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Information Distortion in Electronic Health Records: A Concept Analysis
Jianan Wang1, Yihong Xu1, Rongrong Zhang1
1Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Aims:
To conceptualise information distortion in Electronic Health Records (EHRs), with the goal of providing a theoretical foundation for improving documentation practices.
Design:
A concept analysis.
Methods:
Walker and Avant's strategy for concept analysis was used. The defining attributes, antecedents and consequences were identified.
Data Sources:
A comprehensive search was conducted across PubMed, Web of Science, Embase, CINAHL and Scopus from their inception to December 2024. Studies published in English that addressed information distortion in EHRs were included.
Results:
A total of 37 studies were included. The three defining attributes were: real-world health truth, representation of reality and mismatch relationship. Antecedents were divided into five categories: people-related factors, equipment factors, regulatory factors, working environment factors and management factors. The consequences of information distortion in EHRs included threats to patient safety, poor operational performance, eroded trust, compromised research quality and health inequity.
Conclusion:
This concept analysis enhances the understanding of information distortion in EHRs and provides a foundation for further empirical validation. The findings may contribute to the development of measurement instruments and strategies to mitigate information distortion in healthcare settings.
Impact:
By undertaking a concept analysis of information distortion in EHRs, healthcare professionals will be better equipped to recognise and assess this ethical phenomenon, thereby supporting the development of targeted interventions to mitigate potential harms to healthcare practices. In addition, the clarity of this concept could provide a new angle from which to analyse the origins of flawed EHR documentation and its ripple effects across healthcare systems.
Patient Or Public Contribution:
No patient or public involvement.
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