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Assessing Elopement Risk with the BEAT
Brad Booth, MD, FRCPCSteve Michel, Andrew WatsonMathieu Dufour, MD, FRCPC
September 7, 2018
RANZCP Faculty Forensic ConferenceSydney, Australia
A bit about me… Forensics in Canada including NCR/Fitness Run sex offender unit Some teaching/admin Was clinical director in charge of ~120
forensic beds in two centres
Learning objectives
Review literature on psychiatry elopement/AWOLs
Review tools available to assist in reducing AWOLs
Discuss the BEAT
Can we predict AWOLS?
* Cute pic idea by Phil Resnick
Thoughts?
Can we predict the future?
Prediction of Violence
Accurate prediction of rare events is very difficult: Homicide rate is 2/100,000 population in
Canada Suicide rate is 12/100,000 population in
Canada
Any ability to accurately these rare events usually comes with high false positives
Assume That 1 out of 1000 persons kill Screening a city of 100,000 people will
yield 100 killers There is highly accurate test to
differentiate killers from non-killers at 95% level of accuracy
95/100 killers would be accurately identified
Of the 99,900 non-killers, there would be 4,995 non-killers identified as k illers Monahan, 1981
Risk Assessment
We cannot predict elopement, we can only…Assess the potential risk
Manage the potential risk
Risk Assessment
Important characteristics of Potential Elopement…. Likelihood ImminenceMagnitude – ie what will happen if elope Frequency
How do we assess risk?
Methods of Assessing Risk*
Clinical Judgement
ActuarialStructured
ProfessionalJudgement (SPJ)
ModernComprehensiveRisk Assessment
*Multiple sources incl RSVP manual
Background re AWOLs High profile cases casting close eyes on NCRs:
Vincent Li –beheading/cannibalism of stranger on bus – NCR in 2008 in AB
Allan Schoenborn – murder of his 3 children – NCR in 2008 in BC
Guy Turcotte – cardiologist murdered his 2 children – NCR in 2011 in QC
Trevor Kloschinsky – murder of RCMP – NCR in 2014 in AB Matt de Grood – murder of 5 at house party – NCR in 2015 in
AB Etc: http://globalnews.ca/news/2718174/list-canadas-
prominent-not-criminally-responsible-ncr-cases/
Perception that NCRs are dangerous, but… 1800 pts (Can J Psychiatry 2015) – 9% recidivism in
Ontario, 22% in QC, 10% in BC 0.2% recidivate cause death/attempt (ie 4 charges) 7% of all NCRs in study had murder/attempt murder
Only 1% of those with serious violence index offence with have new violent offences
AWOLs also add to the bad press
Andre Noel Denny
Raymond Taavel
• Andre was found NCR dx schizophrenia• Utt threats, injury dog, breach, stolen dog
• Housed at East Coast Forensic• AWOL April 16/12 – drank alcohol and used
Cocaine with 2 co-AWOLs• Andre went to gay night club in Halifax• Hit two men, including Raymond• Hit Raymond twice in head, knocking down• Once down, kicked in head & slammed face
into pavement several times – turned to 2nd man, who fled, then came backto motionless Raymond, slamminghead 4-5 more times
• Convicted of manslaughter & given 8 years
Sandy Simpson & Johann Brink
AWOL = bad press, but not just in Canada
What predicts AWOL?
Stewart & Bowers 2010 Maudsley – Absconding from psychiatric hospitals:
a literature review (report from the Conflict & Containment Reduction Research Programme)
Reviewed literature from 1872 to 2009, excluding dementia/youths
75 studies included AWOL – definitions vary, but unauthorized leave
>1 hour to >72 hours Rates per 100 admissions per month
USA 8.9/100 UK 6.3/100 Ireland 4.3/100
Stewart & Bowers 2010
Rates per 100 beds per month USA 4.7/100 beds UK 1.4/100 beds
Locked units < Mixed units < Open units 0.65/100 beds vs 2.51/100 beds vs 12.68/100
beds
Some studies note that repeat absconders may be 24% accounting for 44% of AWOLs and that 50% of absconders are repeaters
Stewart & Bowers 2010 Antecedents/Reasons
Opportunity takers – reduced security times, escorted trips often with planning in advance
Recent deterioration in mental state Medication non-compliance (esp 48 hours before) Stressors:
Missing & caring for family/ friends Needing money
Boredom, questioning need for hospitalization, ward environment
Stewart & Bowers 2010 Outcomes
Most common go home or friends’ house If have money, then substance/alcohol common –
may go to pub – one study noted 20% drink, 10% use THC
Very rare suicide attempts, aggression to others, victims of assault in some studies; others note crime up to 10% (theft, threatening behaviours, assault)
Most of time, return in 24 hours – around 10% > 1 month
Stewart & Bowers 2010
Who Younger (<25 to <35 yo) Men > women (maybe – not supported in
some studies) Schizophrenia and Personality disorders seem
to be highest risk Previous criminal hx Early in admission Hx of AWOLs
Wilke et al 2014
Characteristics and motivations of absconders from forensic mental health services: a case-control study
CAMH – 180 beds (4 med and 4 min secure) and 250 NCR in community
57 patients doing 102 incidents of AWOL in 24 months
BMC Psychiatry 2014, 14:91
Wilkie et al
Wilkie et al
• Usually unaccompanied passes• Most in the city• 32% substance• Very rare charges/ violence/ harm to
person• Usually return on own or with police
Wilkie et al
Predictors Psychosis with co-morbid substance History of absconding attempts More in longer stays
Motivation Goal directed – likely voice intent within week, often brief
and return after goal done Frustration/ boredom – most common, often have/request
priv change, show increased verbal/px aggression Symptomatic/ disorganization – active symptoms in
month before, med changes, missed meds, voiced intention (voices saying go, got to get away from harmful vapours)
Accidental – rare
Interventions
Simpson et al 2015 The impact of structured decision making on
absconding by forensic psychiatric patients: results from an A-B design study. BMC Psychiatry 2015, 15:103.
86 patients doing 188 elopements in 42 months Implemented policy with clear process/ risk:
Submit form requesting new priv level HCR-20 items related to past rule/supervision violations,
substance use/ current insight/clinical stability Include specific nature/purpose leave and how relates to
rehab goals Define risks/benefits of leave
BMC Psychiatry 2015, 15:103
All team input to complete form sent for 2nd tier review by team of senior psychiatrist and management staff
Policy clarified re: when to apply, revocation, suspension including AWOLs
Privs were unescorted grounds, escorted community, etcwhich could then be altered by team (eg. Increasing lengths, etc)
Progressive decline seen over observation period Reasons were Frustration/Boredom (53%),
Symptoms/Disorganized (28%), goal-directed (25%), accidental (3%)
Risks included longer days under ORB, higher HCR20, being caucasion, history absconding, comorbid psychosis/substance (just psychosis was lower risk)
Some other papers
Russ Scott & Tom Meehan 2017 – Brisbane – 12 yr period with 46000 leaves and only 17 AWOL with 2 reoffence and 1 self-harm
Brumbles & Meister 2013 – educational package for staff on why elopement occurs
Martin et al 2018 – Ontario forensic hospital –54 events by 33 patients in 2 years – stressful event 2 weeks before best predictor; substance and HCR20 score also
Current tools
Hearn 2012 Developing the leave/abscond risk assessment (LARA)
from the absconding literature: an aide to risk management in secure services Hearn et al 2012, Advances in Mental Health and Intellectual disabilities 6(6):280-290
Noted characteristics may be time/era specific (Altman et al 1972) who highlighted following risks: male; student; Catholic; side-burns; odd haircuts; and cowboy boots.
Hearn 2012
Proposed tool based on literature Structured professional judgement Identify risk and make risk management
plan Not evidence based (ie validated tool)
Cullen et al (2015) developed a tool developed a four-item tool that included 4 factors: History of sexual offending Previous absconding Inpatient substance use Inpatient verbal aggression
Wolber & Karanian (2002) developed a 16-factor tool not been validated cumbersome
BEAT(draft)
BEAT Likelihood factors:
Historical risks Current/dynamic risks
Magnitude factors: What might occur
Length Adverse events harm Media issues
Scored as present/relevant (for research 0, 1, 2)
Historical issues
Elopement in past (list #, when, where) 0=none, 1= few/distant, 2=many/recentDeceitfulness0=mostly reliable, 1=variable, 2=frequent/recentPast substance use0=none, 1=intermittent/distant, 2=significant/recentPast impulsiveness0=none, 1=intermittent/some, 2=longstanding/lotsIs the factor present & relevant?
Recent Clinical Issues
Inability to follow rules (e.gcognition/irritable/impulsive)0=rule follower, 1=occasional, 2=frequentHallucinations/delusions/disorganization directly increasing risk – 0=none, 1 residual, 2 lots/directDepression/apathy/hopelessness re: moving ahead “passive” – 0=positive outlookAlcohol or Substance use/urges 0=none 2 likelyPsych Medication non-compliance 0, 1, 2Voiced plan to leave (by patient or other sources)Other destabilization in mental state (e.g. impulsivity, med changes)
Recent psychosocial issues
Recent decreased tolerance to stress from hospitalization (eg. denied privs, co-patient stress, disagreement with staff, boredom)External stressors increase desire to leave(e.g. Family problems, bad news, losses)Legal stressors (e.g. new/current charges, negative review board finding, possible jail)
Specific risk items if did elope
Hx of high profile/severe violence 0=none, 1 assault, 2=CBHExternal contacts who would facilitate leave (e.g. Criminal associates, family, friends, partners) Acute risk to others of significant violenceSubstance/ alcohol useExtended leave 1 = 24h-1week, 2 more than 1 weekHigh profile/media attentionSuicide/self-harm/lack of self careExploit/harm by others ($, sex,etc)Antisociality – based on crim record
Protective Factors
Ties to hospital (co-patients, staff, other reasons)Insight about consequences of elopingMitigating factors (e.g. decreased mobility, IQ)Others (list): (eg. Limited $, no ID)Scored 0=none, -1 = some/partial, -2
Overall analysis of risk
How probable is elopement- low to high If elope what will happen What risk management steps are you
taking to minimize elopement/ harm if elopes
Current study
Validation study All AWOLs from 2 forensic sites since 2009 190 incidents identified – 150 appropriate for
analysis; 64 patients involved; of 54 analyzed:
78% males 68% psychotic disorder; 44% ASPD; 11% ID 70% substance use disorders Index: 4% murder, 52% assault, 19% utt
threats/harassment; 95% are NCR and rest unfit
Current study
Of 115 incidents analyzed Supervision:
50% unaccompanied grounds pass 18% unaccompanied community pass 13% accompanied community 5% accompanied groups 11% off rehab (secure) unit; none off double
locked unit
Location: 75% in community, 17% beyond community
Current study
Outcomes 45% used substances 2.6% new charges 1 person assaulted by axe, 1 person sex trade
and held hostage
Returns 43% by self, 36% by police and 11% by staff Median leave of 6.5 hours (max 156 days)
Design
Blind files prepared with most recent ORB report, physician/nursing notes, case conference note
Never Absconded matched controls Scored once blindly
Absconded Scored blindly for each episode plus another
time-point to allow self control
Hypothesis
Likelihood items will positively predict elopement: In never-absconded patients and acute risk in
previously absconded patients
Protective items will negatively predict elopement
Overall score will predict elopement If so, then BEAT will serve as useful tool in
gradual community reintegration of forensic clients
Future
Hope this will show predictive value Could become part of a process for
community reintegration of forensic patients
Possibly applicability in non-forensic settings
