Assessing Elopement Risk with the BEAT

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

Questions/Discussion

Any thoughts? brad.booth@theroyal.ca