Birth, aging, illness, and death are phenomena that accompany every individual throughout their lives. Health issues concern the vital interests of all citizens, with healthcare occupying a significant proportion of daily life. Medical security represents a priority area for people's livelihoods and social welfare. Social aging trends and public health crises such as the 2019 COVID-19 pandemic have substantially heightened attention from local governments and residents toward medical resources. In the foreseeable future, the supply and accessibility of medical resources will play an increasingly critical role in enhancing urban service capabilities, competitiveness, and people's decisions regarding residence and career choices.
However, China continues to face challenges of insufficient and unevenly distributed medical resources. Persistent public grievances over "difficulty and high costs in accessing medical care" (看病难、看病贵) have endured for years, exacerbated by severe imbalances in resource allocation across provinces and cities. To address these issues, China has implemented a series of healthcare reform measures, including social medical insurance system reforms, hospital ownership restructuring, pharmaceutical production/distribution reforms, and the promotion of hierarchical diagnosis systems. The effectiveness of these policies remains subject to empirical evaluation.
Both understanding the supply-demand dynamics of medical resources and evaluating healthcare reform outcomes necessitate micro-level big data on actual medical resource distribution. Given that the medical sector constitutes a capital- and technology-intensive public welfare undertaking, quantitative metrics alone cannot fully characterize resource allocation patterns. Additional dimensions such as hospital tier classifications (医院等级) and the distribution of medical professionals must be considered.
In response, the CnOpenData team presents Medical Information Big Data. This dataset comprises two distinct versions, each containing three sub-tables: Hospital Information, Department Information, and Physician Information. These tables encompass detailed geolocation data, hospital tiers (医院等级), department profiles, physician counts, professional resumes, specialized fields, and practitioner levels (医师级别), providing high-quality big data samples for related research. The versions differ in field coverage and data volume, enabling scholars to select according to research requirements.
Temporal Coverage
- Source A: 2019 version, April 30, 2022 version, June 2024 version
- Source B: April 30, 2022 version, June 2024 version
Version Specifications
- Sources A and B derive from distinct information channels, exhibiting overlapping yet non-identical coverage despite identical table structures;
- Regarding coverage scope: Source A includes nationwide hospitals across all tiers, while Source B primarily covers Grade IIIA and above hospitals (三甲医院), with Source A containing larger data volume;
- In field coverage: Sources A and B demonstrate complementary advantages, with Source B offering enhanced information breadth through additional fields such as hospital type (医院类型), department profiles (科室简介), and physician education/specialty/school tags (医生教育/专业/学校标签);
Data Scale
Field Demonstration
Sample Data
Hospital Information Table - Source A
Hospital Information Table - Source B
Department Information Table - Source A
Department Information Table - Source B
Physician Information Table - Source A
Physician Information Table - Source B
Data Update Frequency
Annual updates