Background: Up to 48% of patients with bipolar disorder are either nonadherent or partially adherent to antipsychotic drug treatment. Medication adherence may differ by bipolar disorder subtype.

Objective: This study evaluated the association between antipsychotic treatment adherence and mental health care use among individuals with bipolar disorder with predominantly manic/mixed symptoms or predominantly depressive symptoms.

Methods: Individuals with bipolar or manic disorder who had at least 1 medical claim with International Classification of Diseases, Ninth Revision, Clinical Modification codes 296.4-296.8 (bipolar disorder) or 296.0 or 296.1 (manic disorder) were identified from medical and pharmacy claims in the PharMetrics database for the period from January 1999 through December 2004. Adherence was measured by intensity (medication possession ratio [MPR]) and treatment duration. The association between adherence and health care use during and after antipsychotic treatment was evaluated using multiple regression analysis. The traditional P < 0.05 threshold was used for statistical significance; however, results that approached significance at P < 0.10 were also noted.

Results: Claims data were examined for 13,941 antipsychotic treatment episodes occurring in 12,952 individuals with bipolar or manic disorder. Of these, 6153 treatment episodes occurred in 5711 individuals with predominantly manic/mixed symptoms, and 2617 occurred in 2381 individuals with predominantly depressive symptoms. The remaining 5171 treatment episodes occurred in 4860 individuals with unspecified bipolar disorder and were not included in the analysis. In individuals with manic/mixed symptoms, a higher MPR was associated with reduced total and outpatient mental health expenditures over subsequent stages of treatment (reduction in total expenditure per 1-point increment in MPR: $123-$439; P < 0.001). In individuals with predominantly depressive symptoms, the association between MPR and subsequent mental health expenditure reached statistical significance only in months 10-12, the 3rd of the 4 treatment segments examined (total mental health expenditure: -$714 [P < 0.001]; outpatient mental health expenditure: -$468 [P < 0.001]). A higher MPR was also associated with a lower likelihood of acute mental health care (inpatient hospitalization or an emergency department visit) in subsequent months in individuals with manic/mixed symptoms or depressive symptoms (odds ratio = 0.545 [95% CI, 0.30- 1.00] and 0.395 [95% CI, 0.14-1.12], respectively; both NS at the P < 0.05 threshold), and was not associated with mental health inpatient days. In both subgroups, a longer duration of treatment was associated with lower total and outpatient mental health expenditures during the 4 months after the termination of treatment (both, P < 0.01).

Conclusions: In these individuals with bipolar or manic disorder, improved adherence to antipsychotic treatment was associated with lower subsequent total and outpatient mental health care expenditures. This association was less pronounced in individuals with predominantly depressive symptoms than in those with predominantly manic/mixed symptoms.

Download full-text PDF

Source
http://dx.doi.org/10.1016/s0149-2918(08)80062-8DOI Listing

Publication Analysis

Top Keywords

mental health
40
bipolar disorder
24
antipsychotic treatment
20
health care
20
individuals bipolar
20
manic/mixed symptoms
20
manic disorder
16
depressive symptoms
16
outpatient mental
16
individuals
12

Similar Publications

Rectangular Repetitive Transcranial Magnetic Monophasic vs Biphasic Stimulation for Major Depressive Disorder: A Randomized Controlled Pilot Trial.

Neuromodulation

January 2025

Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.

Objectives: Biphasic sinusoidal repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain stimulation treatment that has been approved by the US Food and Drug Administration for treatment-resistant depression (TRD). Recent advances suggest that standard rTMS may be improved by altering the pulse shape; however, there is a paucity of research investigating pulse shape, owing primarily to the technologic limitations of currently available devices. This pilot study examined the feasibility, tolerability, and preliminary efficacy of biphasic and monophasic rectangular rTMS for TRD.

View Article and Find Full Text PDF

The current study aims to determine how the interactions between practice (distributed/focused) and mental capacity (high/low) in the cloud-computing environment (CCE) affect the development of reproductive health skills and cognitive absorption. The study employed an experimental design, and it included a categorical variable for mental capacity (low/high) and an independent variable with two types of activities (distributed/focused). The research sample consisted of 240 students from the College of Science and College of Applied Medical Sciences at the University of Hail's.

View Article and Find Full Text PDF

The COVID-19 outbreak, caused by the SARS-CoV-2 virus, was linked to significant neurological and psychiatric manifestations. This review examines the physiopathological mechanisms underlying these neuropsychiatric outcomes and discusses current management strategies. Primarily a respiratory disease, COVID-19 frequently leads to neurological issues, including cephalalgia and migraines, loss of sensory perception, cerebrovascular accidents, and neurological impairment such as encephalopathy.

View Article and Find Full Text PDF

The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human-computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants.

View Article and Find Full Text PDF

Personalized Clustering for Emotion Recognition Improvement.

Sensors (Basel)

December 2024

Instituto de Estudios de Género, Universidad Carlos III de Madrid, Calle Madrid, 126, 28903 Getafe, Spain.

Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (affective computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. In this sense, there are applications related to the safety and well-being of people (sexual assaults, gender-based violence, children and elderly abuse, mental health, etc.) that require even more improvements.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!