Measuring Quality of Care Received by Suicide Attempters in the Emergency Department

Rassy, Jessica; Daneau, Diane; Larue, Caroline; Rahme, Elham; Low, Nancy; Lamarre, Suzanne; Turecki, Gustavo; Bonin, Jean‐Pierre; Racine, Hélène; Morin, Suzanne M.; Dasgupta, Kaberi; Renaud, Johanne; Lesage, Alain

doi:10.1080/13811118.2020.1793043

Cited by 7 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 8 Other reports refer to patients with a specific mental disorder or problem needing emergency care, such as patients with ‘borderline personality disorders’, 13 ‘substance use disorders’ 14 or ‘suicide attempters’. 15 Other research focuses on problematic behaviour (that may or may not include people with a mental health problem) such as ‘acute agitation 16 ’, ‘acute behavioural disturbances’ 17 ‘violence and aggression’ 18 or to a lesser extent, ‘emotional dysregulation’. 19 Hence, it is apparent that there is no uniform and internationally used concept that encompasses all presenting patients with mental health and/or behavioural and/or emotional problems in need of ambulance and/or ED care.…”

Section: Introductionmentioning

confidence: 99%

Defining the concept of mental dysregulation in patients requiring ambulance and/or emergency department care: protocol for a Delphi consensus study

Van de Glind,

Crilly,

Galenkamp

et al. 2024

BMJ Open

View full text Add to dashboard Cite

IntroductionFrom the patient and staff perspective, care delivery for patients experiencing a mental health problem in ambulance and emergency department (ED) settings is challenging. There is no uniform and internationally accepted concept to reflect people with a mental health problem who require emergency care, be it for, or as a result of, a mental health or physical health problem. On initial presentation to the emergency service provider (ambulance or ED), the cause of their healthcare condition/s (mental health and/or physical health) is often initially unknown. Due to this (1) the prevalence and range of underlying causes (mental and/or physical) of the patients presenting condition is unknown; (2) misattribution of physical symptoms to a mental health problem can occur and (3) diagnosis and treatment of the initial somatic complaint and cause(s) of the mental/physical health problem may be hindered.This study will name and define a new concept: ‘mental dysregulation’ in the context of ambulance and ED settings.Methods and analysisA Delphi study, informed by a rapid literature review, will be undertaken. For the literature review, a steering group (ie, persons with lived experience, ED and mental health clinicians, academics) will systematically search the literature to provide a working definition of the concept: mental dysregulation. Based on this review, statements will be generated regarding (1) the definition of the concept; (2) possible causes of mental dysregulation and (3) observable behaviours associated with mental dysregulation. These statements will be rated in three Delphi rounds to achieve consensus by an international expert panel (comprising persons with lived experience, clinicians and academics).Ethics and disseminationThis study has been approved by the Medical Ethical Committee of the University of Applied Sciences Utrecht (reference number: 258-000-2023_Geurt van der Glind). Results will be disseminated via peer-reviewed journal publication(s), scientific conference(s) and to key stakeholders.

show abstract

Section: Introductionmentioning

confidence: 99%

Defining the concept of mental dysregulation in patients requiring ambulance and/or emergency department care: protocol for a Delphi consensus study

Van de Glind,

Crilly,

Galenkamp

et al. 2024

BMJ Open

View full text Add to dashboard Cite

show abstract

“…However, suicide remains a rare event with 2017 agestandardized mortality rate by suicide of 11.4 per 100,000 overall and 17.2 and 5.8 per 100,000 in males and females, respectively [4]. In Canada, it is approximated that for each death by suicide, there are 25-30 additional suicide attempts, many of which result in emergency department visits, immediate hospitalization, and/or mental health facility admissions in the past year [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec

Gholi Zadeh Kharrat,

Gagne,

Lesage

et al. 2024

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and act upon the predictions made with ML, more intuitive user interfaces must be validated. Thus, Interpretable AI is one of the crucial directions which could allow policy and decision makers to make reasonable and data-driven decisions that can ultimately lead to better mental health services planning and suicide prevention. This research aimed to develop sex-specific ML models for predicting the population risk of suicide and to interpret the models. Data were from the Quebec Integrated Chronic Disease Surveillance System (QICDSS), covering up to 98% of the population in the province of Quebec and containing data for over 20,000 suicides between 2002 and 2019. We employed a case-control study design. Individuals were considered cases if they were aged 15+ and had died from suicide between January 1st, 2002, and December 31st, 2019 (n = 18339). Controls were a random sample of 1% of the Quebec population aged 15+ of each year, who were alive on December 31st of each year, from 2002 to 2019 (n = 1,307,370). We included 103 features, including individual, programmatic, systemic, and community factors, measured up to five years prior to the suicide events. We trained and then validated the sex-specific predictive risk model using supervised ML algorithms, including Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Multilayer perceptron (MLP). We computed operating characteristics, including sensitivity, specificity, and Positive Predictive Value (PPV). We then generated receiver operating characteristic (ROC) curves to predict suicides and calibration measures. For interpretability, Shapley Additive Explanations (SHAP) was used with the global explanation to determine how much the input features contribute to the models’ output and the largest absolute coefficients. The best sensitivity was 0.38 with logistic regression for males and 0.47 with MLP for females; the XGBoost Classifier with 0.25 for males and 0.19 for females had the best precision (PPV). This study demonstrated the useful potential of explainable AI models as tools for decision-making and population-level suicide prevention actions. The ML models included individual, programmatic, systemic, and community levels variables available routinely to decision makers and planners in a public managed care system. Caution shall be exercised in the interpretation of variables associated in a predictive model since they are not causal, and other designs are required to establish the value of individual treatments. The next steps are to produce an intuitive user interface for decision makers, planners and other stakeholders like clinicians or representatives of families and people with live experience of suicidal behaviors or death by suicide. For example, how variations in the quality of local area primary care programs for depression or substance use disorders or increased in regional mental health and addiction budgets would lower suicide rates.

show abstract

“…These include patients with ‘mental illness’,13 ‘mental disorder’14 or ‘mental health crisis’ 15. Other authors focus on a specific subgroup of patients with mental health problems who need emergency care, such as patients with ‘borderline personality disorders’,16 ‘substance use disorders’17 or ‘suicide attempts’ 18. The problem with these descriptions is that uniformity is lacking.…”

Section: Introductionmentioning

confidence: 99%

“… 15 Other authors focus on a specific subgroup of patients with mental health problems who need emergency care, such as patients with ‘borderline personality disorders’, 16 ‘substance use disorders’ 17 or ‘suicide attempts’. 18 The problem with these descriptions is that uniformity is lacking. Moreover, some healthcare conditions (such as mental health disorders) are in many cases initially unknown and uncharted in the ECC.…”

Section: Introductionmentioning

confidence: 99%

Interventions to reduce interpersonal stigma towards patients with a mental dysregulation for ambulance and emergency department healthcare professionals: review protocol for an integrative review

Van de Glind,

Galenkamp,

Bleijenberg

et al. 2023

BMJ Open

View full text Add to dashboard Cite

IntroductionWorldwide, there is an increase in the extent and severity of mental illness. Exacerbation of somatic complaints in this group of people can result in recurring ambulance and emergency department care. The care of patients with a mental dysregulation (ie, experiencing a mental health problem and disproportionate feelings like fear, anger, sadness or confusion, possibly with associated behaviours) can be complex and challenging in the emergency care context, possibly evoking a wide variety of feelings, ranging from worry or pity to annoyance and frustration in emergency care staff members. This in return may lead to stigma towards patients with a mental dysregulation seeking emergency care. Interventions have been developed impacting attitude and behaviour and minimising stigma held by healthcare professionals. However, these interventions are not explicitly aimed at the emergency care context nor do these represent perspectives of healthcare professionals working within this context. Therefore, the aim of the proposed review is to gain insight into interventions targeting healthcare professionals, which minimise stigma including beliefs, attitudes and behaviour towards patients with a mental dysregulation within the emergency care context.Methods and analysisThe protocol for a systematic integrative review is presented, using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols recommendations. A systematic search was performed on 13 July 2023. Study selection and data extraction will be performed by two independent reviewers. In each step, an expert with lived experience will comment on process and results. Software applications RefWorks-ProQuest, Rayyan and ATLAS.ti will be used to enhance the quality of the review and transparency of process and results.Ethics and disseminationNo ethical approval or safety considerations are required for this review. The proposed review will be submitted to a relevant international journal. Results will be presented at relevant medical scientific conferences.PROSPERO registration numberCRD42023390664 (https://www.crd.york.ac.uk/prospero/).

show abstract

Measuring Quality of Care Received by Suicide Attempters in the Emergency Department

Cited by 7 publications

References 10 publications

Defining the concept of mental dysregulation in patients requiring ambulance and/or emergency department care: protocol for a Delphi consensus study

Defining the concept of mental dysregulation in patients requiring ambulance and/or emergency department care: protocol for a Delphi consensus study

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec

Interventions to reduce interpersonal stigma towards patients with a mental dysregulation for ambulance and emergency department healthcare professionals: review protocol for an integrative review

Contact Info

Product

Resources

About