Title: | Heterogeneous Network Analysis of Disease Clinical Treatment Measures via Mining Electronic Medical Record Data |
Speaker: | Professor Shuangge Ma, Department of Biostatistics, Yale School of Public Health, USA |
Time/Place: | 14:30 - 15:30 FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University |
Abstract: | The analysis of clinical treatment measures has been extensively conducted and can facilitate more effective resource management and planning and also assist better understanding diseases. Most of the existing analyses have been focused on a single disease or a large number of diseases combined. Partly motivated by the successes of gene-centric and phenotypic human disease network (HDN) research, there has been growing interest in the network analysis of clinical treatment measures. However, the existing studies have been limited by a lack of attention to heterogeneity and relevant covariates, ineffectiveness of methods, and low data quality. In this study, our goal is to mine the Taiwan National Health Insurance Research Database (NHIRD), a large population-level electronic medical record (EMR) database, and construct HDNs for number of outpatient visits and medical cost. Significantly advancing from the existing literature, the proposed analysis accommodates heterogeneity and effects of covariates (for example, demographics). Additionally, the proposed method effectively accommodates the zero-inflation nature of data, Poisson distribution, high-dimensionality, and network sparsity. Computational and theoretical properties are carefully examined. Simulation demonstrates competitive performance of the proposed approach. In the analysis of NHIRD data, two and five subject groups are identified for outpatient visit and medical cost, respectively. The identified interconnections, hubs, and network modules are found to have sound implications. |
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