Highlighting the rules between diagnosis types and laboratory diagnostic tests for patients of an emergency department: Use of association rule mining

Abstract

Diagnostic tests are widely used in emergency departments to make detailed investigations on diagnosis and treat patients correctly. However, since these tests are expensive and time-consuming, ordering correct tests for patients is crucial for efficient use of hospital resources. Thus, understanding the relation between diagnosis and diagnostic test requirement becomes an important issue in emergency departments. Association rule mining was used to extract hidden patterns and relation between diagnosis and diagnostic test requirement in real-life medical data received from an emergency department. Apriori was used as an association rule mining algorithm. Diagnosis was grouped into 21 categories based on International Classification of Disease, and laboratory tests were grouped into four main categories (hemogram, biochemistry, cardiac enzyme, urine and human excrement related). Both positive and negative rules were discovered. Since the nature of the data had the dominance of negative values, higher number of negative rules with higher confidences were discovered compared to positive ones. The extracted rules were validated by emergency department experts and practitioners. It was concluded that understanding the association between patient’s diagnosis and diagnostic test requirement can improve decision-making and efficient use of resources in emergency departments. Association rules can also be used for supporting physicians to treat patients.

Diagnosis and Treatment Rules of Chronic Kidney Disease and Nursing Intervention Models of Related Mental Diseases Using Electronic Medical Records and Data Mining

“…Previous studies have shown that pain and discomfort and neuroendocrine changes caused by chronic diseases cause changes in the transmitters of the central nervous system, thereby inducing the depression. Basically all patients with chronic diseases are accompanied by varying degrees of mental dysfunction, and the most frequent occurrence is depression [24][25][26]. All in all, mental illnesses and CKD recovery interact with each other.…”

Exploration of Machine Learning Techniques to Examine the Journey to Neuroendocrine Tumor Diagnosis with Real-World Data

“…Association rule mining is another technique used to discover and formulate rules around frequent patterns in a dataset. Association rule mining has been used to discover relations between different types of diseases and diagnostic tests in the emergency department to make decisions and plan operations more efficiently [32].…”

Association Rules Mining for Hospital Readmission: A Case Study

“…In recent years, the Apriori algorithm in ARM was frequently used in healthcare services to generate association rules between clinical events and various medications, tests, and other relations [7,31]. Among the tasks of interest of ARM in medical applications were identifying risks [27,32], understanding factors [33,34], discovering patterns [7,12], clinical decision support systems [35,36], feature selection [37], and prediction/classification [38].…”

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