[Joint crisis plans in mental health hospitals-Real practice in an association of psychiatric hospitals]. / Behandlungsvereinbarungen in der Psychiatrie ­ reale Praxis in einem Verbund psychiatrischer Kliniken.

BACKGROUND: Joint crisis plans (JCPs) are offered in many psychiatric hospitals, but patients only rarely make use of them. OBJECTIVE: To assess the rates of JCPs among inpatients of mental health hospitals and to analyze the clinical characteristics of patients who make use of a JCP. MATERIAL AND METHODS: We carried out a retrospective analysis of routine data from the statistical database/basis documentation of the LVR hospital association, which consists of nine psychiatric hospitals. The basis documentation is consistent in the nine hospitals. All admissions between 2016 and 2020 were considered. We recorded the existence of a JCP, age, gender and main diagnosis at release, as well as previous hospital stays, detention under the Mental Health Act of the Federal State of NRW and experiences with compulsory measures (seclusion/restraint) in the previous 24 months before index admission. RESULTS: Out of a total of 117,662 inpatients 467 (0.4%) had completed a JCP. Patients with JCP were more likely to be diagnosed with schizophrenia, bipolar disorder, or emotionally unstable personality disorder. Patients with a JCP had more previous inpatient stays and they had more frequently experienced detentions and compulsory measures. However, 50% of the patients with a JCP had other diagnoses and the vast majority of them had experienced no detention or compulsory measure in the 24 months preceding the first documentation of a JCP. CONCLUSIONS: Overall, the use of JCPs is limited. The targeted group of patients with severe mental illness and previous experience with involuntary placements and compulsory measures make use of the offer of a JCP but so do other patients as well. Additional qualitative analyses are required in order to analyze the content and objectives of JCPs in more detail.

Identification of risk factors for involuntary psychiatric hospitalization: using environmental socioeconomic data and methods of machine learning to improve prediction.

BACKGROUND: The purpose of this study was to identify factors associated with a high risk of involuntary psychiatric in-patient hospitalization both on the individual level and on the level of mental health services and the socioeconomic environment that patients live in. METHODS: The present study expands on a previous analysis of the health records of 5764 cases admitted as in-patients in the four psychiatric hospitals of the Metropolitan City of Cologne, Germany, in the year 2011 (1773 cases treated under the Mental Health Act and 3991 cases treated voluntarily). Our previous analysis had included medical, sociodemographic and socioeconomic data of every case and used a machine learning-based prediction model employing chi-squared automatic interaction detection (CHAID). Our current analysis attempts to improve the previous one through (1) optimizing the machine learning procedures (use of a different type of decision-tree prediction model (Classification and Regression Trees (CART) and application of hyperparameter tuning (HT)), and (2) the addition of patients' environmental socioeconomic data (ESED) to the data set. RESULTS: Compared to our previous analysis, model fit was improved. Main diagnoses of an organic mental or a psychotic disorder (ICD-10 groups F0 and F2), suicidal behavior upon admission, admission outside of regular service hours and absence of outpatient treatment prior to admission were confirmed as powerful predictors of detention. Particularly high risks were shown for (1) patients with an organic mental disorder, specifically if they were retired, admitted outside of regular service hours and lived in assisted housing, (2) patients with suicidal tendencies upon admission who did not suffer from an affective disorder, specifically if it was unclear whether there had been previous suicide attempts, or if the affected person lived in areas with high unemployment rates, and (3) patients with psychosis, specifically those who lived in densely built areas with a large proportion of small or one-person households. CONCLUSIONS: Certain psychiatric diagnoses and suicidal tendencies are major risk factors for involuntary psychiatric hospitalization. In addition, service-related and environmental socioeconomic factors contribute to the risk for detention. Identifying modifiable risk factors and particularly vulnerable risk groups should help to develop suitable preventive measures.

[Prices and quality in nursing homes - first empirical results for Germany]. / Preise und Qualität in Pflegeheimen - Erste empirische Ergebnisse für Deutschland.

OBJECTIVES: This paper analyses on the basis of data from over 2 400 nursing homes the relationship between remuneration rates and quality for Germany. Other factors influencing this relationship are taken into account.Data about nursing homes are taken from the nursing home data base PAULA, which includes about 11 500 nursing homes. DATA AND METHODS: Data about quality of care in nursing homes are derived from the so-called transparency reports for residential long-term care (PVTS). In a linear regression framework the different quality measures are regressed on the average nursing home price. Control variables are inter alia ownership, size and location of the nursing homes. RESULTS: The analyses show a statistically significant positive correlation between remuneration rates and quality. Better quality is reflected in higher remuneration rates. CONCLUSIONS: The results show a significant, but in actual size low relationship between quality and remunerations rates. The results cannot be interpreted as a causal relationship. Additionally, it is not possible to explain differences in nursing home prices over federal states with differences in quality.