Demographics, in-hospital analysis, and prevalence of 33 rare diseases with effective treatment in Shanghai

Orphanet Journal of Rare Diseases

Xiaoshu Cai¹  Guangjun Yu¹  Hui Lu²  Georgi Z. Genchev³  Ping He⁴ 

[1] Center for Biomedical Informatics, Shanghai Children’s Hospital, Shanghai, China;Center for Biomedical Informatics, Shanghai Children’s Hospital, Shanghai, China;SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, Shanghai, China;Department of Bioinformatics and Biostatistics, Shanghai Jiao Tong University, Shanghai, China;Center for Biomedical Informatics, Shanghai Children’s Hospital, Shanghai, China;SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, Shanghai, China;Department of Bioinformatics and Biostatistics, Shanghai Jiao Tong University, Shanghai, China;Bulgarian Institute for Genomics and Precision Medicine, Sofia, Bulgaria;Shanghai Hospital Development Center, Shanghai, China;

关键词: Rare disease;    Orphan disease;    Health care policy;    Shanghai;    China;    Epidemiology;    Rare disease prevalence;   

DOI  :  10.1186/s13023-021-01830-4

来源: Springer

【 摘 要 】

BackgroundRare diseases are ailments which impose a heavy burden on individual patients and global society as a whole. The rare disease management landscape is not a smooth one—a rare disease is quite often hard to diagnose, treat, and investigate. In China, the country’s rapid economic rise and development has brought an increased focus on rare diseases. At present, there is a growing focus placed on the importance and public health priority of rare diseases and on improving awareness, definitions, and treatments.MethodsIn this work we utilized clinical data from the Shanghai HIE System to characterize the status of 33 rare diseases with effective treatment in Shanghai for the time period of 2013–2016.Results and conclusionFirst, we describe the total number of patients, year-to-year change in new patients with diagnosis in one of the target diseases and the distribution of gender and age for the top six (by patient number) diseases of the set of 33 rare diseases. Second, we describe the hospitalization burden in terms of in-hospital ratio, length of stay, and medical expenses during hospitalization. Finally, rare disease period prevalence is calculated for the rare diseases set.

【 授权许可】

CC BY