Name
Abstract | ||
|---|---|---|
Patient–physician communication is an often overlooked yet a very important aspect of providing medical care. Positive patient–physician quality of communication within discourse has an influence on various aspects of a consultation such as a patient’s treatment adherence to prescribed medical regimen and their medical care outcome. As few reference standards exist for exploring semantics within the patient–physician setting and its effects on personalized healthcare, this paper presents a study exploring three methods to capture, model and evaluate patient–physician communication among three distinct data-sources. We introduce, compare and contrast these methods for capturing and modeling patient–physician communication quality using relatedness between discourse content within a given consultation. Results are shown for all three data-sources and communication quality scores among physicians recorded. We found our models demonstrate the ability to capture positive communication quality between both participants within a consultation. We also evaluate these findings against self-reported questionnaires highlighting various aspects of the consultation and rank communication quality among seventeen physicians who consulted amid one-hundred and thirty-two patients. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.jbi.2020.103589 | Journal of Biomedical Informatics |
Keywords | DocType | Volume |
00-01,99-00 | Journal | 112 |
ISSN | Citations | PageRank |
1532-0464 | 1 | 0.37 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Clint Cuffy | 1 | 1 | 0.37 |
| Nao Hagiwara | 2 | 1 | 0.37 |
| Scott Vrana | 3 | 1 | 0.37 |
| Bridget T. McInnes | 4 | 280 | 23.66 |