Empirical study of Data Completeness in Electronic Health Records in China

Caihua Liu, Didar Zowghi, Amir Talaei-Khoei, Zhi Jin


Background: As a dimension of data quality in electronic health records (EHR), data completeness plays an important role in improving quality of care. Although many studies of data management focus on constructing the factors that influence data quality for the purpose of quality improvement, the constructs that are developed for interpreting factors influencing data completeness in the EHR context have received limited attention.

Methods: Based on related studies, we constructed the factors influencing EHR data completeness in a conceptual model. We then examined the proposed model by surveying clinical practitioners in China.

Results: Our results show that the data quality management literature can serve as a starting point to derive a conceptual model of factors influencing data completeness in the EHR context. This study also demonstrates that “resources” should be added as a factor that influences data completeness in EHR.

Conclusion: Our resulting conceptual model shows a substantial explanation of data completeness in EHR assessed in this study. Although the proposed relationships between the included factors were previously supported in the literature, our work provides the beginning empirical evidence that some relationships may not be always significantly supported. The possible explanation of these differences has been discussed in the present research. This study thus benefits decision makers and EHR program managers in implementing EHR as well as EHR vendors in the EHR integration by addressing data completeness issues.


Data Completeness; Electronic Health Records; Conceptual Model; China

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Citation: Liu, C., Zowghi, D., Talaei-Khoei, A., & Jin, Z. (2020). Empirical study of Data Completeness in Electronic Health Records in China. Pacific Asia Journal of the Association for Information Systems, 12(2), 102-127. https://doi.org/10.17705/1pais.12204