Documenting psychiatric risk: more than ticking boxes.

Australas Psychiatry

Mental Health and Addictions Services, Counties Manukau District Health Board, Auckland, New Zealand.

Published: December 2019

Objective: The purpose of this study was to audit the completion of risk assessment documentation by staff working within an acute adult mental health setting.

Method: Fifty risk assessment forms in a district health board's acute adult mental health service were audited for completion. Clinicians provided verbal feedback on the audit results.

Results: Risk assessment forms were completed in 58.3% of cases. A risk formulation statement was completed in 43.8% of cases. Rates of completion varied between senior medical officers, registrars and nurses.

Conclusion: Accurate risk formulation and safety planning are more important than ensuring all boxes are ticked on a form. Optimising the design of electronic forms may enhance access to information about historical risk.

Download full-text PDF

Source
http://dx.doi.org/10.1177/1039856219859272DOI Listing

Publication Analysis

Top Keywords

risk assessment
12
acute adult
8
adult mental
8
mental health
8
assessment forms
8
risk formulation
8
risk
7
documenting psychiatric
4
psychiatric risk
4
risk ticking
4

Similar Publications

Objective: Aneurysmal subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality rates. In particular, functional outcomes of SAH caused by large or giant (≥ 10 mm) ruptured intracranial aneurysms are worsened by high procedure-related complication rates. However, studies describing the risk factors for poor functional outcomes specific to ruptured large/giant aneurysms are sparse.

View Article and Find Full Text PDF

Objective: To assess factors influencing Neonatal Respiratory Distress Syndrome (RDS) risk, incorporating maternal demographics, behaviors, medical conditions, pregnancy-related factors, and PM2.5 speciation pollutants exposures.

Methods: Using Florida de-identified birth records, logistic regression analyses were conducted to assess associations between maternal exposure to PM2.

View Article and Find Full Text PDF

Objective: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.

Study Design: Prospective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.

Setting: Tertiary referral center.

View Article and Find Full Text PDF

In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performance remains limited owing to challenges such as imbalanced data, local optima, and parameter adjustment complexities. Thus, this paper introduces a novel hybrid unsupervised classification method, named the two-stage hybrid system with spectral clustering and semi-supervised support vector machine (TSC-SVM), which effectively addresses the unsupervised imbalance problem in credit risk assessment by targeting global optimal solutions.

View Article and Find Full Text PDF

Endosomes play a pivotal role in cellular biology, orchestrating processes such as endocytosis, molecular trafficking, signal transduction, and recycling of cellular materials. This study aims to construct an endosome-related gene (ERG)-derived risk signature for breast cancer prognosis. Transcriptomic and clinical data were retrieved from The Cancer Genome Atlas and the University of California Santa Cruz databases to build and validate the model.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!