Mortality in women with a history of incarceration in Norway: a 20-year national cohort study.

BACKGROUND: Women carry a substantial burden of psychiatric, somatic and lifestyle-related morbidity in the prison context. By describing causes of death and estimating the risk and burden of mortality compared with the general population, this study investigates how mortality operates in this highly marginalized and under-researched population. METHODS: In this registry-based study of all women incarcerated in Norwegian prisons from 2000 to 2019 (N = 11 313), we calculated crude mortality rates, years of lost life and, by using mortality in age-matched women from the general population as a reference, age-standardized mortality ratios and years of lost life rates. RESULTS: Over a mean follow-up time of 10.7 years, at a median age of 50 years, 9% of the population had died (n = 1005). Most deaths (80%) were premature deaths from an avoidable cause. Drug-induced causes and deaths from major non-communicable diseases (NCDs) were most frequent (both 32%). Compared with women in the general population, women with a history of incarceration were more likely to die from any cause. Trends in annual age-standardized years of lost life rates suggest that the mortality burden associated with major NCDs has gradually replaced drug-induced causes. CONCLUSIONS: Women with a history of incarceration die at a greater rate than their peers and largely from avoidable causes. The profile of causes contributing to the substantial burden of mortality placed on this population has changed over time and has important implications for future efforts to reduce morbidity and the risk of premature death following release from prison.

Psychiatric morbidity among women in Norwegian prisons, 2010-2019: a register-based study.

PURPOSE: Research suggests that women in prison have more mental health problems than men and are prone to suffer from more severe psychiatric disorders. This study utilizes national registry data to describe demographic and psychiatric gender differences in Norwegian prisons, and to investigate comorbid psychiatric disorders and time trends in psychiatric morbidity among women. METHODS: Longitudinal data from the Norwegian Prison Release Study linked with the Norwegian Patient Registry and data from Statistics Norway provided information on health care utilization, socioeconomic status, and history of psychiatric disorders among all individuals (nwomen = 5,429; nmen = 45,432) who were incarcerated in a Norwegian prison between 2010 and 2019. RESULTS: Women were more likely than men to have a history of any psychiatric disorder (75% vs. 59%). Substance use disorders and dual disorders were highly prevalent in both genders, yet highest among women (56 and 38% respectively, versus 43 and 24% among men). From 2010 to 2019, we found a considerable increase in the 12-month prevalence of most diagnostic categories among women entering prison. CONCLUSION: Psychiatric and dual disorders are highly prevalent in Norwegian prisons, and especially among women. The proportion of women entering prison with a recent history of mental health problems has increased rapidly over the last decade. Women's prison institutions need to adjust health and social services, and awareness about substance use and other psychiatric disorders in order to meet the increasing proportion of women facing these challenges.

A roadmap for applying machine learning when working with privacy-sensitive data: predicting non-response to treatment for eating disorders.

OBJECTIVES: Applying machine-learning methodology to clinical data could present a promising avenue for predicting outcomes in patients receiving treatment for psychiatric disorders. However, preserving privacy when working with patient data remains a critical concern. METHODS: In showcasing how machine-learning can be used to build a clinically relevant prediction model on clinical data, we apply two commonly used machine-learning algorithms (Random Forest and least absolute shrinkage and selection operator) to routine outcome monitoring data collected from 593 patients with eating disorders to predict absence of reliable improvement 12 months after entering outpatient treatment. RESULTS: An RF model trained on data collected at baseline and after three months made 31.3% fewer errors in predicting lack of reliable improvement at 12 months, in comparison with chance. Adding data from a six-month follow-up resulted in only marginal improvements to accuracy. CONCLUSION: We were able to build and validate a model that could aid clinicians and researchers in more accurately predicting treatment response in patients with EDs. We also demonstrated how this could be done without compromising privacy. ML presents a promising approach to developing accurate prediction models for psychiatric disorders such as ED.

Design and testing of a health economic Markov model for treatment of anorexia nervosa.

OBJECTIVES: Anorexia Nervosa (AN) is a severe psychiatric disorder and knowledge about the cost-effectiveness of potential interventions is limited. The aim of this paper is to introduce the Trimbos Institute health economic cost-effectiveness model for Anorexia Nervosa (AnoMod-TI), a flexible modeling tool for assessing the long-term cost-effectiveness of interventions for AN in late adolescent and adult patients, which could support clinical decision making. METHODS: AnoMod-TI is a state-transition cohort simulation (Markov) model developed from a Dutch societal perspective, which consists of four health states - namely full remission (FR), partial remission (PR), AN and death. Results are expressed as total healthcare costs, QALYs and incremental cost-effectiveness ratio. RESULTS: For the purpose of demonstrating AnoMod-TI and how it could be used to estimate cost-effectiveness over a 20-year time horizon, it was applied to a hypothetical treatment scenario. Results illustrate how a relatively costly intervention with only modest effects can still be cost-effective in the long term. CONCLUSIONS: AnoMod-TI can be used to examine long-term cost-effectiveness of various interventions aimed at either treating AN or preventing relapse from a state of partial or full remission. AnoMod-TI is freely available upon request to the authors.