Ethical issues in biomedical research using electronic health records: a systematic review.
Jan PiaseckiEwa Walkiewicz-ŻarekJustyna Figas-SkrzypulecAnna KordeckaVilius DranseikaPublished in: Medicine, health care, and philosophy (2021)
Digitization of a health record changes its accessibility. An electronic health record (EHR) can be accessed by multiple authorized users. Health information from EHRs contributes to learning healthcare systems' development. The objective of this systematic review is to answer a question: What are ethical issues concerning research using EHRs in the literature? We searched Medline Ovid, Embase and Scopus for publications concerning ethical issues of research use of EHRs. We employed the constant comparative method to retrieve common ethical themes. We descriptively summarized empirical studies. The study reveals the breadth, depth, and complexity of ethical problems associated with research use of EHRs. The central ethical question that emerges from the review is how to manage access to EHRs. Managing accessibility consists of interconnected and overlapping issues: streamlining research access to EHRs, minimizing risk, engaging and educating patients, as well as ensuring trustworthy governance of EHR data. Most of the ethical problems concerning EHR-based research arise from rapid cultural change. The framing of concepts of privacy, as well as individual and public dimensions of beneficence, are changing. We are currently living in the middle of this transition period. Human emotions and mental habits, as well as laws, are lagging behind technological developments. In the medical tradition, individual patient's health has always been in the center. Transformation of healthcare care, its digitalization, seems to have some impacts on our perspective of health care ethics, research ethics and public health ethics.
Keyphrases
- electronic health record
- healthcare
- public health
- health information
- systematic review
- mental health
- clinical decision support
- decision making
- big data
- adverse drug
- social media
- global health
- endothelial cells
- ejection fraction
- end stage renal disease
- machine learning
- chronic kidney disease
- palliative care
- climate change
- deep learning
- meta analyses
- emergency department