Multimorbidity is a complex problem that has received increasing attention in recent decades. The static quantitative measurements and small-scale conditions focus may obscure the interaction amongst conditions. Network science can inherently capture these interactions via extracting topological features in the network. This study developed a dynamic index to assess primary care for the elderly with multimorbidity. 1,924 Australians with long-term multimorbidity, aged 65 and over, were extracted from the Australian National Health Survey 2014-2015. Twenty-eight health conditions were weighted via gender-stratified network eigenvector centralities. The correlation between the network index for individuals and corresponding general practitioner (GP) utilization was compared with the Charlson Comorbidity Index (CCI). The network approach can achieve a 114% increase in this correlation and a 53% increase in R2 after risk-factor adjustment compared to the CCI. Therefore, network approach may offer a new and dynamic approach to assess GP utilization for Australian elderly patients with mental and physical multimorbidity. A high correlation between CCI and network index suggests that combining with CCI the new index may promote the assessment of primary care utilization. However, the generalizability of the new approach requires further validation tests.
Guo, Ruihua; Choi, Boris; and Poon, Simon, "A New Network-Based Multimorbidity Index for BEtter Primary Care Assessment for Elders: The Australian Context" (2020). ECIS 2020 Research-in-Progress Papers. 49.
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