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Original Investigation | Meta-analysis

Interventions to Reduce Compulsory Psychiatric Admissions A Systematic Review and Meta-analysis

Mark H. de Jong, MD1; Astrid M. Kamperman, PhD2; Margreet Oorschot, PhD1; Stefan Priebe, FRCPsych3; Wichor Bramer, BSc4; Roland van de Sande, PhD5; Arthur R. Van Gool, PhD1; Cornelis L. Mulder, PhD2
[+] Author Affiliations
1Yulius Academy, Yulius Mental Health, Barendrecht, the Netherlands
2Epidemiological and Social Psychiatric Research Institute (ESPRi), Department of Psychiatry, Erasmus University Medical Centre, Rotterdam, the Netherlands
3Unit for Social and Community Psychiatry, Newham Centre for Mental Health, Queen Mary University of London, London, England
4Medical Library, Erasmus University Medical Centre, Rotterdam, the Netherlands
5Faculty of Health, University of Applied Science, Utrecht, the Netherlands
JAMA Psychiatry. 2016;73(7):657-664. doi:10.1001/jamapsychiatry.2016.0501.
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Importance  Compulsory admissions, defined as admissions against the will of the patient (according to local judicial procedures), have a strong effect on psychiatric patients. In several Western countries, the rate of such admissions is tending to rise. Its reduction is urgently needed.

Objective  To establish which interventions effectively reduce compulsory admissions in adult psychiatric patients in outpatient settings.

Data Sources  A systematic computerized literature search was performed using EMBASE, MEDLINE, Web of Science, PsycINFO, CINAHL, PubMed (not yet indexed for MEDLINE), Cochrane Central, and Google Scholar. Every database was searched from its inception until April 30, 2015.

Study Selection  Randomized clinical trials (RCTs) that studied any kind of intervention designed to reduce compulsory admission rates in adult psychiatric patients (age range, 18-65 years) in outpatient settings were eligible. Eligibility was independently assessed by 2 of us.

Data Extraction and Synthesis  Two of us independently extracted relevant data. The Cochrane Collaboration’s tool was used for assessing risk of bias. Overall risk reduction (random-effects estimate) was calculated in the following 4 subgroups of interventions: advance statements, community treatment orders, compliance enhancement, and integrated treatment.

Main Outcomes and Measures  Relative risk (RR) was calculated on the basis of the number of patients who had been compulsorily admitted.

Results  Our meta-analyses included 13 RCTs comprising 2970 psychiatric patients. The meta-analysis of the RCTs on advance statements showed a significant 23% (RR, 0.77; 95% CI, 0.60-0.98; I2 = 2.2%) (n = 1102) risk reduction in compulsory admissions. In contrast, the RCTs on community treatment orders (RR, 0.95; 95% CI, 0.81-1.10; I2 = 0.0%) (n = 742), compliance enhancement (RR, 0.52; 95% CI, 0.11-2.37; I2 = 55.7%) (n = 250), and integrated treatment (RR, 0.71; 95% CI, 0.49-1.02; I2 = 49.0%) (n = 876) showed no significant risk reduction in compulsory admissions.

Conclusions and Relevance  The meta-analysis of the RCTs on advance statements showed a statistically significant and clinically relevant 23% reduction in compulsory admissions in adult psychiatric patients, whereas the meta-analyses of the RCTs on community treatment orders, compliance enhancement, and integrated treatment showed no evidence of such a reduction. To date, only 13 RCTs have used compulsory admissions as their primary or secondary outcome measure. This demonstrates the need for more research in this field.

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Figure 1.
Flowchart Showing the Study Selection Process

A systematic computerized literature search was performed using EMBASE, MEDLINE, Web of Science, PsycINFO, CINAHL, PubMed (not yet indexed for MEDLINE), Cochrane Central, and Google Scholar. Every database was searched from its inception until April 30, 2015.

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Figure 2.
Relative Risk of Compulsory Admission per Subgroup of Intervention

Small blue diamonds represent relative risks of the individual randomized clinical trials, gray squares represent weights, horizontal lines or arrows represent 95% CIs, and large blue diamonds represent total relative risk per type of intervention and 95% CIs. Weights are from random-effects analysis.

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Figure 3.
Visual Assessment of Risk of Bias Across Studies

The 95% pseudoconfidence areas are shown.

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