@inproceedings{polepalli_ramesh_systems_2013,
	title = {Systems for {Improving} {Electronic} {Health} {Record} {Note} {Comprehension}},
	url = {https://research.nuance.com/wp-content/uploads/2014/12/Systems-for-Improving-Electronic-Health-Record-Note-Comprehension.pdf},
	abstract = {Allowing patients access to their physicians’ notes has the potential to enhance their understanding of disease and improve medication adherence and healthcare outcomes. However, a recent study involving over ten thousand patients showed that allowing patients to read their electronic health record (EHR) notes caused confusion, especially for the vulnerable (e.g., lower literacy, lower income) groups. This finding is not surprising as EHR notes contain medical jargon that may be difficult for patients to comprehend. To improve patients’ EHR note comprehension, we are developing a biomedical natural language processing system called NoteAid (http://clinicalnotesaid.org), which translates medical jargon into consumer-oriented lay language. The current NoteAid implementations link EHR medical terms to their definitions and other related educational material. Our evaluation has shown that all NoteAid implementations improve self-rated EHR note comprehension by 23\% to 40\% of lay people.},
	booktitle = {{ACM} {SIGIR} {Workshop} on {Health} {Search} \& {Discovery}},
	author = {Polepalli Ramesh, Balaji and Yu, Hong},
	year = {2013},
}

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