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Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist
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ARTICLE IN PRESS Australasian Emergency Care xxx (2018) xxx–xxx
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Australasian Emergency Care journal homepage: www.elsevier.com/locate/auec
Research paper
Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist Bradley Partridge a,b,∗ , Julia Affleck a a b
Research Development Unit, Caboolture Hospital, Caboolture, Queensland, Australia School of Clinical Medicine, Prince Charles Hospital Northside Clinical Unit, The University of Queensland, Brisbane, Australia
a r t i c l e
i n f o
Article history: Received 29 August 2017 Received in revised form 10 November 2017 Accepted 16 November 2017 Keywords: Risk assessment Violence Brøset Violence Checklist Emergency department Security
a b s t r a c t Introduction: The Brøset Violence Checklist (BVC) is a six item checklist that rates patients according to their risk of violence in the subsequent 24 h – a score of ≥3 indicates a “high risk” of violence. This study is the first to evaluate the statistical utility of the BVC when administered by a security officer in a hospital emergency department (ED). Method: A healthcare security officer conducted BVC assessments on patients who presented to the ED of a public hospital in metropolitan South East Queensland, Australia, over a two month period. Violent/aggressive acts requiring security intervention were registered in a database. Results: 2064 ED patients were assessed on the BVC and 35 patients committed a violent/aggressive act (1.7%). BVC sensitivity was 45.7% and specificity 99.4%. At a cut-off score of BVC 3, the positive predictive value was 55.2%. Violent patients were around 71 times more likely to score BVC ≥ 3 than non-violent patients. Conclusions: The BVC has good sensitivity, specificity, and predictive value in this setting. Using the BVC may help to implement measures that mitigate the impact of violent patients in the ED, or ideally, implement procedures that prevent violence towards ED workers in the first place. © 2017 Published by Elsevier Ltd on behalf of College of Emergency Nursing Australasia.
Introduction Healthcare workers in hospital emergency departments (EDs) experience high rates of occupational violence, and ED nurses in particular often bear the brunt of abuse and aggression from patients [1–5]. In addition to the physical harms resulting from violence, aggressive acts can contribute to feelings of stress, low morale, and drive ED workers away from their profession [2]. In turn, this can adversely impact the quality of patient care in the ED [6,7]. Enacting measures to prevent or reduce violence towards ED workers is therefore an obligation that hospitals have to their staff and patients. To this end, there is considerable interest in the use of predictive risk assessment tools to identify patients that may pose a threat to healthcare workers and hospital staff while they are in the ED [8]. Structured risk assessment tools have been shown to help
∗ Corresponding author at: Research Development Unit, Caboolture Hospital, McKean Street, Caboolture, Queensland 4510, Australia. E-mail address: [email protected] (B. Partridge).
healthcare workers more accurately identify potentially violent patients when compared to unstructured clinical judgement [9], and violence assessment tools have been used in mental health and psychiatric settings for decades. However, risk assessment tools developed for use in a specific setting (or with a specific population, such as psychiatric in-patients) may not always translate well to an emergency department setting [10]. EDs are often extremely busy environments characterised by relatively rapid intake and discharging of patients with a very broad range of conditions. A recent systematic review of risk assessment tools showed that there are few tools designed specifically for use in the ED setting, and a lack of evidence for the validity and reliability for those few that do exist [11]. Nevertheless, the authors of that review suggest that some well-validated risk assessment tools could potentially be adaptable enough for use in the ED [11]. The Brøset Violence Checklist (BVC) is one of the most studied violence risk assessments in the literature and was developed for assessing risk of violence among psychiatric in-patients in the subsequent 24 h [12]. The BVC is a 6 item violence checklist that assesses the presence or absence of three “characteristics” that may indicate a risk of violence (confusion, irritability and boisterousness) and three “behaviours” (verbal
https://doi.org/10.1016/j.auec.2017.11.001 2588-994X/© 2017 Published by Elsevier Ltd on behalf of College of Emergency Nursing Australasia.
Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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threats, physical threats and attacking objects). Each item is independently scored for presence (1) or absence (0), and summed to receive a total score between 0 and 6. A score of 0 suggests that risk of violence in the next 24 h is small; 1–2 suggests that the risk of violence is moderate; and, a score of ≥3 suggest that the risk of violence is high [12]. The tool has been shown to be more reliable in predicting short-term violence than clinical opinion or intuition [13–21]. It has also demonstrated the best validity and reliability among inpatient violence risk assessments [11]. While the predictive validity of the BVC has been well reported when administered by a clinician or nurse in psychiatric facilities, there have been no studies to date indicating whether the BVC is useful in predicting acute violence or aggression in an ED setting. The overall aim of this study was to evaluate the statistical utility of the BVC when administered by a designated hospital security officer in the triage area of an ED. Method Study setting and procedure Our study evaluated a violence risk screening trial that was implemented in the ED of a metropolitan public hospital located in South-East Queensland, Australia. The hospital is a 233 bed facility with a Level 3 Emergency Department (urban district ED) according to the Australian College for Emergency Medicine delineation [22]. For a two month period between mid-July and mid-September in 2016, the hospital trialled having a Protective Services Officer (security officer) assigned specifically to the ED. Prior to this trial, the hospital had two security officers on duty to cover the entire hospital at any one time, but the trial allowed an extra officer to be located solely in the ED for 16 h per day (typically from 6 am to 10 pm – three officers rotated through 8-h shifts over the course of the trial). Patients attending the ED during these hours were assessed for their risk of violence upon presentation to triage by the ED security officer using the BVC. Each patient was assessed on the BVC on one occasion only. For each patient, the ED security officer recorded scores for, (a) each of the six BVC components, and (b) total BVC score. The officer entered all patient BVC scores (in real time) into a safety management and incident reporting database “Report Exec”. Report Exec is a database maintained and used by security officers within the hospital to log all the cases (jobs) they attend. Every case report in the Report Exec database that relates to a violent/aggressive incident attended by security officers contains narrative details of the incident and other relevant information, including pre-defined descriptive tags. These pre-defined descriptive tags are attached to case reports and include categories such as “assault”; “patient aggressive”. During the BVC trial, individual case reports were also created for every BVC risk assessment that was done.
tags unrelated to patients (for example, descriptive tags such as “open locked door” or “fire alarm”), (ii) ensure all case reports with tags a such as “assault” or “patient aggressive” were included, and (iii) remove any case reports that did not occur in the ED. Together, both authors then conducted a manual review of the remaining case reports in the database to determine whether they indicated that a violent/aggressive incident had occurred in the ED (subsequent to a BVC being conducted). We did this by examining the narrative details of the incident provided by the attending security officer, and any relevant descriptive tags attached to the case report, for details that indicated violent/aggressive behaviour. Throughout this process both authors discussed each case report and reached a consensus on the few cases in which there was not initial agreement. This produced a final list of case reports that was then reviewed by the Co-ordinator of Protective Services at the hospital to further ensure validity. For example, the following two excerpts are from case report narratives that we deemed to be indicative of a violent/aggressive incident: Example 1. “Security urgently requested to ED, male toilets. Upon arrival, patient was verbally abusive and threatening. Patient then swung his cane at Security Officers. Patient restrained by Security, standing up.” Example 2. Security was patrolling the ED when team leader informed security that a nursing staff member had been spat on, by the patient. Security found the patient. Nursing staff member attempted to talk with the patient which resulted with the patient striking the nurse. Security restrained the patient.” However, the following two excerpts are from case reports that we did not include in our sample of violent incidents: Example 3. “Patient very agitated and wanting to leave. Classified as a abscond risk. Patient not physically aggressive and compliant at the moment.” Example 4. “Patient agitated, under the influence of drugs and has a history of violence against staff. Patient settled after a while with ambulance service staff talking him through his agitation. Patient voluntary, calm and compliant. Security stood down.” As can be seen in Example 3, although security was called to assist the ED staff (and thus, the job was recorded in the Report Exec database), the patient was agitated rather than violent/aggressive, and there was no indication that the patient had committed a violent/aggressive act. In Example 4, although the patient has a history of violence and security was called to monitor, there was no indication from the case report that the patient committed a violent/aggressive act on this occasion.
Analysis Generation of dataset We extracted a dataset from the Report Exec database that included: (1) all BVC scores recorded over the two month period of the trial, and (2) all violent/aggressive incidents attended by security in the ED over the two months of the trial. In order to examine the usefulness of the BVC in predicting violent/aggressive incidents, we used patient identifiers recorded in Report Exec to cross match the two components. Other studies of the BVC have similarly generated the relevant sample of violent acts by referring to incident or “occurrence” reports of violence/aggression [19]. To generate our sample of violent/aggressive incidents, one of the authors (JA) first filtered case reports to, (i) remove any with
We extracted all the BVCs recorded during the trial period and used descriptive statistics to determine the proportion of patients who rated as, (1) low risk of violence (BVC = 0); (2) moderate risk (× = 1–2); and (3) high risk (BVC ≥ 3), and identified the most commonly observed BVC indicators. We then extracted all the case reports of violent/aggressive incidents in the ED that were attended to by security and cross matched that patient their BVC score. In this way we could assess the BVC’s specificity, sensitivity, positive predictive value, and positive likelihood ratio, at different BVC cut off points. We did the same for each individual BVC item in order to explore how single items are related to overall BVC scores and subsequent violence/aggression.
Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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Results Security officers conducted BVC assessments on 2064 patients who presented to the ED during the two month trial period. Our review of security case reports then identified that 35 patients subsequently engaged in a violent/aggressive act (“violent group”), whilst 2029 did not (“non-violent group”). The prevalence of violence for the total sample was 1.7%. Table 1 shows the proportion of BVC scores that rated as a low (BVC 0), moderate (BVC 1 and BVC 2), and high (BVC ≥ 3) risk of violence. Total BVC scores ranged from 0 (n = 1878, 90.9%), 1 (n = 119, 5.8%), 2 (n = 38, 1.8%), 3 (n = 18, 0.9%), 4 (n = 8, 0.4%), 5 (n = 2, 0.1%), and 6 (n = 1, 0.0%). In the total sample, 90.9% of people scored 0 on the BVC and only 0.2% of them (n = 4) went on to commit a violent/aggressive incident. Although a minority of the sample scored 1 or more on the BVC (9.2%, n = 186), the prevalence of violence among this group was 16.7%. Of the 29 people who had a BVC score of 3 or higher (1.4% of the total sample), classifying them as high risk of violence, the prevalence of violence was 55.2%. Not all of the BVC items appear with the same frequency within the sample, and the presence of some items are clearly more likely to be indicative of a high risk BVC scores. Table 2 shows the frequency of each individual BVC item that was identified in the sample. “Irritable” was the most frequently scored BVC item within the total sample (6.7%) and within the violent group (82.9%). Among the violent group, “Confused” (42.9%), “Boisterous” (34.3%) and “Verbally threatening” (34.3%) were also frequently observed items. Of the 186 patients who scored at least 1 on the BVC, 148 were observed to have one or more of the three “characteristic” items only (i.e. confusion, irritability and/or boisterousness) without any of the three “behaviour” items (i.e. physically threatening, verbally threatening, and/or attacking objects). A further 38 people exhibited some combination of “characteristics” and “behaviours”. Only 3 people exhibited at least one of the three “behaviours” without also exhibiting confusion, irritability and/or boisterousness (in each of these three cases, the patient was verbally threatening).
Table 1 BVC score distribution across violent and non-violent groups within the sample. BVC Score
Total % (n)
Violent group Non-violent group % (n) % (n)
Prevalence of violent incident
0 1 2 ≥3
91% (1878) 5.8% (119) 1.8% (38) 1.4% (29)
11.4% (4) 22.9% (8) 20% (7) 54.7% (16)
92.4% (1874) 5.5% (111) 1.5% (31) 0.6% (13)
0.2% 6.7% 18.4% 55.2%
Total
100% (2064)
100% (35)
100% (2029)
1.7%
Table 2 Frequency of individual BVC items observed (a) within the total sample, (b) among those who committed a violent/aggressive act, and (c) among those who scored BVC ≥ 3. BVC Items
All patients (n = 2064) % (n)
Violent patients (n = 35) % (n)
Patients who scored BVC ≥ 3 (n = 29) % (n)
Confused Irritable Boisterous Physically threatening Verbally threatening Attacking objects
3.8% (78) 6.7% (139) 1.6% (32) 0.4% (8) 1.6% (33) 0.3% (7)
42.9% (15) 82.9% (29) 34.3% (12) 17.1% (6) 34.3% (12) 11.4% (4)
65.5% (19) 100% (29) 68.9% (20) 24.1% (7) 72.4% (21) 20.7% (6)
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Patients who committed a violent act or who were rated as “high risk” (i.e. BVC ≥ 3) commonly exhibited irritability or confusion, however it should be noted that most patients who scored on these items were not “high risk”. For instance, Table 3 shows that 50% of people who were observed as confused had no other indicators of risk (i.e. they scored BVC = 1), and a further 25.6% scored on only one other indicator of risk (i.e. they scored BVC = 2). Similarly, 53.2% of people who were observed as irritable had no other indicators of risk (i.e. they scored BVC = 1), and a further 25.9% had only one other indicator of risk (i.e. they scored BVC = 2). In contrast, while there were relatively few ED patients who were physically threatening or attacking objects, nearly all of them had a high risk BVC score (87.5% and 85.7% respectively). Statistical utility of the BVC in predicting subsequent violent/aggressive acts. Using a BVC score of 3 as a cut-off point to indicate a high risk of violence, the BVC had a sensitivity of 45.7% and a specificity of 99.4% (Table 4). This indicates that in this ED setting the BVC was able to correctly identify 16 of 35 violent patients (45.7%) and 2016 of 2029 non-violent patients (99.4%). The positive Likelihood Ratio (LR+) using the ≥3 cut-off point was 71.4 indicating that violent patients were 71.4 times more likely to have a high risk BVC score (BVC ≥ 3) compared to non-violent patients. Table 4 also shows the Likelihood Ratio for lower BVC cut off points: violent patients were 30.3 times more likely to have a BVC of ≥2 than non-violent patients, and 11.6 times more likely to have a BVC of ≥1. The positive predictive value (PPV) indicates the probability that a patient will commit a violent incident in the next 24 h after a chosen cut-off score on the BVC. Using the high risk cut-off score of BVC 3, Table 4 shows that the PPV was 55.2% meaning that just over half of all patients who scored BVC ≥ 3 went on to commit a violent incident. At a cut-off point of BVC 2 the PPV was 34.3%, at a cut-off point of BVC 1 the PPV was 16.7%. Given that some BVC items are more commonly observed than others – and some items are more commonly observed within the violent group – we explored the statistical utility of each BVC item as a predictor of violence/aggression. For this analysis, we explored the data in terms of the presence/absence of that single item, regardless of whether the patient scored on other BVC items or not. The results are shown in Table 5. This yields an interesting picture of the individual BVC items and their relationship to subsequent violence. For example, patients who committed a violent/aggressive act requiring security intervention were 173 times more likely to have been “physically threatening” when being assessed on the BVC compared to nonviolent patients. Indeed, the predictive value of this item is quite high: 75% of patients who were scored on the “physically threatening” BVC item went on to commit a violent/aggressive act meaning that we would be relatively confident that a patient scoring positive on this BVC item would be subsequently violent. However, only a minority of violent patients were physically threatening upon being assessed for the BVC (17.1%), meaning that the sensitivity of this item alone is quite low. In contrast, for example, the sensitivity of “irritability” alone is high: 29 out of the 35 violent patients were observed as irritable. However, the predictive value of “irritability” alone as a marker of violence is much lower at 20.9%. That is, although nearly all violent patients were irritable, only 1 in 5 irritable patients were violent. Discussion The BVC has shown good utility when used by clinicians within psychiatric settings, and our study is the first explore the usefulness
Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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Table 3 Proportion of patients exhibiting BVC items according to their total BVC score. Confused % (n)
Irritable % (n)
Boisterous % (n)
Physically threatening % (n)
Verbally threatening % (n)
Attacking objects % (n)
BVC 1 BVC 2 BVC ≥ 3
50% (39) 25.6% (20) 24.4% (19)
53.2% (74) 25.9% (36) 20.9% (29)
9.4% (3) 28.1% (9) 62.5% (20)
0% (0) 12.5% (1) 87.5% (7)
9.1% (3) 27.3% (9) 63.6% (21)
0% (0) 14.3% (1) 85.7% (6)
Total
100% (78)
100% (139)
100% (32)
100% (8)
100% (33)
100% (7)
Table 4 Sensitivity, specificity, positive predictive value and positive likelihood ratio for different cut-off scores on the BVC in predicting a subsequent violent/aggressive act. BVC cut-off
Sensitivity
Specificity
Predictive value
Likelihood ratio
1 2 3
88.6% 65.7% 45.7%
92.4% 97.8% 99.4%
16.7% 34.3% 55.2%
11.6 30.3 71.4
Table 5 Sensitivity, specificity, positive predictive value and positive likelihood ratio for individual BVC items predicting a subsequent violent/aggressive act. Presence of BVC item
Sensitivity Specificity Predictive value Likelihood ratio
Confused Irritable Boisterous Physically threatening Verbally threatening Attacking objects
42.9% 82.9% 34.3% 17.1%
92.9% 94.6% 99.1% 99.9%
19.2% 20.9% 37.5% 75%
13.8 15.3 34.8 173.9
34.3%
98.9%
36.4%
33.1
11.4%
99.9%
57.1%
77.3
of the BVC in a hospital ED setting when administered by hospital security officers on a single occasion. Our results show that the BVC had good sensitivity, specificity and predictive value when assessing which patients may become violent towards staff in a hospital emergency department. This supports the view that some well validated violence risk tools could be adaptable enough for use in the ED [11]. In this ED setting the overall prevalence of violence was fairly low (1.7%), and just over 90% of ED patients scored 0 on the BVC. There is naturally a considerable focus on the BVC cut-off score that indicates “high risk” (i.e. BVC ≥ 3), and we found that after presenting to triage over half of all ED patients who scored BVC ≥ 3 (55.2%) subsequently committed a violent incident requiring security intervention. Our results also show that even lower BVC cut-off scores may have useful insights in this setting. Indeed, only 1 in every 470 patients in our study who scored 0 on the BVC were subsequently violent, but the risk of violence rose sharply to 1 out of every 6 patients who scored BVC ≥ 1 (16.7%), and 1 in every 3 patients who scored BVC ≥ 2 (34.3%). The sensitivity of the BVC in our study was comparable to other studies using the BVC with psychiatric patients, and the PPV in our study was even higher than in some [23]. Public hospital EDs obviously see a much broader patient profile to psychiatric facilities (where the BVC has been developed and primarily used), and this may be borne out in the relatively frequency that some BVC items appeared in our study compared to those with psychiatric in-patients. For instance, in their study of forensic psychiatric patients, Hvidhjelm et al. found that 78% of patients with BVC ≥ 1 were “physically threatening” and 74% “boisterous” [23]. In our study, irritability and confusion were by far the most commonly scored BVC items while physical threats were rare. Furthermore, although all BVC items are equally weighted in determining a patient’s overall BVC score, in our sample it is clear that the “behaviours” indicating a risk of violence are rarely exhibited
without at least one “characteristic” – however the reverse is not true. Our results show marked differences in the risk of violence between patients with low and high risk BVC scores suggesting that this information could be pre-emptively used to prime ED workers for situations that heighten the risk of occupational violence. However the statistical properties of the tool are only one aspect of usefulness and there are several practical considerations, ethical issues, and limitations of the study that should be considered when assessing overall utility. Firstly, previous studies in psychiatric facilities have had nurses or other clinicians conduct the BVC assessment and whereas in our study a professional security officer conduct the BVC assessment. It is possible that professional security officers are better able to identify behaviours that may increase the risk of patient violence, and enact preventative measures accordingly. The security officers who conducted BVC assessments in this study are all required to complete aggressive behaviour management training that includes occupational violence awareness and de-escalation. There is scope to compare whether clinicians and security officers differ in their BVC assessments, and whether this makes a difference in predicting violence. For example, it is possible that clinical staff and security staff may assess characteristics such as “confused” or “irritable” in different ways as a result of the professional training each have received. The extent to which different groups of assessors diverge in their assessments of particular BVC items would be worthwhile exploring. In practical terms, it is unclear whether the task of conducting BVC assessments is better borne by clinical or security staff when considering the performance of the ED as a whole. Although many ED staff experience occupational violence, the vast majority of patients attending EDs are not violent and in this study the vast majority of patients scored 0 on the BVC and did not commit a violent incident. BVC assessments (and recording of information) may distract clinical staff from other care related tasks and so they may benefit from having security officers do this instead. However, the time (and cost) taken for a designated security officer to administer and record the BVC for thousands of patients in a busy ED is not insignificant, and even in our study, security officers limited their collection of more detailed patient information to those who scored 1 or more on the BVC – as a result, our analysis could not explore other potentially interesting patient factors impacting violence such as gender or diagnosis. Expanding the scope of trial to incorporate assessments over a greater length of time would allow greater confidence in the generalizability of these results, as would generating a larger dataset by including other EDs. In our study, patients were assessed on the BVC once at triage whereas in other settings the BVC is intended to be used multiple times. It could be worthwhile exploring whether multiple BVC assessments in the ED add any meaningful information, or perhaps whether single assessments at other points during ED presentation are worthwhile. Some studies conduct the BVC assessment multiple times with the same patient in order to track their risk of violence over time, and as their circumstances change [19,23], but this is much more feasible with smaller samples of patients who are in residential treatment for days, weeks, or months. In contrast, the ED is a busy environment characterised by relatively rapid intake
Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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and discharging of patients and so it is not clear that multiple BVCs are always possible when many patients are not in the ED for an extended period. Our study used a database of actual violent/aggressive incidents attended to by security to generate our sample of violent incidents, which is similar to some studies that use occurrence reports of violence from clinicians in the study ward [19]. Although it is possible that this may underestimate the true number of violent incidents that occurred, it is likely that a high proportion of violent incidents in our study were captured through these security case reports given that the security officer during the trial was actually embedded within the ED. This is a novel study that is intended to serve as a platform for more concerted investigations of having security officers use violence risk assessment tools in the ED. Our results show that more than half of all ED attendees who scored “high risk” on the BVC went on to commit violent/aggressive acts in the ED, and that violent patients were more than 70 times more likely to score high on the BVC than non-violent patients. While expanded trials would help to confirm these results, our study indicates that the BVC may be adaptable to the ED when conducted by security officers. If the BVC yields useful information in this setting then EDs may be in a better position to implement measures that mitigate the impact of violent patients, or ideally, implement procedures that prevent violence towards ED workers in the first place. A useful first step would be to ensure that hospital security officers in the ED are able to readily observe patients in triage and record BVC assessments in a user friendly format. Next, it is crucial for hospital security officers in the ED to quickly liaise with clinical staff about a patient’s risk of violence on the basis of their BVC assessment – this may require regular monitoring of patients who are deemed to be high risk, and ensuring that staff who rotate into the ED are made aware of any risks. Once a BVC assessment has identified a patient as being high risk, it is incumbent upon ED security staff to ensure that other staffs in the ED are made aware of this. Ethics The study protocol was reviewed by The Prince Charles Hospital Human Research Ethics Committee (TPCH HREC) Office. It was deemed compliant with the NHMRC guidance “Ethical Considerations in Quality Assurance and Evaluation Activities” 2014 and exempt from full review (HREC/17/QPCH/112). Conflicts of interest BP and JA are employees of the Caboolture Hospital Research Development Unit. No other conflicts of interest were declared. Acknowledgements The authors would like to thank Donna Ward, Scott Trudgett, Phil Flaherty, and Brett Sell for their assistance with this study.
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References [1] Partridge B, Affleck J. Verbal abuse and physical assault in the emergency department: rates of violence, perceptions of safety, and attitudes towards security. Aust Emerg Nurs J 2017;20(3):139–45. [2] Johnston A, Abraham L, Greenslade J, Thom O, Carlstrom E, Wallis M, et al. Review article: Staff perception of the emergency department working environment: Integrative review of the literature. Emerg Med Aust 2016;28(1):7–26. [3] Behnam M, Tillotson RD, Davis SM, Hobbs GR. Violence in the emergency department: a national survey of emergency medicine residences and attending physicians. J Emerg Med 2011;40(5):565–79. [4] Gates DM, Ross CS, McQueen L. Violence against emergency department workers. J Emerg Med 2006;31(3):331–7. [5] Hyland S, Watts J, Fry M. Rates of workplace aggression in the emergency department and nurses’ perceptions of this challenging behaviour: a multimethod study. Aust Emerg Nurs J 2016;19(3):143–8. [6] Victorian Auditor General. Occupational violence against healthcare workers. Victoria, Australia: Victorian Government; 2015. [7] Gates DM, Gillespie GL, Succop P. Violence against nurses and its impact on stress and productivity. Nurs Econ 2011;29(2):59–66, quiz 7. [8] Queensland Health Occupational Violence Taskforce. Occupational Violence Prevention in Queensland Health’s Hospital and Health Services: Taskforce Report; 2016, May. [9] Ogloff J, Daffern M. The dynamic appraisal of situational aggression: an instrument to assess risk for imminent aggression in psychiatric inpatients. Behav Sci Law 2006;24:799–813. [10] Stowell K, Hughes N, Rozel J. Violence in the emergency department. Psychiatr Clin N Am 2016;39:557–66. [11] Calow N, Lewis A, Showen S, Hall N. Literature synthesis: patient aggression risk assessment tools in the emergency department. J Emerg Nurs 2016;42(1):19–24. [12] Almvik R, Woods P. The Brøset Violence Checklist (BVC) and the prediction of inpatient violence: some preliminary results. Psychiatr Care 1998;5(6):208–11. [13] Abderhalden C, Needham I, Miserez B, Almvik R, Dassen T, Haug HJ, et al. Predicting inpatient violence in acute psychiatric wards using the Broset-Violence-Checklist: a multicentre prospective cohort study. J Psychiatr Ment Health Nurs 2004;11(4):422–7. [14] Abderhalden C, Needham I, Dassen T, Halfens R, Haug HJ, Fischer J. Predicting inpatient violence using an extended version of the Broset-Violence-Checklist: instrument development and clinical application. BMC Psychiatr 2006;6:17. [15] Abderhalden C, Needham I, Dassen T, Halfens R, Haug H-J, Fischer JE. Structured risk assessment and violence in acute psychiatric wards: randomised controlled trial. Br J Psychiatr 2008;193(1):44–50. [16] Almvik R, Woods P, Rasmussen K. The Brøset Violence Checklist sensitivity, specificity, and interrater reliability. J Interpers Violence 2000;15(12):1284–96. [17] Almvik R, Woods P, Rasmussen K. Assessing risk for imminent violence in the elderly: the Broset Violence Checklist. Int J Geriatr Psychiatry 2007;22(9):862–7. [18] Woods P, Ashley C, Kayto D, Heusdens C. Piloting violence and incident reporting measures on one acute mental health inpatient unit. Issues Ment Health Nurs 2008;29(5):455–69. [19] Clarke DE, Brown AM, Griffith P. The Brøset Violence Checklist: clinical utility in a secure psychiatric intensive care setting. J Psychiatr Ment Health Nurs 2010;17(7):614–20. [20] Vaaler AE, Iversen VC, Morken G, Flovig JC, Palmstierna T, Linaker OM. Short-term prediction of threatening and violent behaviour in an Acute Psychiatric Intensive Care Unit based on patient and environment characteristics. BMC Psychiatr 2011;11:44. [21] Bjorkdahl A, Olsson D, Palmstierna T. Nurses’ short-term prediction of violence in acute psychiatric intensive care. Acta Psychiatr Scand 2006;113(3):224–9. [22] Australasian College for Emergency. Statement on the delineation of emergency departments. Available from: https://acem.org.au/getattachment/ 541e19cd-6e5e-48b2-93f6-7416c43ac13a/Statement-on-the-Delineation-ofEmergency-Departme.aspx [9.11.17]. [23] Hvidhjelm J, Sestoft D, Skovgaard LT, Bue Bjorner J. Sensitivity and specificity of the Broset Violence Checklist as predictor of violence in forensic psychiatry. Nord J Psychiatr 2014;68(8):536–42.
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Research paper
Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist Bradley Partridge a,b,∗ , Julia Affleck a a b
Research Development Unit, Caboolture Hospital, Caboolture, Queensland, Australia School of Clinical Medicine, Prince Charles Hospital Northside Clinical Unit, The University of Queensland, Brisbane, Australia
a r t i c l e
i n f o
Article history: Received 29 August 2017 Received in revised form 10 November 2017 Accepted 16 November 2017 Keywords: Risk assessment Violence Brøset Violence Checklist Emergency department Security
a b s t r a c t Introduction: The Brøset Violence Checklist (BVC) is a six item checklist that rates patients according to their risk of violence in the subsequent 24 h – a score of ≥3 indicates a “high risk” of violence. This study is the first to evaluate the statistical utility of the BVC when administered by a security officer in a hospital emergency department (ED). Method: A healthcare security officer conducted BVC assessments on patients who presented to the ED of a public hospital in metropolitan South East Queensland, Australia, over a two month period. Violent/aggressive acts requiring security intervention were registered in a database. Results: 2064 ED patients were assessed on the BVC and 35 patients committed a violent/aggressive act (1.7%). BVC sensitivity was 45.7% and specificity 99.4%. At a cut-off score of BVC 3, the positive predictive value was 55.2%. Violent patients were around 71 times more likely to score BVC ≥ 3 than non-violent patients. Conclusions: The BVC has good sensitivity, specificity, and predictive value in this setting. Using the BVC may help to implement measures that mitigate the impact of violent patients in the ED, or ideally, implement procedures that prevent violence towards ED workers in the first place. © 2017 Published by Elsevier Ltd on behalf of College of Emergency Nursing Australasia.
Introduction Healthcare workers in hospital emergency departments (EDs) experience high rates of occupational violence, and ED nurses in particular often bear the brunt of abuse and aggression from patients [1–5]. In addition to the physical harms resulting from violence, aggressive acts can contribute to feelings of stress, low morale, and drive ED workers away from their profession [2]. In turn, this can adversely impact the quality of patient care in the ED [6,7]. Enacting measures to prevent or reduce violence towards ED workers is therefore an obligation that hospitals have to their staff and patients. To this end, there is considerable interest in the use of predictive risk assessment tools to identify patients that may pose a threat to healthcare workers and hospital staff while they are in the ED [8]. Structured risk assessment tools have been shown to help
∗ Corresponding author at: Research Development Unit, Caboolture Hospital, McKean Street, Caboolture, Queensland 4510, Australia. E-mail address: [email protected] (B. Partridge).
healthcare workers more accurately identify potentially violent patients when compared to unstructured clinical judgement [9], and violence assessment tools have been used in mental health and psychiatric settings for decades. However, risk assessment tools developed for use in a specific setting (or with a specific population, such as psychiatric in-patients) may not always translate well to an emergency department setting [10]. EDs are often extremely busy environments characterised by relatively rapid intake and discharging of patients with a very broad range of conditions. A recent systematic review of risk assessment tools showed that there are few tools designed specifically for use in the ED setting, and a lack of evidence for the validity and reliability for those few that do exist [11]. Nevertheless, the authors of that review suggest that some well-validated risk assessment tools could potentially be adaptable enough for use in the ED [11]. The Brøset Violence Checklist (BVC) is one of the most studied violence risk assessments in the literature and was developed for assessing risk of violence among psychiatric in-patients in the subsequent 24 h [12]. The BVC is a 6 item violence checklist that assesses the presence or absence of three “characteristics” that may indicate a risk of violence (confusion, irritability and boisterousness) and three “behaviours” (verbal
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Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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threats, physical threats and attacking objects). Each item is independently scored for presence (1) or absence (0), and summed to receive a total score between 0 and 6. A score of 0 suggests that risk of violence in the next 24 h is small; 1–2 suggests that the risk of violence is moderate; and, a score of ≥3 suggest that the risk of violence is high [12]. The tool has been shown to be more reliable in predicting short-term violence than clinical opinion or intuition [13–21]. It has also demonstrated the best validity and reliability among inpatient violence risk assessments [11]. While the predictive validity of the BVC has been well reported when administered by a clinician or nurse in psychiatric facilities, there have been no studies to date indicating whether the BVC is useful in predicting acute violence or aggression in an ED setting. The overall aim of this study was to evaluate the statistical utility of the BVC when administered by a designated hospital security officer in the triage area of an ED. Method Study setting and procedure Our study evaluated a violence risk screening trial that was implemented in the ED of a metropolitan public hospital located in South-East Queensland, Australia. The hospital is a 233 bed facility with a Level 3 Emergency Department (urban district ED) according to the Australian College for Emergency Medicine delineation [22]. For a two month period between mid-July and mid-September in 2016, the hospital trialled having a Protective Services Officer (security officer) assigned specifically to the ED. Prior to this trial, the hospital had two security officers on duty to cover the entire hospital at any one time, but the trial allowed an extra officer to be located solely in the ED for 16 h per day (typically from 6 am to 10 pm – three officers rotated through 8-h shifts over the course of the trial). Patients attending the ED during these hours were assessed for their risk of violence upon presentation to triage by the ED security officer using the BVC. Each patient was assessed on the BVC on one occasion only. For each patient, the ED security officer recorded scores for, (a) each of the six BVC components, and (b) total BVC score. The officer entered all patient BVC scores (in real time) into a safety management and incident reporting database “Report Exec”. Report Exec is a database maintained and used by security officers within the hospital to log all the cases (jobs) they attend. Every case report in the Report Exec database that relates to a violent/aggressive incident attended by security officers contains narrative details of the incident and other relevant information, including pre-defined descriptive tags. These pre-defined descriptive tags are attached to case reports and include categories such as “assault”; “patient aggressive”. During the BVC trial, individual case reports were also created for every BVC risk assessment that was done.
tags unrelated to patients (for example, descriptive tags such as “open locked door” or “fire alarm”), (ii) ensure all case reports with tags a such as “assault” or “patient aggressive” were included, and (iii) remove any case reports that did not occur in the ED. Together, both authors then conducted a manual review of the remaining case reports in the database to determine whether they indicated that a violent/aggressive incident had occurred in the ED (subsequent to a BVC being conducted). We did this by examining the narrative details of the incident provided by the attending security officer, and any relevant descriptive tags attached to the case report, for details that indicated violent/aggressive behaviour. Throughout this process both authors discussed each case report and reached a consensus on the few cases in which there was not initial agreement. This produced a final list of case reports that was then reviewed by the Co-ordinator of Protective Services at the hospital to further ensure validity. For example, the following two excerpts are from case report narratives that we deemed to be indicative of a violent/aggressive incident: Example 1. “Security urgently requested to ED, male toilets. Upon arrival, patient was verbally abusive and threatening. Patient then swung his cane at Security Officers. Patient restrained by Security, standing up.” Example 2. Security was patrolling the ED when team leader informed security that a nursing staff member had been spat on, by the patient. Security found the patient. Nursing staff member attempted to talk with the patient which resulted with the patient striking the nurse. Security restrained the patient.” However, the following two excerpts are from case reports that we did not include in our sample of violent incidents: Example 3. “Patient very agitated and wanting to leave. Classified as a abscond risk. Patient not physically aggressive and compliant at the moment.” Example 4. “Patient agitated, under the influence of drugs and has a history of violence against staff. Patient settled after a while with ambulance service staff talking him through his agitation. Patient voluntary, calm and compliant. Security stood down.” As can be seen in Example 3, although security was called to assist the ED staff (and thus, the job was recorded in the Report Exec database), the patient was agitated rather than violent/aggressive, and there was no indication that the patient had committed a violent/aggressive act. In Example 4, although the patient has a history of violence and security was called to monitor, there was no indication from the case report that the patient committed a violent/aggressive act on this occasion.
Analysis Generation of dataset We extracted a dataset from the Report Exec database that included: (1) all BVC scores recorded over the two month period of the trial, and (2) all violent/aggressive incidents attended by security in the ED over the two months of the trial. In order to examine the usefulness of the BVC in predicting violent/aggressive incidents, we used patient identifiers recorded in Report Exec to cross match the two components. Other studies of the BVC have similarly generated the relevant sample of violent acts by referring to incident or “occurrence” reports of violence/aggression [19]. To generate our sample of violent/aggressive incidents, one of the authors (JA) first filtered case reports to, (i) remove any with
We extracted all the BVCs recorded during the trial period and used descriptive statistics to determine the proportion of patients who rated as, (1) low risk of violence (BVC = 0); (2) moderate risk (× = 1–2); and (3) high risk (BVC ≥ 3), and identified the most commonly observed BVC indicators. We then extracted all the case reports of violent/aggressive incidents in the ED that were attended to by security and cross matched that patient their BVC score. In this way we could assess the BVC’s specificity, sensitivity, positive predictive value, and positive likelihood ratio, at different BVC cut off points. We did the same for each individual BVC item in order to explore how single items are related to overall BVC scores and subsequent violence/aggression.
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Results Security officers conducted BVC assessments on 2064 patients who presented to the ED during the two month trial period. Our review of security case reports then identified that 35 patients subsequently engaged in a violent/aggressive act (“violent group”), whilst 2029 did not (“non-violent group”). The prevalence of violence for the total sample was 1.7%. Table 1 shows the proportion of BVC scores that rated as a low (BVC 0), moderate (BVC 1 and BVC 2), and high (BVC ≥ 3) risk of violence. Total BVC scores ranged from 0 (n = 1878, 90.9%), 1 (n = 119, 5.8%), 2 (n = 38, 1.8%), 3 (n = 18, 0.9%), 4 (n = 8, 0.4%), 5 (n = 2, 0.1%), and 6 (n = 1, 0.0%). In the total sample, 90.9% of people scored 0 on the BVC and only 0.2% of them (n = 4) went on to commit a violent/aggressive incident. Although a minority of the sample scored 1 or more on the BVC (9.2%, n = 186), the prevalence of violence among this group was 16.7%. Of the 29 people who had a BVC score of 3 or higher (1.4% of the total sample), classifying them as high risk of violence, the prevalence of violence was 55.2%. Not all of the BVC items appear with the same frequency within the sample, and the presence of some items are clearly more likely to be indicative of a high risk BVC scores. Table 2 shows the frequency of each individual BVC item that was identified in the sample. “Irritable” was the most frequently scored BVC item within the total sample (6.7%) and within the violent group (82.9%). Among the violent group, “Confused” (42.9%), “Boisterous” (34.3%) and “Verbally threatening” (34.3%) were also frequently observed items. Of the 186 patients who scored at least 1 on the BVC, 148 were observed to have one or more of the three “characteristic” items only (i.e. confusion, irritability and/or boisterousness) without any of the three “behaviour” items (i.e. physically threatening, verbally threatening, and/or attacking objects). A further 38 people exhibited some combination of “characteristics” and “behaviours”. Only 3 people exhibited at least one of the three “behaviours” without also exhibiting confusion, irritability and/or boisterousness (in each of these three cases, the patient was verbally threatening).
Table 1 BVC score distribution across violent and non-violent groups within the sample. BVC Score
Total % (n)
Violent group Non-violent group % (n) % (n)
Prevalence of violent incident
0 1 2 ≥3
91% (1878) 5.8% (119) 1.8% (38) 1.4% (29)
11.4% (4) 22.9% (8) 20% (7) 54.7% (16)
92.4% (1874) 5.5% (111) 1.5% (31) 0.6% (13)
0.2% 6.7% 18.4% 55.2%
Total
100% (2064)
100% (35)
100% (2029)
1.7%
Table 2 Frequency of individual BVC items observed (a) within the total sample, (b) among those who committed a violent/aggressive act, and (c) among those who scored BVC ≥ 3. BVC Items
All patients (n = 2064) % (n)
Violent patients (n = 35) % (n)
Patients who scored BVC ≥ 3 (n = 29) % (n)
Confused Irritable Boisterous Physically threatening Verbally threatening Attacking objects
3.8% (78) 6.7% (139) 1.6% (32) 0.4% (8) 1.6% (33) 0.3% (7)
42.9% (15) 82.9% (29) 34.3% (12) 17.1% (6) 34.3% (12) 11.4% (4)
65.5% (19) 100% (29) 68.9% (20) 24.1% (7) 72.4% (21) 20.7% (6)
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Patients who committed a violent act or who were rated as “high risk” (i.e. BVC ≥ 3) commonly exhibited irritability or confusion, however it should be noted that most patients who scored on these items were not “high risk”. For instance, Table 3 shows that 50% of people who were observed as confused had no other indicators of risk (i.e. they scored BVC = 1), and a further 25.6% scored on only one other indicator of risk (i.e. they scored BVC = 2). Similarly, 53.2% of people who were observed as irritable had no other indicators of risk (i.e. they scored BVC = 1), and a further 25.9% had only one other indicator of risk (i.e. they scored BVC = 2). In contrast, while there were relatively few ED patients who were physically threatening or attacking objects, nearly all of them had a high risk BVC score (87.5% and 85.7% respectively). Statistical utility of the BVC in predicting subsequent violent/aggressive acts. Using a BVC score of 3 as a cut-off point to indicate a high risk of violence, the BVC had a sensitivity of 45.7% and a specificity of 99.4% (Table 4). This indicates that in this ED setting the BVC was able to correctly identify 16 of 35 violent patients (45.7%) and 2016 of 2029 non-violent patients (99.4%). The positive Likelihood Ratio (LR+) using the ≥3 cut-off point was 71.4 indicating that violent patients were 71.4 times more likely to have a high risk BVC score (BVC ≥ 3) compared to non-violent patients. Table 4 also shows the Likelihood Ratio for lower BVC cut off points: violent patients were 30.3 times more likely to have a BVC of ≥2 than non-violent patients, and 11.6 times more likely to have a BVC of ≥1. The positive predictive value (PPV) indicates the probability that a patient will commit a violent incident in the next 24 h after a chosen cut-off score on the BVC. Using the high risk cut-off score of BVC 3, Table 4 shows that the PPV was 55.2% meaning that just over half of all patients who scored BVC ≥ 3 went on to commit a violent incident. At a cut-off point of BVC 2 the PPV was 34.3%, at a cut-off point of BVC 1 the PPV was 16.7%. Given that some BVC items are more commonly observed than others – and some items are more commonly observed within the violent group – we explored the statistical utility of each BVC item as a predictor of violence/aggression. For this analysis, we explored the data in terms of the presence/absence of that single item, regardless of whether the patient scored on other BVC items or not. The results are shown in Table 5. This yields an interesting picture of the individual BVC items and their relationship to subsequent violence. For example, patients who committed a violent/aggressive act requiring security intervention were 173 times more likely to have been “physically threatening” when being assessed on the BVC compared to nonviolent patients. Indeed, the predictive value of this item is quite high: 75% of patients who were scored on the “physically threatening” BVC item went on to commit a violent/aggressive act meaning that we would be relatively confident that a patient scoring positive on this BVC item would be subsequently violent. However, only a minority of violent patients were physically threatening upon being assessed for the BVC (17.1%), meaning that the sensitivity of this item alone is quite low. In contrast, for example, the sensitivity of “irritability” alone is high: 29 out of the 35 violent patients were observed as irritable. However, the predictive value of “irritability” alone as a marker of violence is much lower at 20.9%. That is, although nearly all violent patients were irritable, only 1 in 5 irritable patients were violent. Discussion The BVC has shown good utility when used by clinicians within psychiatric settings, and our study is the first explore the usefulness
Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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Table 3 Proportion of patients exhibiting BVC items according to their total BVC score. Confused % (n)
Irritable % (n)
Boisterous % (n)
Physically threatening % (n)
Verbally threatening % (n)
Attacking objects % (n)
BVC 1 BVC 2 BVC ≥ 3
50% (39) 25.6% (20) 24.4% (19)
53.2% (74) 25.9% (36) 20.9% (29)
9.4% (3) 28.1% (9) 62.5% (20)
0% (0) 12.5% (1) 87.5% (7)
9.1% (3) 27.3% (9) 63.6% (21)
0% (0) 14.3% (1) 85.7% (6)
Total
100% (78)
100% (139)
100% (32)
100% (8)
100% (33)
100% (7)
Table 4 Sensitivity, specificity, positive predictive value and positive likelihood ratio for different cut-off scores on the BVC in predicting a subsequent violent/aggressive act. BVC cut-off
Sensitivity
Specificity
Predictive value
Likelihood ratio
1 2 3
88.6% 65.7% 45.7%
92.4% 97.8% 99.4%
16.7% 34.3% 55.2%
11.6 30.3 71.4
Table 5 Sensitivity, specificity, positive predictive value and positive likelihood ratio for individual BVC items predicting a subsequent violent/aggressive act. Presence of BVC item
Sensitivity Specificity Predictive value Likelihood ratio
Confused Irritable Boisterous Physically threatening Verbally threatening Attacking objects
42.9% 82.9% 34.3% 17.1%
92.9% 94.6% 99.1% 99.9%
19.2% 20.9% 37.5% 75%
13.8 15.3 34.8 173.9
34.3%
98.9%
36.4%
33.1
11.4%
99.9%
57.1%
77.3
of the BVC in a hospital ED setting when administered by hospital security officers on a single occasion. Our results show that the BVC had good sensitivity, specificity and predictive value when assessing which patients may become violent towards staff in a hospital emergency department. This supports the view that some well validated violence risk tools could be adaptable enough for use in the ED [11]. In this ED setting the overall prevalence of violence was fairly low (1.7%), and just over 90% of ED patients scored 0 on the BVC. There is naturally a considerable focus on the BVC cut-off score that indicates “high risk” (i.e. BVC ≥ 3), and we found that after presenting to triage over half of all ED patients who scored BVC ≥ 3 (55.2%) subsequently committed a violent incident requiring security intervention. Our results also show that even lower BVC cut-off scores may have useful insights in this setting. Indeed, only 1 in every 470 patients in our study who scored 0 on the BVC were subsequently violent, but the risk of violence rose sharply to 1 out of every 6 patients who scored BVC ≥ 1 (16.7%), and 1 in every 3 patients who scored BVC ≥ 2 (34.3%). The sensitivity of the BVC in our study was comparable to other studies using the BVC with psychiatric patients, and the PPV in our study was even higher than in some [23]. Public hospital EDs obviously see a much broader patient profile to psychiatric facilities (where the BVC has been developed and primarily used), and this may be borne out in the relatively frequency that some BVC items appeared in our study compared to those with psychiatric in-patients. For instance, in their study of forensic psychiatric patients, Hvidhjelm et al. found that 78% of patients with BVC ≥ 1 were “physically threatening” and 74% “boisterous” [23]. In our study, irritability and confusion were by far the most commonly scored BVC items while physical threats were rare. Furthermore, although all BVC items are equally weighted in determining a patient’s overall BVC score, in our sample it is clear that the “behaviours” indicating a risk of violence are rarely exhibited
without at least one “characteristic” – however the reverse is not true. Our results show marked differences in the risk of violence between patients with low and high risk BVC scores suggesting that this information could be pre-emptively used to prime ED workers for situations that heighten the risk of occupational violence. However the statistical properties of the tool are only one aspect of usefulness and there are several practical considerations, ethical issues, and limitations of the study that should be considered when assessing overall utility. Firstly, previous studies in psychiatric facilities have had nurses or other clinicians conduct the BVC assessment and whereas in our study a professional security officer conduct the BVC assessment. It is possible that professional security officers are better able to identify behaviours that may increase the risk of patient violence, and enact preventative measures accordingly. The security officers who conducted BVC assessments in this study are all required to complete aggressive behaviour management training that includes occupational violence awareness and de-escalation. There is scope to compare whether clinicians and security officers differ in their BVC assessments, and whether this makes a difference in predicting violence. For example, it is possible that clinical staff and security staff may assess characteristics such as “confused” or “irritable” in different ways as a result of the professional training each have received. The extent to which different groups of assessors diverge in their assessments of particular BVC items would be worthwhile exploring. In practical terms, it is unclear whether the task of conducting BVC assessments is better borne by clinical or security staff when considering the performance of the ED as a whole. Although many ED staff experience occupational violence, the vast majority of patients attending EDs are not violent and in this study the vast majority of patients scored 0 on the BVC and did not commit a violent incident. BVC assessments (and recording of information) may distract clinical staff from other care related tasks and so they may benefit from having security officers do this instead. However, the time (and cost) taken for a designated security officer to administer and record the BVC for thousands of patients in a busy ED is not insignificant, and even in our study, security officers limited their collection of more detailed patient information to those who scored 1 or more on the BVC – as a result, our analysis could not explore other potentially interesting patient factors impacting violence such as gender or diagnosis. Expanding the scope of trial to incorporate assessments over a greater length of time would allow greater confidence in the generalizability of these results, as would generating a larger dataset by including other EDs. In our study, patients were assessed on the BVC once at triage whereas in other settings the BVC is intended to be used multiple times. It could be worthwhile exploring whether multiple BVC assessments in the ED add any meaningful information, or perhaps whether single assessments at other points during ED presentation are worthwhile. Some studies conduct the BVC assessment multiple times with the same patient in order to track their risk of violence over time, and as their circumstances change [19,23], but this is much more feasible with smaller samples of patients who are in residential treatment for days, weeks, or months. In contrast, the ED is a busy environment characterised by relatively rapid intake
Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001
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and discharging of patients and so it is not clear that multiple BVCs are always possible when many patients are not in the ED for an extended period. Our study used a database of actual violent/aggressive incidents attended to by security to generate our sample of violent incidents, which is similar to some studies that use occurrence reports of violence from clinicians in the study ward [19]. Although it is possible that this may underestimate the true number of violent incidents that occurred, it is likely that a high proportion of violent incidents in our study were captured through these security case reports given that the security officer during the trial was actually embedded within the ED. This is a novel study that is intended to serve as a platform for more concerted investigations of having security officers use violence risk assessment tools in the ED. Our results show that more than half of all ED attendees who scored “high risk” on the BVC went on to commit violent/aggressive acts in the ED, and that violent patients were more than 70 times more likely to score high on the BVC than non-violent patients. While expanded trials would help to confirm these results, our study indicates that the BVC may be adaptable to the ED when conducted by security officers. If the BVC yields useful information in this setting then EDs may be in a better position to implement measures that mitigate the impact of violent patients, or ideally, implement procedures that prevent violence towards ED workers in the first place. A useful first step would be to ensure that hospital security officers in the ED are able to readily observe patients in triage and record BVC assessments in a user friendly format. Next, it is crucial for hospital security officers in the ED to quickly liaise with clinical staff about a patient’s risk of violence on the basis of their BVC assessment – this may require regular monitoring of patients who are deemed to be high risk, and ensuring that staff who rotate into the ED are made aware of any risks. Once a BVC assessment has identified a patient as being high risk, it is incumbent upon ED security staff to ensure that other staffs in the ED are made aware of this. Ethics The study protocol was reviewed by The Prince Charles Hospital Human Research Ethics Committee (TPCH HREC) Office. It was deemed compliant with the NHMRC guidance “Ethical Considerations in Quality Assurance and Evaluation Activities” 2014 and exempt from full review (HREC/17/QPCH/112). Conflicts of interest BP and JA are employees of the Caboolture Hospital Research Development Unit. No other conflicts of interest were declared. Acknowledgements The authors would like to thank Donna Ward, Scott Trudgett, Phil Flaherty, and Brett Sell for their assistance with this study.
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Please cite this article in press as: Partridge B, Affleck J. Predicting aggressive patient behaviour in a hospital emergency department: An empirical study of security officers using the Brøset Violence Checklist. Australasian Emergency Care (2018), https://doi.org/10.1016/j.auec.2017.11.001