Achieving Data Completeness in Electronic Medical Records: A Conceptual Model and Hypotheses Development
Conference paper
Caihua Liu, Didar Zowghi, Amir Talaei-Khoei and Jay Daniel 2018. Achieving Data Completeness in Electronic Medical Records: A Conceptual Model and Hypotheses Development. University of Hawaii. https://doi.org/10.24251/hicss.2018.357
| Authors | Caihua Liu, Didar Zowghi, Amir Talaei-Khoei and Jay Daniel |
|---|---|
| Type | Conference paper |
| Abstract | This paper aims at proposing a conceptual model of achieving data completeness in electronic medical records (EMR). For this to happen, firstly, we draw on the model of factors influencing data quality management to construct our conceptual model. Secondly, we develop hypotheses of relationships between influencing factors for data completeness and mediators for achieving data completeness in EMR based on the literature. Our conceptual model extends the prior model for factors influencing data quality management by adding a new factor and exploring the relationships between the influencing factors within the context of data completeness in EMR. The proposed conceptual model and the presented hypotheses once empirically validated will be the basis for the development of tools and techniques for achieving data completeness in EMR. |
| Keywords | Big data; Conceptual model; Data completeness; Data quality; Electronic medical records; Healthcare data |
| Year | 2018 |
| Journal | Proceedings of the 51st Hawaii International Conference on System Sciences |
| Publisher | University of Hawaii |
| Digital Object Identifier (DOI) | https://doi.org/10.24251/hicss.2018.357 |
| Web address (URL) | http://hdl.handle.net/10545/622725 |
| hdl:10545/622725 | |
| ISBN | 9780998133119 |
| File | File Access Level Open |
| File | File Access Level Open |
| Publication dates | 2018 |
| Publication process dates | |
| Deposited | 22 May 2018, 11:06 |
| Contributors | University of Technology Sydney and University of Nevada |
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