Sentiments in the nursing notes of healthcare providers are
good indicators of whether intensive care unit (ICU) patients will survive,
according to the findings of a study conducted by researchers at the University
of Waterloo.

Hospitals typically use severity of illness scores to
predict the 30-day survival of ICU patients. These scores include lab results,
vital signs, and physiological and demographic characteristics gathered within
24 hours of admission.

“The physiological information collected in those first
24 hours of a patient’s ICU stay is really good at predicting 30-day
mortality,” said Joel Dubin, an associate professor in the Department of
Statistics and Actuarial Science and the School of Public Health and Health
Systems. “But maybe we shouldn’t just focus on the objective components of
a patient’s health status. It turns out that there is some added predictive
value to including nursing notes as opposed to excluding them.”

The researchers used the large publicly available intensive
care unit (ICU) database, Medical Information Mart for Intensive Care III,
containing patient data between 2001 and 2012. After some inclusion and
exclusion criteria were considered, such as the need for at least one nursing
note for a given patient, the dataset used in the analysis included details of
more than 27 000 patients, as well as the nursing notes. The researchers
applied an open-source sentiment analysis algorithm to extract adjectives in
the text to establish whether it is a positive, neutral or negative statement.
A multiple logistic regression model was then fit to the data to show a
relationship between the measured sentiment and 30-day mortality while
controlling for gender, type of ICU, and simplified acute physiology score.

The sentiment analysis provided a noticeable improvement for
predicting 30-day mortality in the multiple logistic regression model for this
group of patients. There was also a clear difference between the patients with
the most positive messages who experienced the highest survival rates and the
patients with the most negative messages who experienced the lowest survival
rates.

“Mortality is not the only outcome that nursing notes
could potentially predict,” said Dubin. “They might also be used to
predict readmission, or recovery from infection while in the ICU.”

Source: University
of Waterloo

Reference:  Dubin
JA, et al Sentiment in nursing notes as an indicator of out-of-hospital
mortality in intensive care patient. PLOS ONE. Published online 7 June 2018. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198687