(C-194) Methodology and Framework for Estimating the Burden of Rare Diseases Using Regional Healthcare Data

Background: Rare diseases remain a formidable public health challenge. However, rare disease epidemiological data, which are essential for timely diagnosis, drug development, and treatment, remain limited, especially in China.

Objectives: To explore and evaluate the epidemiological characteristics, treatment patterns, and economic burden of rare diseases in Beijing by utilizing regional healthcare data, and to construct a framework for estimating the rare disease burden, which could provide a basis for improving the prevention and treatment of rare disease patients.

Methods: The database of the Beijing Municipal Health Commission contains inpatient and outpatient case records from 2017 to 2023, providing a data foundation for analyzing the disease and economic burden of rare diseases in Beijing. A framework was developed to calculate the burden of rare diseases using regional medical data, which includes steps such as patient identification, determining new and prevalent cases, demographic characteristic grouping, comorbidity analysis, medication usage evaluation, and economic burden assessment.

Results: Data sources included outpatient records from 30 hospitals, admission records from over 300 hospitals, and inpatient records from 30 hospitals. Patient identification was conducted using the International Classification of Diseases, 10th Revision (ICD-10), along with Chinese diagnostic standards, and was verified by specialized physicians. Due to data volume limitations, the calculation of disease burden involved four steps: data collection and organization, calculation of disease-specific rates from 30 hospitals, overall dermatology rates, construction of regression models to predict the total number of cases in the city, and calculation of incidence and prevalence rates. Economic burden metrics included the average annual visit frequency per capita, average annual expenditure per capita, daily average hospitalization costs per patient, and average annual medication costs per capita. Both disease and economic burdens were stratified by sex and age.

Conclusions: Regional healthcare data provides data support for epidemiological studies of rare diseases. However, variations in data size and structure may introduce challenges in estimating disease burden. This study developed a framework for calculating the burden of rare diseases and associated economic costs using regional data from Beijing, offering methodological insights for future rare disease research.