Many studies have explored the relationship between the demographics, diagnosis and treatment variables on length of stay in an acute psychiatric hospital. These studies have been able to account for about 10-37% of the variance in the length of stay. The relevant findings impacting the length of stay are shown in Table 2 .
Schizophrenia is a severe mental illness with a lifetime prevalence of approximately one percent worldwide. Maintenance antipsychotic treatment has been effective in preventing relapses in long-term follow-up studies. Logically it can be proposed that long-acting injectable antipsychotics (LAI) might reduce both unintentional and intentional nonadherence. Long-acting injectable aripiprazole was approved for the treatment of schizophrenia by the U.S. FDA on 28th February 2013 and will be marketed under the name Abilify Maintena. Aripiprazole LAI (ALAI) is a lyophilized powder that needs to be reconstituted with sterile water to form an injectable suspension without affecting the original molecule. The monthly injection interval is very attractive since patients prefer fewer injections. From a tolerability perspective, ALAI appears to be both weight neutral and lacking metabolic side effects. This can confer an advantage over the other currently available second-generation antipsychotic LAIs. Simple constitution with sterile water and no requirement to refrigerate make storage and administration easier. Like all medications, there are always potential disadvantages to ALAI. There is a period of oral coverage, while not as long as for long-acting risperidone microspheres (RLAI), that is required. Care must be taken to review concomitant medications for the presence of metabolic inducers and inhibitors. One would also expect some patients to be sensitive to extrapyramidal symptoms, especially akathisia which is well documented in the oral preparation. All things considered, we welcome our new tool, ALAI, to our work-place and predict both clinical practice and post marketing analysis and studies will discover its true value.
In a 2012 survey, in the United States alone, there were more than 35 000 reported suicides with approximately 1800 of being psychiatric inpatients. Recent Centers for Disease Control and Prevention (CDC) reports indicate an upward trend in these numbers. In psychiatric facilities, staff perform intermittent or continuous observation of patients manually in order to prevent such tragedies, but studies show that they are insufficient, and also consume staff time and resources. In this paper, we present the Watch-Dog system, to address the problem of detecting self-harming activities when attempted by in-patients in clinical settings. Watch-Dog comprises of three key components-Data sensed by tiny accelerometer sensors worn on wrists of subjects; an efficient algorithm to classify whether a user is active versus dormant (i.e., performing a physical activity versus not performing any activity); and a novel decision selection algorithm based on random forests and continuity indices for fine grained activity classification. With data acquired from 11 subjects performing a series of activities (both self-harming and otherwise), Watch-Dog achieves a classification accuracy of , , and for same-user 10-fold cross-validation, cross-user 10-fold cross-validation, and cross-user leave-one-out evaluation, respectively. We believe that the problem addressed in this paper is practical, important, and timely. We also believe that our proposed system is practically deployable, and related discussions are provided in this paper.
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