Suicidal ideation in patients with mental illness and concurrent substance use: analyses of national census data in Norway.

BACKGROUND: Suicidal ideation may signal potential risk for future suicidal behaviors and death. We examined the prevalence of recent suicidal ideation in patients with mental illness and concurrent substance use and explored the clinical and sociodemographic factors associated with suicidal ideation in this patient subgroup, which represents a particular risk group for adverse psychiatric outcomes. METHODS: We used national cross-sectional census data in Norway collected from 25,525 patients in specialized mental health services. The analytic sample comprised 3,842 patients with concurrent substance use, defined as having a co-morbid substance use disorder or who reported recent regular alcohol use/occasional illicit drug use. Data included suicidal ideation measured in relation to the current treatment episode, sociodemographic characteristics and ICD-10 diagnoses. Bivariate and multivariate analyses were used to examine differential characteristics between patients with and without suicidal ideation. RESULTS: The prevalence of suicidal ideation was 25.8%. The suicidal ideation rates were particularly high for those with personality disorders, posttraumatic stress disorder, and depression, and for alcohol and sedatives compared with other substances. Patients with suicidal ideation were characterized by being younger, having single marital status, and having poorly perceived social relationships with family and friends. CONCLUSION: Suicidal ideation in patients with mental illness and concurrent substance use was associated with a number of distinct characteristics. These results might help contribute to an increased focus on a subgroup of individuals at particular risk for suicidality and support suicide prevention efforts in specialized mental health services.

Substance use among patients in specialized mental health services in Norway: prevalence and patient characteristics based on a national census.

PURPOSE: The aim of this study was to investigate the clinical and demographic variation in the prevalence of substance use among the general psychiatric population in Norway. METHODS: A national census in psychiatric institutions and outpatient clinics was conducted. Data were returned for 2358 inpatients (response rate, 65%) and 23,167 outpatients (response rate, 60%). Substance use was measured based on substance use disorder diagnosis or reported substance use in the last 4 weeks (alcohol 2-4 days a week or more frequently/illicit drug use). Regression analyses controlling for demographic and sociodemographic characteristics were carried out. RESULTS: Substance use was identified in 32.4% of inpatients and 13.9% of outpatients. The most frequently reported substances used were alcohol, sedatives and cannabis. Among inpatients, the prevalence of substance use was highest in patients with schizophrenia, personality disorders and anxiety disorders. Among outpatients, the prevalence was highest in patients with schizophrenia and other psychoses. Inpatients with anxiety disorders and outpatients with schizophrenia and other psychoses had a significantly higher risk of substance use than other patients. In both samples, the prevalence of substance use was higher among males, 24 to 29-year-olds and the most socially deprived. CONCLUSIONS: This study provides further knowledge about patients at risk for co-morbid substance abuse and poor treatment outcomes. Clinicians may consider targeting patients with schizophrenia and other psychoses, young males and those who are socially deprived in efforts to prevent emerging substance abuse and improve outcomes.

Patterns of mental health care utilisation: distribution of services and its predictability from routine data.

OBJECTIVES: Explore if a multi-dimensional analytic approach to routinely registered data provides a comprehensive way to characterise utilisation patterns, and to test if the patients' functional status is a predictor for the use of services. METHOD: We linked register contact data during a two-year period, including all types of specialised mental health services, in the population of a Norwegian county. Cox regression was applied in the models for prediction of admission and readmission. RESULTS: Great variability and complexity in patterns of utilisation were found, including multiple transitions between in-patient and out-patient statuses. The distribution of services was characterised by a small group of patients receiving a disproportionally large amount of resources. A majority of 77% appeared as out-patients only. Severity of symptoms as well as of dysfunction, as assessed by the split GAF-score, differentiated amongst utilisation groups. Both dimensions were significant predictors for admission. In contrast, only the severity of dysfunction predicted readmission. CONCLUSION: Multi-dimensional data architecture and analytical perspectives can be applied to routine data, and should be used to analyse the diverse patterns of utilisation. Risk populations could be predicted by routinely registered information on functional status.

Comparison of social and sociodemographic characteristics and treatment goals of persons with alcohol versus drug use disorders: Result from a national census of inpatients in specialized treatment for substance use.

INTRODUCTION: We examined differences in social and sociodemographic characteristics and treatment goals between people with primary alcohol use disorder (AUD) versus those with a primary drug use disorder receiving inpatient treatment for a substance use disorder (SUD). METHODS: A national census utilizing a cross sectional design included 56 of 60 specialized inpatient SUD treatment clinics in Norway and all patients receiving treatment on a specific date (responserate = 70%). Data on substance use, social and sociodemographic characteristics, and patient-reported treatment goals were collected. Patients were classified as having primary AUD or a drug use disorder based on the main SUD diagnosis relevant to the treatment episode. RESULTS: The analytic sample included 1093 patients. Patients with primary AUD (n = 362) were more often older, had a higher educational level and income from work, and lived in permanent housing compared with patients with a drug use disorder (n = 731). Patients with AUD were more likely to have good relationships with friends. The higher frequency of reported reduced substance use (versus quitting substance use) as the treatment goal among AUD patients disappeared when controlled for sociodemographic factors. CONCLUSIONS: Knowledge about the different characteristics of inpatients with AUD versus a drug use disorder is relevant when conducting research involving the SUD treatment population and for facilitating treatment. The lower frequency of perceived support from friends among patients with a drug use disorder suggests a need for targeted efforts in (re)building supportive social relationships for inpatients being treated for SUD.

Unplanned admissions to inpatient psychiatric treatment and services received prior to admission.

BACKGROUND: Inpatient bed numbers are continually being reduced but are not being replaced with adequate alternatives in primary health care. There is a considerable risk that eventually all inpatient treatment will be unplanned, because planned or elective treatments are superseded by urgent needs when capacity is reduced. AIMS OF THE STUDY: To estimate the rate of unplanned admissions to inpatient psychiatric treatment facilities in Norway and analyse the difference between patients with unplanned and planned admissions regarding services received during the three months prior to admission as well as clinical, demographical and socioeconomic characteristics of patients. METHOD: Unplanned admissions were defined as all urgent and involuntary admissions including unplanned readmissions. National mapping of inpatients was conducted in all inpatient treatment psychiatric wards in Norway on a specific date in 2012. Binary logit regressions were performed to compare patients who had unplanned admissions with patients who had planned admissions (i.e., the analyses were conditioned on admission to inpatient psychiatric treatment). RESULTS: Patients with high risk of unplanned admission are suffering from severe mental illness, have low functional level indicated by the need for housing services, high risk for suicide attempt and of being violent, low education and born outside Norway. CONCLUSION: Specialist mental health services should support the local services in their efforts to prevent unplanned admissions by providing counselling, short inpatient stays, outpatient treatment and ambulatory outpatient psychiatry services. IMPLICATIONS FOR HEALTH POLICIES: This paper suggests the rate of unplanned admissions as a quality indicator and considers the introduction of economic incentives in the income models at both service levels.

Measuring readmissions: focus on the time factor.

OBJECTIVE: To assess the effects of choosing different time-intervals of observation when using unplanned readmissions as an outcome indicator. DESIGN: A conceptual model was developed based on the risk curve. The model assigned readmissions above a background level as 'related' to the earlier episode of illness. The characteristics of the hazard curve were used to estimate how the rates of related and unrelated readmissions varied with time. SETTING: Patients living in a region of Middle Norway served by eight acute-care hospitals and discharged in the year 1996. MAIN OUTCOME MEASURE: The conditional risk (hazard rate) of having an unplanned readmission. The information gathered allowed inclusion of readmissions to all hospitals in the area, and to make risk corrections for deaths. RESULTS: The identified proportion of readmissions judged as related to the earlier episode of illness was found to be very sensitive to changes in the time interval. With the commonly used interval of 30 days, 0.5 of all related readmissions were identified, while 0.7 of the readmissions included at this time were estimated as related ones ('true positives'). The hazard curve was different for medical and surgical patients, but the corresponding proportions of related and unrelated readmissions were relatively similar. Adjusting for deaths in the observation period did not result in significantly different risk curves. CONCLUSION: When unplanned readmissions are used as an outcome indicator, the measure is susceptible to the choice of time interval. The operative characteristics must be interpreted in the context of where it is intended that the indicator should be used.