Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study. Ni, K., Chu, H., Zeng, L., Li, N., & Zhao, Y. BMJ Open, 9(7):e029314, July, 2019.
Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study [link]Paper  doi  abstract   bibtex   
Objectives There is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals’ experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context. Setting Four tertiary hospitals in Beijing, China. Participants Nineteen healthcare professionals with experience in using EHR data for clinical research participated in the study. Methods A qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach. Results The main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation. Conclusions These results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.
@article{ni_barriers_2019,
	title = {Barriers and facilitators to data quality of electronic health records used for clinical research in {China}: a qualitative study},
	volume = {9},
	issn = {2044-6055, 2044-6055},
	shorttitle = {Barriers and facilitators to data quality of electronic health records used for clinical research in {China}},
	url = {http://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2019-029314},
	doi = {10.1136/bmjopen-2019-029314},
	abstract = {Objectives
              There is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals’ experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context.
            
            
              Setting
              Four tertiary hospitals in Beijing, China.
            
            
              Participants
              Nineteen healthcare professionals with experience in using EHR data for clinical research participated in the study.
            
            
              Methods
              A qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach.
            
            
              Results
              The main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation.
            
            
              Conclusions
              These results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.},
	language = {en},
	number = {7},
	urldate = {2020-07-13},
	journal = {BMJ Open},
	author = {Ni, Kaiwen and Chu, Hongling and Zeng, Lin and Li, Nan and Zhao, Yiming},
	month = jul,
	year = {2019},
	pages = {e029314},
}

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