Dr. Son Chae Kim helps design aggression assessment tool
Dr. Son Chae Kim, PLNU professor of nursing, along with Kristyn Ideker, a registered nurse at Scripps Memorial Hospital, led a study of more than 2,000 patients admitted to an acute care hospital over a five-month period and developed a new aggression tool to predict violent patients in medical and surgical wards.
Using the specially designed risk assessment tool was an effective way of identifying violent hospital patients in medical and surgical units, according to a study in the November issue of the Journal of Advanced Nursing.
"Patient violence occurs in all healthcare settings and, although a number of tools have been developed for use in psychiatric units, there is a lack of brief screening tools for medical and surgical settings," said Kim. "That is why we developed the ten-point Aggressive Behaviour Risk Assessment Tool (ABRAT), which was completed within 24 hours of admission and appears to provide a promising tool for predicting which patients will become violent during their hospital stay. For example less than one per cent of patients with an ABRAT rating of zero became violent, compared with 41 percent of those with a rating of two or more."
Key findings of the study included:
- Fifty-six of the 2,063 patients (three percent) were involved in one or more of the violent incidents. These included 35 episodes of verbal abuse, 26 physical attacks, 15 threats of physical attack, 12 incidents where an emergency call went out to security personnel and three cases of sexual harassment.
- Less than one percent of the patients with an ABRAT score of zero became violent, compared with eight percent of the patients with a score of one and 41 percent of the patients with a score of two or more.
- Half of the violent incidents involved patients aged over 70, despite the fact that they only made up 40 percent of the patients studied. Males, who made up 48 percent of the patients studied were almost twice as likely to become violent as females (64 percent versus 34 percent). The researchers quantified the ability of the ABRAT to predict violence in the medical and surgical settings by using the predictive value, where 100 percent represents a perfect prediction.
- The negative predictive value of an ABRAT score of zero - the proportion of subjects with negative test results who were correctly classified to represent a low risk of violence – was greater than 99 percent.
- The positive predictive value of an ABRAT score of two or more - the proportion of subjects with positive test results who were correctly classified to represent a high risk of violence - was 41 percent.
- The five most common predictors of violence were: confusion/cognitive impairment, anxiety, agitation, shouting/demanding and a history of physical aggression.
Nurses who had undergone a training course in use of the tool collected the data from patients admitted to six different medical-surgical units.
"The results from this study indicate that the ten-item ABRAT could be useful in identifying potentially violent patients in medical-surgical units, with acceptable accuracy and agreement between users," said Kim. "Further studies are now needed to see whether the use of the ABRAT can actually reduce violence in clinical settings."