Background Mental health services are encouraged to use language consistent with principles of recovery-oriented practice. This study presents a novel approach for identifying whether clinical documentation contains recovery-oriented rehabilitation language,… Click to show full abstract
Background Mental health services are encouraged to use language consistent with principles of recovery-oriented practice. This study presents a novel approach for identifying whether clinical documentation contains recovery-oriented rehabilitation language, and evaluates an intervention to improve the language used within a community-based rehabilitation team. Aims This is a pilot study of training to enhance recovery-oriented rehabilitation language written in care review summaries, as measured through a text-based analysis of language used in mental health clinical documentation. Method Eleven case managers participated in a programme that included instruction in recovery-oriented rehabilitation principles. Outcomes were measured with automated textual analysis of clinical documentation, using a custom-built dictionary of rehabilitation-consistent, person-centred and pejorative terms. Automated analyses were run on Konstanz Information Miner (KNIME), an open-source data analytics platform. Differences in the frequency of term categories in 50 pre-training and 77 post-training documents were analysed with inferential statistics. Results The average percentage of sentences with recovery-oriented rehabilitation terms increased from 37% before the intervention to 48% afterward, a relative increase of 28% (P < 0.001). There was no significant change in use of person-centred or pejorative terms, possibly because of a relatively high frequency of person-centred language (22% of sentences) and low use of pejorative language (2.3% of sentences) at baseline. Conclusions This computer-driven textual analysis method identified improvements in recovery-oriented rehabilitation language following training. Our study suggests that brief interventions can affect the language of clinical documentation, and that automated text-analysis may represent a promising approach for rapidly assessing recovery-oriented rehabilitation language in mental health services.
               
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