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Abstract. Background: Outreach psychiatric emergency services play an important role in all stages of a suicidal crisis; however, empirical assessment data are scarce. This study describes characteristics of patients assessed by these services and involved in suicidal crises. Method: During a 5-year period, detailed information from psychiatric emergency service assessments was recorded; 14,705 assessments were included. Characteristics of patients with/without suicidal behavior and with/without suicide attempts were compared. Outcomes were adjusted for clustering of features within individual patients. Results: Suicidal behavior was assessed in 32.2% of patients, of whom 9.2% attempted suicide. Suicidal behavior was most commonly associated with depression or adjustment disorder and these patients were referred to the service by a general practitioner or a general hospital, whereas those who attempted suicide were less likely to be referred by a general practitioner. Those who attempted suicide were more likely to be female and have had a referral by a general hospital. Self-poisoning by medication was the most common method of attempting suicide. Limitations: Bias could be due to missed or incomplete assessments. Primary diagnoses were based on clinical observation at the time of the assessment or on the primary diagnosis previously recorded. In addition, suicidal behavior or attempted suicide might have been underestimated. Conclusions: Suicidal behavior is commonplace in assessments by psychiatric emergency services. Suicidal patients with/without a suicide attempt differed with respect to demographic features, primary diagnoses, and referring entities, but not with respect to treatment policy. About 40% of the suicidal patients with/without an attempt were admitted following assessment.

Aim: With the introduction of “Electronic Medical Record” (EMR) a wealth of digital data has become available. This provides a unique opportunity for exploring precedents for seclusion. This study explored the feasibility of text mining analysis in the EMR to eventually help reduce the use of seclusion in psychiatry. Methods: The texts in notes and reports of the EMR during 5 years on an acute and non-acute psychiatric ward were analyzed using a text mining application. A period of 14 days was selected before seclusion or for non-secluded patients, before discharge. The resulting concepts were analyzed using chi-square tests to assess which concepts had a significant higher or lower frequency than expected in the “seclusion” and “non-seclusion” categories. Results: Text mining led to an overview of 1,500 meaningful concepts. In the 14 day period prior to the event, 115 of these concepts had a significantly higher frequency in the seclusion category and 49 in the non-seclusion category. Analysis of the concepts from days 14 to 7 resulted in 54 concepts with a significantly higher frequency in the seclusion-category and 14 in the non-seclusion category. Conclusions: The resulting significant concepts are comparable to reasons for seclusion in literature. These results are “proof of concept”. Analyzing text of reports in the EMR seems therefore promising as contribution to tools available for the prediction of seclusion. The next step is to build, train and test a model, before text mining can be part of an evidence-based clinical decision making tool.