Abstract
As the adoption of electronic health records (EHR) in primary care, ensuring high-quality data used is the premise of the quality of decision making and quality of care. Prior literature on EHR data quality has addressed dimensions and methods of data quality assessment for reuse, however, the challenges of data quality in EHR during the process of primary care from the perspective of EHR data structure have received limited attention. Looking at the EHR data structure helps improve the understanding of data quality challenges from the information pathway. Such a study assists in better designing and developing EHR systems and achieving high-quality data when using EHR. This paper thus aims at exploring challenges of data quality from the perspective of EHR data structure. For this to happen, the present study firstly investigates five main practices of primary care and describes a use case diagram of EHR systems based on these practices. Referring to the EHR systems’ functions described in the use case diagram, the study then conceptualizes the EHR data structure used in primary care, including a conceptual data model, a data flow diagram and a database schema, to better understand the data elements contained in EHR, and analyzes the changes of data elements in EHR when the practices of primary care are carried out and possible challenges of data quality in EHR. Finally, this study proposes several strategies addressing these challenges to help practitioners achieve high-quality data. Future research directions are also discussed.
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Notes
- 1.
Health Level-7 standards refer to a set of international standards for the exchange, integration, sharing, and retrieval of electronic health information [8].
- 2.
When patients have a usual source of care that serves for four essential functions, patients can be considered to receive primary care. The four functions are “providing first contact care for new health problems, comprehensive care for the majority of health problems, long-term person-focused care and care coordination across providers” [11].
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Acknowledgement
This research was supported and funded by the Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China (Grant No. 21YJC870009).
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Liu, C., Peng, G.(., Lan, C., Kong, S. (2023). Explore Data Quality Challenges Based on Data Structure of Electronic Health Records. In: Mori, H., Asahi, Y. (eds) Human Interface and the Management of Information. HCII 2023. Lecture Notes in Computer Science, vol 14015. Springer, Cham. https://doi.org/10.1007/978-3-031-35132-7_17
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