physician, it is higly probable to mislead physician to get the wrong decision. Moreover, the other issue related to application of CDSS is who will take the responsibility of error diagnostic result. Will the machine take the responsibility? It is a problem...

By Di Pan