Context: Developmental psychopathology theory suggests a relationship between early childhood adversity and mental disorder.Objective: To examine the relationship between the specific items on the Adverse Childhood Experiences (ACE) survey and the International Classification of Diseases, Tenth Revision (ICD-10) categories of psychiatric diagnoses in a pediatric sample.Design: The sample included patients enrolled in the Child and Adolescent Addiction Mental Health and Psychiatry Program with both a completed ACE survey and at least 1 diagnosis of record (per admission). These criteria yielded 2 samples for each sex (ACE survey item frequencies and values in collapsed and multiple-admission groups). Data were analyzed employing tetrachoric correlation, hierarchical regression, and polychoric factor analysis.Results: Hierarchical regression analysis identified that ICD-10 diagnostic categories, except for substance disorders, were not consistently related to ACE total score and tended to reduce the magnitude of the ACE total score in the multiple-admission group. Tetrachoric correlation revealed very low (< 0.4) positive and negative correlations between ICD-10 categories and ACE items in both multiple-admission and collapsed sample groups. Polychoric factor analysis indicated that the ACE survey items and the ICD-10 categories for both sexes were independent, with only the diagnostic ICD-10 category substance disorders being marginally associated with the ACE items factor for females. Conclusion:The nominal relationship between ACE items and ICD-10 diagnostic categories indicates the need to include ACE assessment in advance of differential diagnosis and implementation of conventional mental health interventions for children and adolescents. METHODS This research was conducted underThe University of Calgary Research Ethics Board approval (REB15-1057). Staff training on the collection of the ACE survey, the details of data collection, storage, and retrieval, as well as the relationship of ACE scores to clinical and demographic variables have been described. 1 This article focuses on the relationship of individual ACE survey items to psychiatric diagnoses of record. For each separation from service, where applicable, at least 1 and often several psychiatric diagnoses assigned by the attending resident or psychiatrist were recorded in each patient's file and entered into the electronic Regional Access and Intake System (RAIS).
Making the transition from the hospital to a community setting can be extremely challenging for patients with acute mental health conditions. Transitional services have been created to help patients overcome difficulties associated with this transition. Nurses frequently play an integral role in the success of these services. By providing patients with individualized support during such transitions, nurses act as clinical liaisons and directly contribute to an increase in positive patient and system-level outcomes. This article describes a transitional service called the Bridge Program, designed to help adolescents make a successful transition from the hospital to the community. An overview of the Bridge Program is provided, and the results of an evaluation of this program are presented. Results suggest that the Bridge Program contributes to a decrease in the length of hospital stays and improves continuity of care for patients and their families. <h4>ABOUT THE AUTHORS</h4> <p>Mr. Cameron is Psychologist, Ms. Birnie is Evaluation Assistant, Ms. Dharma-Wardene is Evaluation Analyst, Ms. Raivio is Psychiatric Nurse, and Mr. Marriott is Evaluation Assistant, Calgary Health Region, Mental Health and Addictions Services, Calgary, Alberta, Canada.</p> <p>The authors disclose that they have no significant financial interests in any product or class of products discussed directly or indirectly in this activity, including research support.</p> <p>Address correspondence to Christopher L. Cameron, BSc (Hons.), MA, Psychologist, Calgary Health Region, Mental Health and Addictions, Family, Adolescent, and Child Services, Room 207, 2675 36th Street NE, Calgary, Alberta, Canada T1Y 6H6; e-mail: <a href="MAILTO:christopher.cameron@calgaryhealthregion.ca">christopher.cameron@calgaryhealthregion.ca</a>.</p>
Canada is a federal country of 10 provinces and three territories. High level information on mental health conditions and service use has mostly been generated from administrative data collected by provinces and territories. These include four major types - hospital admissions and discharges, physician billings, ambulatory care services, and drug databases. At the national level, the Canadian Institute for Health Information brings together this information to produce indicators of outcome. Although these data provide information on patient and health system characteristics, they do not capture the full spectrum of formal and informal mental healthcare. These include changes in health status, functioning, community integration and quality of life. As a result, some jurisdictions have begun to implement more standardized measures of outcome such as the clinician-rated Health of the Nation Outcome Scales or the inpatient Resident Assessment Instrument - Mental Health. In this paper we provide an overview of mental-health-related data sources in Canada, highlight some of the more progressive practices beginning to emerge, and conclude with some thoughts about how the routine measurement and reporting of mental health outcomes in Canada might be advanced including efforts at engaging both clinicians and decision-makers.
Background Extensive literature has shown an association of Adverse Childhood Experiences (ACEs) with adverse health outcomes; however, its ability to predict events or stratify risks is less known. Individuals with mental illness and ACE exposure have been shown to visit emergency departments (ED) more often than those in the general population. This study thus examined the ability of the ACEs checklist to predict ED visits within the subsequent year among children and adolescents presenting to mental health clinics with pre-existing mental health issues. Methods The study analyzed linked data (n = 6100) from two databases provided by Alberta Health Services (AHS). The Regional Access and Intake System (RAIS 2016–2018) database provided data on the predictors (ACE items, age, sex, residence, mental health program type, and primary diagnosis) regarding children and adolescents (aged 0–17 years) accessing addiction and mental health services within Calgary Zone, and the National Ambulatory Care Reporting System (NACRS 2016–2019) database provided data on ED visits. A 25% random sample of the data was reserved for validation purposes. Two Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression models, each employing a different method to tune the shrinkage parameter lambda (namely cross-validated and adaptive) and performing 10-fold cross-validation for a set of 100 lambdas in each model were examined. Results The adaptive LASSO model had a slightly better fit in the validation dataset than the cross-validated model; however, it still demonstrated poor discrimination (AUC 0.60, sensitivity 37.8%, PPV 49.6%) and poor calibration (over-triaged in low-risk and under-triaged in high-risk subgroups). The model’s poor performance was evident from an out-of-sample deviance ratio of − 0.044. Conclusion The ACEs checklist did not perform well in predicting ED visits among children and adolescents with existing mental health concerns. The diverse causes of ED visits may have hindered accurate predictions, requiring more advanced statistical procedures. Future studies exploring other machine learning approaches and including a more extensive set of childhood adversities and other important predictors may produce better predictions. Furthermore, despite highly significant associations being observed, ACEs may not be deterministic in predicting health-related events at the individual level, such as general ED use.
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