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Self-harm injury hospitalisations: an analysis of case selection criteria
Pamela Imm1, Brittany Grogan2, Ousmane Diallo3
1University of Wisconsin Population Health Institute, University of Wisconsin-Madison, Madison, Wisconsin, USA Pamela.Imm@dhs.wisconsin.gov.
Background:
This study explores the impact of using different criteria to identify nonfatal hospitalisations with self-harm injuries using 2017-2018 Wisconsin discharge data.
Methods:
Using International Classification of Diseases, 10th Revision, Clinical Modification codes, we classified records by three mutually exclusive selection criteria: subset A--principal diagnosis of injury, and any code for self-harm, initial encounter only; subset B--non-injury principal diagnosis, and any code for self-harm, initial encounter only; subset C--any principal diagnosis, and any code for self-harm, subsequent and sequelae encounters only. These categories were used to conduct two separate logistic regression models. Model 1 analysed the impact of surveillance limited to a principal diagnosis of injury, initial self-harm encounter (subset B compared with A). Model 2 analysed the impact if limited to initial encounters for self-harm, regardless of principal diagnosis (subset C compared with (A+B)). Both patient-level and visit-level analyses were conducted.
Results:
For both patient-level models, subsets that included additional records based on an expansion of selection criteria were significantly more likely to include children (model 1: OR 2.8, model 2: OR 2.9; compared with those 25-54 years), those with mental health disorders (model 1: OR 6.5, model 2: OR 4.3) and rural residents (model 1: OR 1.2, model 2: OR 1.4). Drug-related disorder and means of self-harm were significantly different among subsets for both models. Visit-level analyses revealed similar results.
Discussion:
Expanding case selection criteria would better capture the scale of hospitalisation for nonfatal self-harm. Using restrictive selection criteria may result in biased understanding of the affected populations, potentially impacting the development of policy and prevention programmes.
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