Telepsychiatry

Fitz-Gerald, Patrick; Park, Taryn

doi:10.1007/978-3-030-50808-1_15

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…62 Involuntary admissions occur when an individual with mental illness is admitted to hospital under Ontario's Mental Health Act against their will owing to a perceived imminent danger to the individual or others. 63 Involuntary admission is a known antecedent of violence or aggression in emergency settings 10 22 64 as it disrupts the patient-provider relationship and has a negative impact on the patient's perception of their care. 65 66 Incidents are also more likely to occur during the first few days of admission, prior to the stabilisation of acute symptoms.…”

Section: Methods and Analysis Approachmentioning

confidence: 99%

Predictive care: a protocol for a computational ethnographic approach to building fair models of inpatient violence in emergency psychiatry

et al. 2023

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IntroductionManaging violence or aggression is an ongoing challenge in emergency psychiatry. Many patients identified as being at risk do not go on to become violent or aggressive. Efforts to automate the assessment of risk involve training machine learning (ML) models on data from electronic health records (EHRs) to predict these behaviours. However, no studies to date have examined which patient groups may be over-represented in false positive predictions, despite evidence of social and clinical biases that may lead to higher perceptions of risk in patients defined by intersecting features (eg, race, gender). Because risk assessment can impact psychiatric care (eg, via coercive measures, such as restraints), it is unclear which patients might be underserved or harmed by the application of ML.Methods and analysisWe pilot a computational ethnography to study how the integration of ML into risk assessment might impact acute psychiatric care, with a focus on how EHR data is compiled and used to predict a risk of violence or aggression. Our objectives include: (1) evaluating an ML model trained on psychiatric EHRs to predict violent or aggressive incidents for intersectional bias; and (2) completing participant observation and qualitative interviews in an emergency psychiatric setting to explore how social, clinical and structural biases are encoded in the training data. Our overall aim is to study the impact of ML applications in acute psychiatry on marginalised and underserved patient groups.Ethics and disseminationThe project was approved by the research ethics board at The Centre for Addiction and Mental Health (053/2021). Study findings will be presented in peer-reviewed journals, conferences and shared with service users and providers.

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Section: Methods and Analysis Approachmentioning

confidence: 99%

Predictive care: a protocol for a computational ethnographic approach to building fair models of inpatient violence in emergency psychiatry

et al. 2023

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“…Psychiatric presentations to emergency departments (EDs) continue to rise (Hill et al, 2021; Holland et al, 2021; Sara et al, 2022), leading to challenges related to ‘boarding’ in the ED that have proven difficult to address (Nordstrom et al, 2019; Zun, 2012). Many EDs rely heavily on ED staff to manage these presentations; however, various alternative system approaches have emerged (Coates, 2018; Fitz-Gerald and Takeshita, 2020). In Australia, one common model involves short-stay emergency psychiatric wards situated either adjacent to or within the ED.…”

Section: Introductionmentioning

confidence: 99%

The effectiveness of brief non-pharmacological interventions in emergency departments and psychiatric inpatient units for people in crisis: A systematic review and narrative synthesis

Huber,

Milton,

Brewer

et al. 2023

Aust N Z J Psychiatry

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Objective: Heterogeneous brief non-pharmacological interventions and guidelines exist to treat the burgeoning presentations to both emergency department and inpatient settings, for those in a crisis of mental ill-health. We systematically reviewed the literature to create a taxonomy of these brief non-pharmacological interventions, and review their evaluation methods and effectiveness. Method: We conducted a systematic review across Cochrane, CINAHL, DARE, Embase, MEDLINE, PsycINFO databases. Studies meeting quality criteria, using Joanna Briggs Institute tools, were eligible. Interventions were categorised, and outcomes synthesised. Results: Thirty-nine studies were included: 8 randomised controlled trials, 17 quasi-experimental, 11 qualitative studies, and 3 file audits. Taxonomy produced six coherent intervention types: Skills-focussed, Environment-focussed, Special Observation, Psychoeducation, Multicomponent Group and Multicomponent Individual. Despite this, a broad and inconsistent range of outcome measures reflected different outcome priorities and prevented systematic comparison of different types of intervention or meta-analysis. Few brief non-pharmacological interventions had consistent evidential support: sensory modulation rooms consistently improved distress in inpatient settings. Short admissions may reduce suicide attempts and readmission, if accompanied by psychotherapy. Suicide-specific interventions in emergency departments may improve depressive symptoms, but not suicide attempt rates. There was evidence that brief non-pharmacological interventions did not reduce incidence of self-harm on inpatient wards. We found no evidence for frequently used interventions such as no-suicide contracting, special observation or inpatient self-harm interventions. Conclusion: Categorising brief non-pharmacological interventions is feasible, but an evidence base for many is severely limited if not missing. Even when there is evidence, the inconsistency in outcomes often precludes clinicians from making inferences, although some interventions show promise.

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Geriatrics

Cho¹,

Takeshita²,

Huynh³

et al. 2023

Emergency Psychiatry

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Psychiatric emergencies in the geriatric population are expected to increase in the next decade and pose a unique challenge for clinicians in the emergency department or emergency consult setting. This cohort generally presents with numerous medical comorbidities and polypharmacy, and clinicians must be aware of age-related changes in physiology and pharmacokinetics. Geriatric psychiatric emergencies may also be precipitated by psychosocial factors such as retirement, grief, or elder abuse. Evaluation should initially focus on safety and typically requires utilization of collateral sources of history. Underlying medical etiologies of delirium should be ruled out, in addition to dementia screening and evaluation of depression or decompensated psychiatric illness. Medications should be used judiciously if indicated, and particular attention should be given to drug interactions and risk of toxicity. The COVID-19 pandemic has complicated the evaluation and management of psychiatric emergencies because there must now be clear procedures for screening, isolating, and treating COVID-19-positive patients. Age remains one of the most robust risk factors for both morbidity and mortality due to COVID-19. The growing use of telepsychiatry has improved access to emergency psychiatric services, geriatric patients included, but can be challenging.

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Telepsychiatry

Cited by 3 publications

References 19 publications

Predictive care: a protocol for a computational ethnographic approach to building fair models of inpatient violence in emergency psychiatry

Predictive care: a protocol for a computational ethnographic approach to building fair models of inpatient violence in emergency psychiatry

The effectiveness of brief non-pharmacological interventions in emergency departments and psychiatric inpatient units for people in crisis: A systematic review and narrative synthesis

Geriatrics

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