Diseases can be interconnected. In the recent years, there has been a surge of multidisease studies. Among them, HDN (human disease network) analysis takes a system perspective, examines the interconnections among diseases along with their individual properties, and has demonstrated great potential. Most of the existing HDN analyses are based on either molecular information (which may be unreliable and have limited clinical relevance) or phenotypic measures (which may have limited implications for disease management and not directly reflect disease severity). In this study, we take advantage of the uniquely valuable Taiwan NHIRD (National Health Insurance Research Database) data and conduct an HDN analysis of disease treatment cost. Complementing the existing literature, treatment cost can serve as a surrogate of disease severity (and hence be clinically highly relevant) and also directly describe the financial burden of illness (and hence be uniquely informative for disease management). With inpatient and outpatient treatment data on close to 1 million randomly selected subjects and collected during the period of 2000 to 2013, the human disease cost network is constructed using a novel copula-based approach and the weighted correlation-based network construction technique. Extensive analysis is conducted, and the results are found to be biomedically sensible.