Underdiagnosis, misdiagnosis, and patterns of social inequality that translate into unequal access to health systems all pose barriers to identifying and recruiting diverse and representative populations into research on Alzheimer's disease and Alzheimer's disease related dementias. In response, some have turned to algorithms to identify patients living with dementia using information that is associated with this condition but that is not as specific as a diagnosis. This paper explains six ethical issues associated with the use of such algorithms including the generation of new, sensitive, identifiable medical information for research purposes without participant consent, issues of justice and equity, risk, and ethical communication. It concludes with a discussion of strategies for addressing these issues and prompting valuable research.
Keyphrases
- mild cognitive impairment
- machine learning
- end stage renal disease
- cognitive decline
- healthcare
- cognitive impairment
- newly diagnosed
- ejection fraction
- decision making
- chronic kidney disease
- deep learning
- health information
- prognostic factors
- cross sectional
- peritoneal dialysis
- patient reported outcomes
- social media
- genetic diversity
- drug induced