Nov 27, 2018
This episode features Dr Alex Chan (Department of
Psychosocial Oncology and Palliative Care, Dana-Farber Cancer
Institute, Boston, MA).
Routine assessment of many established quality indicators is nearly
impossible because the information is embedded as unstructured free
text within electronic clinical notes. A key example of
this is timely documentation of patient care preferences in
critically ill older adults. The paper demonstrates that deep
learning algorithms can be applied to assess a palliative care
quality measure endorsed by the National Quality Forum. The
deep learning algorithm analyzed clinical notes >18,000 times
faster than clinician coders (0.022 s/note vs 402 s/note).
The algorithms can analyze electronic clinical notes in a tiny
fraction of the time needed for manual review, offering
a practical option for rapid audit and feedback regarding care
preference documentation at the system and clinician level.
Full paper available from: https://journals.sagepub.com/doi/full/10.1177/0269216318810421
If you would like to record a podcast about your published (or
accepted) Palliative Medicine paper, please contact Dr Amara
Nwosu: anwosu@liverpool.ac.uk