Designing a diagnostic test order recommendation system: a data analytics approach

Official URL: https://risc01.sabanciuniv.edu/record=b2482904 _(Table of Contents)

In the thesis, we propose a frequent itemset detection based on a diagnostic test order set recommendation by ICD code for internal medicine physicians. In order to carry out this study, we used an examination data from the internal medicine department of a state hospital in Ankara, Turkey, which included 68,033 unique visits and 46,314 unique patients in the closed interval of 2015-2016. In the study, we calculated how using the test sets that we determined with the Apriori algorithm in the training set might affect the test selection effort in the ongoing period. As an evaluation criterion, we used the percentage change in the total number of clicks that the physician will use when choosing a test on HIMS if the test request group is used. In addition, we calculated the percentage of the visit that the recommendation set could be used by looking at the intersection of the examination request of the physician and the test set we recommended