Objective:This study aims to summarize the experience of building a research data platform at Peking University First Hospital and propose pathways for constructing healthcare big data platforms in medical institutions to provide insights for the further expansion of the application of the health care big data platform and construction of smart healthcare.Methods:Hospital multi-domain data was collected through a systematic process. After data classification and cleaning, international medical standards and NLP technology were utilized to achieve data standardization and structuring. At the same time, the eCRF form, data source judgment, and mathematical calculations were optimized to ensure the data quality and application value of the scientific research data platform.Results:By carrying out the construction of a scientific research data platform, Peking University First Hospital achieved the transformation of clinical data into research data, completed data collection, pushing, integration, cleaning, and governance, and conducted health care big data research.Conclusions:It is recommended to subsequently expand the data scope, promote the transformation of clinical data into research data, enhance clinical experts' participation in prospective design and data collection, use an integrated data platform for automatic data pushing and calling, explore the application of large language models and conduct technical exploration and reserves.

Objective:This study aims to summarize the experience of building a research data platform at Peking University First Hospital and propose pathways for constructing healthcare big data platforms in medical institutions to provide insights for the further expansion of the application of the health care big data platform and construction of smart healthcare.Methods:Hospital multi-domain data was collected through a systematic process. After data classification and cleaning, international medical standards and NLP technology were utilized to achieve data standardization and structuring. At the same time, the eCRF form, data source judgment, and mathematical calculations were optimized to ensure the data quality and application value of the scientific research data platform.Results:By carrying out the construction of a scientific research data platform, Peking University First Hospital achieved the transformation of clinical data into research data, completed data collection, pushing, integration, cleaning, and governance, and conducted health care big data research.Conclusions:It is recommended to subsequently expand the data scope, promote the transformation of clinical data into research data, enhance clinical experts' participation in prospective design and data collection, use an integrated data platform for automatic data pushing and calling, explore the application of large language models and conduct technical exploration and reserves.