A Prospective Cohort Study of Absconsion Incidents in Forensic Psychiatric Settings: Can We Identify Those at High-Risk?

Cullen, Alexis E.; Jewell, Amelia; Tully, John; Coghlan, Suzanne; Dean, Kimberlie; Fahy, Tom

doi:10.1371/journal.pone.0138819

Cited by 25 publications

(48 citation statements)

References 30 publications

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“…Patient absconding is defined as leaving a medical center without permission from service providers (2), which can pose risks to patients, their families, and hospital staff. The potential consequences of patient absconding include self-harm, suicide, violence, harm to others, self-neglect, death, treatment disruption, lengthened recovery, and stigmatized reputation of the hospital and health system (3)(4)(5)(6).…”

Section: Introductionmentioning

confidence: 99%

Patient Absconding and Its Predictors: A 5-Year Retrospective Analysis in a General Teaching Hospital in Tehran, Iran

et al. 2017

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Background and Purpose: Patient absconding from a hospital or leaving without permission is a major challenge with economic and social consequences for patients, healthcare staff, and society. Identification of the characteristics of absconding patients is essential to the prediction and prevention of such behaviors. Methods: This cross sectional study was performed in a large general teaching hospital in Tehran, Iran. Data of 460 absconding patients and 460 nonabsconding patients, admitted during March 2010 -March 2016, were extracted from the hospital information system. Backward stepwise logistic regression analysis was used to describe the importance and effect of each predictor. Results: The findings showed that 0.4% of the patients had left the hospital without permission or notice to the staff. Addiction

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Section: Introductionmentioning

confidence: 99%

Patient Absconding and Its Predictors: A 5-Year Retrospective Analysis in a General Teaching Hospital in Tehran, Iran

et al. 2017

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“…The current study utilises data from a longitudinal study [27] of forensic psychiatric inpatients within the South London and Maudsley (SLaM) National Health Service (NHS) Foundation Trust. SLaM is one of Europe’s largest providers of secondary mental health care and provides care predominately for the London boroughs of Lambeth, Southwark, Croydon, and Lewisham [28].…”

Section: Methodsmentioning

confidence: 99%

“…SLaM is one of Europe’s largest providers of secondary mental health care and provides care predominately for the London boroughs of Lambeth, Southwark, Croydon, and Lewisham [28]. In November 2011, an initial census was conducted of all SLaM patients receiving treatment in forensic inpatient services during a 2-week period [27], including those who were admitted or discharged during this time. At baseline, SLaM’s forensic inpatient services consisted of two medium-secure units (comprising eight inpatient wards) and one low-secure unit consisting of a single ward.…”

Section: Methodsmentioning

confidence: 99%

“…The current study utilised data from a longitudinal study of a sample ( N = 135) of forensic psychiatric inpatients in the UK [27]. Given the paucity of research examining dynamic factors, particularly in forensic populations, the primary aim of the current study was to examine the extent to which dynamic factors related to recent inpatient behaviour, cooperation with treatment, and substance misuse are associated with outcome at tribunal in this population.…”

Section: Introductionmentioning

confidence: 99%

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Predictors of Mental Health Review Tribunal (MHRT) outcome in a forensic inpatient population: a prospective cohort study

et al. 2017

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BackgroundPrevious studies have investigated factors associated with outcome at Mental Health Review Tribunals (MHRTs) in forensic psychiatric patients; however, dynamic variables such as treatment compliance and substance misuse have scarcely been examined, particularly in UK samples. We aimed to determine whether dynamic factors related to behaviour, cooperation with treatment, and activities on the ward were prospectively associated with outcome at MHRT.MethodsAt baseline, demographic, clinical, behavioural, and treatment-related factors were ascertained via electronic medical records and census forms completed by the patient’s clinical team. Data on MHRTs (i.e., number attended, responsible clinician’s recommendation, and outcome) were collected at a 2-year follow-up. Logistic regression analyses were performed to determine factors associated with outcome among those who attended a MHRT within the follow-up period. Of the 135 forensic inpatients examined at baseline, 79 patients (59%) attended a MHRT during the 2-year follow-up period and therefore comprised the study sample. Of these 79 patients included in the current study, 28 (35%) were subsequently discharged.ResultsIn univariable analyses, unescorted community leave, responsible clinician’s recommendation of discharge, and restricted Mental Health Act section were associated with a greater likelihood of discharge at MHRT; whilst inpatient aggression, a recent episode of acute illness, higher total score on the Historical Clinical Risk – 20 (HCR-20), higher HCR-20 clinical and risk scores, and agitated behaviour were negatively associated with discharge (p < 0.05). In multivariable analyses, HCR-20 clinical scale scores and physical violence independently predicted outcome at tribunal after controlling for other dynamic variables.ConclusionBy identifying dynamic factors associated with discharge at tribunal, the results have important implications for forensic psychiatric patients and their clinical teams. Our findings suggest that by reducing levels of agitated behaviour, verbal aggression, and physical violence on the ward, achieving unescorted community leave, and targeting specific items on the HCR-20 risk assessment tool, patients may be able to improve their changes of discharge at a MHRT.

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“…Both escape and absconding from closed psychiatric wards, and especially from secure forensic hospitals, can be serious events leading to potentially grave outcomes [1][2][3][4][5]. These can directly affect the patient concerned, such as overdosing [6][7][8], self-inflicted injury [8][9][10], attempted suicide [10][11][12][13][14] or completed suicide [15,16], prolonged rehabilitation and treatment [17], medication non-compliance [17], violence against others [4,9,14] or (re-) offending [8,13,15,[18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Escape and absconding among offenders with schizophrenia spectrum disorder – an explorative analysis of characteristics

2021

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Background Escape and absconding, especially in forensic settings, can have serious consequences for patients, staff and institutions. Several characteristics of affected patients could be identified so far, albeit based on heterogeneous patient populations, a limited number of possible factors and basal statistical analyses. The aim of this study was to determine the most important characteristics among a large number of possible variables and to describe the best statistical model using machine learning in a homogeneous group of offender patients with schizophrenia spectrum disorder. Methods A database of 370 offender patients suffering from schizophrenia spectrum disorder and 507 possible predictor variables was explored by machine learning. To counteract overfitting, the database was divided into training and validation set and a nested validation procedure was used on the training set. The best model was tested on the validation set and the most important variables were extracted. Results The final model resulted in a balanced accuracy of 71.1% (95% CI = [58.5, 83.1]) and an AUC of 0.75 (95% CI = [0.63, 0.87]). The variables identified as relevant and related to absconding/ escape listed from most important to least important were: more frequent forbidden intake of drugs during current hospitalization, more index offences, higher neuroleptic medication, more frequent rule breaking behavior during current hospitalization, higher PANSS Score at discharge, lower age at admission, more frequent dissocial behavior during current hospitalization, shorter time spent in current hospitalization and higher PANSS Score at admission. Conclusions For the first time a detailed statistical model could be built for this topic. The results indicate the presence of a particularly problematic subgroup within the group of offenders with schizophrenic spectrum disorder who also tend to escape or abscond. Early identification and tailored treatment of these patients could be of clinical benefit.

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A Prospective Cohort Study of Absconsion Incidents in Forensic Psychiatric Settings: Can We Identify Those at High-Risk?

Cited by 25 publications

References 30 publications

Patient Absconding and Its Predictors: A 5-Year Retrospective Analysis in a General Teaching Hospital in Tehran, Iran

Patient Absconding and Its Predictors: A 5-Year Retrospective Analysis in a General Teaching Hospital in Tehran, Iran

Predictors of Mental Health Review Tribunal (MHRT) outcome in a forensic inpatient population: a prospective cohort study

Escape and absconding among offenders with schizophrenia spectrum disorder – an explorative analysis of characteristics

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