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1.
Int J Ment Health Nurs ; 28(1): 288-296, 2019 Feb.
Article in English | MEDLINE | ID: mdl-30120873

ABSTRACT

Rates of seclusion vary across New Zealand's publicly funded district health board (DHB) adult mental health inpatient services as indicated by national data. Anecdotally, this variation has been attributed to a range of factors directly relating to the people admitted to acute inpatient services. This study examined the extent to which variation in seclusion rates could be explained by the sociodemographic and clinical differences between populations admitted into adult mental health inpatient services. Retrospective data were obtained from the Programme for the Integration of Mental Health Data (PRIMHD). A logistic regression model was fitted to these data, with seclusion (yes/no) as the dependent variable and DHB groups as the independent variable. The DHBs were classified into four groups based on their seclusion rates. The model adjusted for ethnicity, age, number of bed nights, total Health of the Nation Outcome Scales (HoNOS) scores, and compulsory treatment status. Odds ratios remained virtually unchanged after adjustment for sociodemographic and clinical factors. People admitted to DHB Group 4 (highest secluding DHBs) were 11 times more likely to be secluded than people in Group 1 (lowest secluding DHBs), adjusted OR = 11.1, 95% CI [7.5,16.4], P < 0.001. Results indicate DHB variation in seclusion rates cannot be attributed to the sociodemographic and clinical factors of people admitted into DHB adult mental health inpatient services. Instead, this variation may be explained by differences in service delivery models and practice approaches. A model of system improvements aimed at reducing seclusion is discussed.


Subject(s)
Mental Health Services/statistics & numerical data , Patient Isolation/statistics & numerical data , Adult , Age Factors , Ethnicity/statistics & numerical data , Female , Humans , Male , Mental Disorders/psychology , Mental Disorders/therapy , New Zealand
2.
Int J Ment Health Nurs ; 28(1): 199-208, 2019 Feb.
Article in English | MEDLINE | ID: mdl-30010239

ABSTRACT

The Health of the Nation Outcomes Scales (HoNOS) provides an overview of a person's behaviour, impairment, clinical symptoms, and social functioning. This study investigated the profile of people who had been secluded in New Zealand's adult mental health inpatient services using 12 individual HoNOS ratings. Routinely collected clinical data were extracted from the Programme for the Integration of Mental Health Data (PRIMHD). This is the national data set for mental health and addiction services. A logistic regression model was fitted to the data which adjusted for age, sex, ethnicity, bed nights, compulsory treatment, and district health board. After adjustment, three HoNOS items significantly predicted the risk of seclusion: overactive, aggressive, disruptive, or agitated behaviour (adjusted OR = 4.82, 95% CI [3.88, 5.97], P < 0.001); problem drinking or drug-taking (adjusted OR = 1.51, 95% CI [1.25, 1.82], P < 0.001); and problems with hallucinations and delusions (adjusted OR = 1.33, 95% CI [1.09, 1.63], P = 0.006). In addition, two HoNOS items were protective for seclusion: nonaccidental self-injury (adjusted OR = 0.65, 95% CI [0.51, 0.83], P < 0.001) and depressed mood (adjusted OR = 0.58, 95% CI [0.47, 0.72], P < 0.001). Thus, responding effectively to agitation and/or aggression, substance use, and psychosis plays an important role in reducing the use of seclusion. Mental health nurses and other workers can reduce seclusion through early assessment, effective communication, de-escalation techniques, reduction tools, trauma-informed care, and consulting with consumers and whanau.


Subject(s)
Patient Isolation/psychology , Psychiatric Department, Hospital/statistics & numerical data , Adolescent , Adult , Female , Humans , Inpatients/psychology , Inpatients/statistics & numerical data , Male , Mental Disorders/psychology , Mental Disorders/therapy , Middle Aged , New Zealand/epidemiology , Patient Isolation/statistics & numerical data , Treatment Outcome , Young Adult
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