2018
DOI: 10.1093/tbm/iby029
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OpenNotes in oncology: oncologists’ perceptions and a baseline of the content and style of their clinician notes

Abstract: Patients' ability to access their provider's clinical notes (OpenNotes) has been well received and has led to greater transparency in health systems. However, the majority of this research has occurred in primary care, and little is known about how patients' access to notes is used in oncology. This study aims to understand oncologists' perceptions of OpenNotes, while also establishing a baseline of the linguistic characteristics and patterns used in notes.Data from 13 in-depth, semistructured interviews with … Show more

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Cited by 17 publications
(26 citation statements)
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“…To conduct a semantic-based analysis, we used Language Inquiry and Word Count (LIWC) 2015, an empirically validated textual analysis program capable of translating language into quantitative metrics related to different psychological processes (affective, social, cognitive, perceptual, and others) and linguistic dimensions (parts of speech, grammar, and others) [23]. Previous studies have used LIWC 2015 for similar purposes [24][25][26][27]. For our analysis, we used the four summary variables available on LIWC 2015, which were developed and validated using previously published datasets comprising large comparison samples [23,[28][29][30][31]: (1) analytical thinking, (2) clout, (3) authenticity, and (4) emotional tone.…”
Section: Semantic Analysismentioning
confidence: 99%
“…To conduct a semantic-based analysis, we used Language Inquiry and Word Count (LIWC) 2015, an empirically validated textual analysis program capable of translating language into quantitative metrics related to different psychological processes (affective, social, cognitive, perceptual, and others) and linguistic dimensions (parts of speech, grammar, and others) [23]. Previous studies have used LIWC 2015 for similar purposes [24][25][26][27]. For our analysis, we used the four summary variables available on LIWC 2015, which were developed and validated using previously published datasets comprising large comparison samples [23,[28][29][30][31]: (1) analytical thinking, (2) clout, (3) authenticity, and (4) emotional tone.…”
Section: Semantic Analysismentioning
confidence: 99%
“…We utilized LIWC2015, a previously validated 11 , 18 application that analyzes textual data based on quantitative metrics related to psycholinguistic parameters. 19 For sentiment analysis, we used four summary variables (analytical thinking, clout, authenticity, and emotion) and three emotional tone-based variables (anxiety, anger, and sadness) to evaluate decision making.…”
Section: Methodsmentioning
confidence: 99%
“…Ideally, satisfaction scores need to be 4 and above (i.e., satisfied or extremely satisfied). While multiple studies report that patients were highly satisfied to receive access to their notes, 4,8,10,31,[38][39][40][41] these conclusions were generally based on a broad subjective question, rather than a formal tool designed to assess satisfaction. Our findings suggest that participants are not satisfied with the content of the notes (information, time to read, language used, and design).…”
Section: Satisfactionmentioning
confidence: 99%