M. Gonçalves-Pinho, Portugal
Centro Hospitalar do Tâmega e Sousa, Penafiel, Portugal Department of Psychiatry and Mental HealthPresenter of 4 Presentations
EPV0240 - Erik Satie – a psychopathological approach
ABSTRACT
Introduction
Éric Satie was a French classical music composer born in May of 1866. He composed several music pieces that did not fit the contemporaneous musical standard once he did not follow the orthodox rules of composition and harmonic expression.
Objectives
To analyse Erik Satie personality traits and possible psychopathological findings.
Methods
A narrative review was performed using Google Scholar database.
Results
His music, as it occurs in most musical composers, was said to translate his own personality and state of mind at the time. He was described as an eccentric with multiple descriptions demonstrating unstable and explosive personality traits of pride, determination, perfectionism and a hatred for convention that would put him near a Cluster A type of personality.
Conclusions
Although some authors conclude that Satie could be diagnosed with Asperger Syndrome I believe that his specificities represent more of personality traits than pathological findings.
EPV0582 - The use of Big Data in Psychiatry – the role of pharmacy registries
ABSTRACT
Introduction
Administrative databases (AD) are repositories of administrative and clinical data related to patient contact episodes with all sorts of health facilities (primary care, hospitals, pharmacies,…).The large number of patients/contact episodes with pharmaceutical facilities available, the systematic and broad register and the fact that AD provides Real-world data are some of the pros in using AD data.
Objectives
To perform a narrative review on the role of Big Data pharmaceutical registries in Mental Health research.
Methods
We conducted a narrative review using MEDLINE and Google Scholar databases in order to analyse current literature regarding the role of BigData pharmaceutical registries in Mental Health Research.
Results
Administrative variables like drug names and prices may be used and linked to other clinical variables such as patients disease, in-hospital mortality, length of stay,(…). The use of electronic medical records may also contribute to systematic surveillance approaches like local or national pharmacovigilance strategies, identification of patients at risk of developing complications and software pop-up warnings related to medication dosage, duplication and lateral effects. The use of Big Data pharmaceutical registries allows to create predictive epidemiological models regarding drugs lateral effects or interactions and may help to perform pharmacovigilance phase 4 clinical trials. Its use may be applied to the optimization of clinical decision, monitoring of drug adverse events, drug cost and administrative monitoring and as surrogate measures of quality care indicators.
Conclusions
Big Data use in pharmaceutical registries allows to collect large and important clinical and administrative data that may be later used in Mental Health care and research.
O007 - Bipolar Disorder hospitalizations – a Big Data approach
ABSTRACT
Introduction
Bipolar Disorder (BD) is a mental disorder characterized by long hospitalizations and frequent need for acute psychiatric care. Hospitalizations represent a valuable quality of care indicator in BD.
Objectives
The aim of this study was to describe a nationwide perspective of BD related hospitalizations and to use a BigData based approach in mental health research.
Methods
We performed a retrospective observational study using a nationwide hospitalization database containing all hospitalizations registered in Portuguese public hospitals from 2008 to 2015. Hospitalizations with a primary diagnosis of BD were selected based on International Classification of Diseases version 9, Clinical Modification (ICD-9-CM) codes of diagnosis 296.xx (excluding 296.2x; 296.3x and 296.9x).
Results
A total of 20,807 hospitalizations were registered belonging to 13,300 patients. 33.4% of the hospitalizations occurred in male patients and the median LoS was 16.0 days. Mean age was 47.9 years and male patients were younger(46.6 vs. 48.6; p< 0.001). 59 hospitalizations had a deadly outcome (0.3%). The most common cause of hospitalization in BD was the diagnosis code 296.4x (Bipolar I disorder, most recent episode (or current) manic) representing 34.3% of all hospitalizations, followed by the code 296.5x (Bipolar I disorder, most recent episode (or current) depressed) with 21.4%. The mean hospitalization charges were 3,508.5€ per episode, with a total charge of 73M€ in the 8-year period of this study.
Conclusions
This is a nationwide study using BigData analysis giving a broad perspective of BD hospitalization panorama at a nationwide level. We found differences in hospitalization characteristics by gender, age and primary diagnosis.
O251 - Schizophrenia hospitalizations - a big data approach
ABSTRACT
Introduction
Schizophrenia is characterized by long hospitalizations and a recurrent use of chronic and acute psychiatric care.
Objectives
The aim of this study was to analyze schizophrenia related hospitalizations in Portugal.
Methods
A retrospective observational study was conducted using a nationwide hospitalization database containing all hospitalizations registered in Portuguese public hospitals from 2008 to 2015.Hospitalizations with a primary diagnosis of schizophrenia were selected and schizophrenia subtypes were grouped using the International Classification of Diseases version 9, Clinical Modification(ICD-9-CM) codes of diagnosis 295.xx.
Results
There was a total of 25,385 hospitalizations in public hospitals of Portugal between 2008 and 2015 with a primary diagnosis of Schizophrenia or other psychotic disorders. A total of 14,279 patients were hospitalized during the study period with an average of 1,78 hospitalizations episodes per patient in the 8-year interval(0.22 hospitalizations/patient/year). 68.0% of the hospitalizations occurred in male patients and the median length of stay was 18.0 days. Mean hospitalization charges were 3,509.7€ per hospitalization, summed to a total charge of 89.1M€ .
Throughout the study period there was a significant linear decrease in the number of hospitalizations (r = 0.940; B= -47.488; p = 0.001). The last year of the study(2015) had the lowest number of hospitalizations with a total of 2,958 (vs. 3,314 in 2008). When adjusted for the yearly population, there was also a decrease of the number of hospitalizations per 100,000 inhabitants from 31.39 to 28.56 hospitalizations per 100,000 inhabitants between 2008 and 2015, respectively.
Conclusions
We found differences in hospitalization characteristics by gender, age and primary diagnosis.