Technology has the potential to remotely monitor patient safety in real-time that helps staff and without disturbing the patient. However, staff and patients' perspectives on using passive remote ...monitoring within an inpatient setting is lacking. The study aim was to explore stakeholders' perspectives about using Oxehealth passive monitoring technology within a high-secure forensic psychiatric hospital in the UK as part of a wider mixed-methods service evaluation.
Semi-structured interviews were conducted with staff and patients with experience of using Oxehealth technology face-to-face within a private room in Broadmoor Hospital. We applied thematic analysis to the data of each participant group separately. Themes and sub-themes were integrated, finalised, and presented in a thematic map. Design, management, and analysis was meaningfully informed by both staff and patients.
Twenty-four participants were interviewed (n = 12 staff, n = 12 patients). There were seven main themes: detecting deterioration and improving health and safety, "big brother syndrome", privacy and dignity, knowledge and understanding, acceptance, barriers to use and practice issues and future changes needed. Oxehealth technology was considered acceptable to both staff and patients if the technology was used to detect deterioration and improve patient's safety providing patient's privacy was not invaded. However, overall acceptance was lower when knowledge and understanding of the technology and its camera was limited. Most patients could not understand why both physical checks through bedroom windows, and Oxehealth was needed to monitor patients, whilst staff felt Oxehealth should not replace physical checks of patients as reassures staff on patient safety.
Oxehealth technology is considered viable and acceptable by most staff and patients but there is still some concern about its possible intrusive nature. However, more support and education for new patients and staff to better understand how Oxehealth works in the short- and long-term could be introduced to further improve acceptability. A feasibility study or pilot trial to compare the impact of Oxehealth with and without physical checks may be needed.
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Objective: Research on predictors of treatment outcome in depression has largely derived from randomized clinical trials involving strict standardization of treatments, stringent patient exclusion ...criteria, and careful selection and supervision of study clinicians. The extent to which findings from such studies generalize to naturalistic psychiatric settings is unclear. This study sought to predict depression outcomes for patients seeking treatment within an intensive psychiatric hospital setting and while comparing the performance of a range of machine learning approaches. Method: Depressed patients (N = 484; ages 18-72; 89% White) receiving treatment within a psychiatric partial hospital program delivering pharmacotherapy and cognitive behavioral therapy were split into a training sample and holdout sample. First, within the training sample, 51 pretreatment variables were submitted to 13 machine learning algorithms to predict, via cross-validation, posttreatment Patient Health Questionnaire-9 depression scores. Second, the best performing modeling approach (lowest mean squared error; MSE) from the training sample was selected to predict outcome in the holdout sample. Results: The best performing model in the training sample was elastic net regularization (ENR; MSE = 20.49, R2 = .28), which had comparable performance in the holdout sample (MSE = 11.26; R2 = .38). There were 14 pretreatment variables that predicted outcome. To demonstrate the translation of an ENR model to personalized prediction of treatment outcome, a patient-specific prognosis calculator is presented. Conclusions: Informed by pretreatment patient characteristics, such predictive models could be used to communicate prognosis to clinicians and to guide treatment planning. Identified predictors of poor prognosis may suggest important targets for intervention.
What is the public health significance of this article?
Knowledge of which patients are likely to exhibit a poor outcome may have important clinical implications regarding treatment recommendations (e.g., a more intensive, alternative or combination treatment) and can inform more careful symptom and treatment progress monitoring. In the present study, we used machine learning to develop predictions of treatment outcome for depressed individuals seeking treatment in a "real-world" psychiatric hospital clinic. A prognosis calculator was developed which generates personalized predictions of treatment outcome for individual depressed patients.
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Background: The advent of community-based care and de-institutionalization of persons with mental disorders have led to a progressive shift of care from formal health-care systems to informal care ...providers such as the family. This shift of care, from hospitals to the families, has led to a significant level of the burden on the family caregiver. This study aimed to identify factors which are associated with burden of care among caregivers of patients with bipolar affective disorder (BAD) seen at the Federal Psychiatric Hospital, Calabar. Materials and Methods: A simple random sampling technique of "yes or no" balloting was utilized to select 105 caregivers of bipolar patients seen at the outpatient clinic of the hospital. The selected caregivers (those who picked "yes") were recruited along with their respective patients after obtaining their consent. They were assessed using a set of five questionnaires, of which three (Patient Health Questionnaire-9 PHQ-9, Young Mania Rating Scale YMRS and Brief Psychiatric Rating Scale BPRS) were administered by the researchers on the patients whereas the remaining two (sociodemographic questionnaire and Family Burden Interview Schedule) were self-completed by the caregivers. Results: One hundred out of the 105 caregivers who were recruited completed the study procedure and returned properly filled questionnaires. The rates of objective and subjective burden on the caregivers were 79% and 74%, respectively. While the objective burden was associated with the patient's educational attainment and his/her scores on the YMRS and BPRS, the subjective burden was associated with the caregiver's monthly income and marital status, the patient's gender, number of suicide attempts, and scores on PHQ-9, YMRS, and BPRS. Of all the variables, the patients' scores on YMRS (P = 0.025) and PHQ-9 (P = 0.011) were the significant predictors of objective and subjective burden, respectively. Conclusion: This study identified the extent and factors associated with burden of care on caregivers of patients with BAD. Awareness of those factors might guide clinicians in instituting treatment strategies toward reducing the burden on caregivers.
Current outcomes for mental illness are widely regarded as poor. Since the introduction of psychotropic medications in the mid 1950's, previous psychosocial practices were minimized in favor of ...medication focused treatment. The majority of large U.S. state hospitals have closed with records destroyed or in storage, inaccessible to researchers. This creates barriers to studying and comparing outcomes before and after this shift in treatment practices.
The study aim was to examine discharge outcomes in relation to length of stay and diagnosis in one U.S. state hospital.
This case series study examined 5618 medical records of participants admitted to one state hospital from 1945 to 1954, the decade prior to adoption of psychotropic medications.
Of the 3332 individuals who left the facility, over half (59.87%) of first episode hospitalizations were discharged within 1 year, and 16.95% were hospitalized for more than 5 years. 46.17% of all admissions were discharged from hospital with no readmission. The most common diagnoses included schizophrenia, other forms of psychosis, and alcoholism. In the decade before the introduction of psychotropic medications, participants were often admitted for a single episode and returned to their homes within several years.
Although limited to one site, findings suggest that discharge outcomes prior to psychotropic medication as a primary treatment for mental illness may be more positive than previously understood.
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To examine whether the pandemic in 2020 caused changes in psychiatric hospital cases, the percentage of patients exposed to coercive interventions, and aggressive incidents. We used the case registry ...for coercive measures of the State of Baden-Wuerttemberg, comprising case-related data on mechanical restraint, seclusion, physical restraint, and forced medication in each of the State's 31 licensed hospitals treating adults, to compare data from 2019 and 2020. The number of cases in adult psychiatry decreased by 7.6% from 105,782 to 97,761. The percentage of involuntary cases increased from 12.3 to 14.1%, and the absolute number of coercive measures increased by 4.7% from 26,269 to 27,514. The percentage of cases exposed to any kind of coercive measure increased by 24.6% from 6.5 to 8.1%, and the median cumulative duration per affected case increased by 13.1% from 12.2 to 13.8 hrs, where seclusion increased more than mechanical restraint. The percentage of patients with aggressive incidents, collected in 10 hospitals, remained unchanged. While voluntary cases decreased considerably during the pandemic, involuntary cases increased slightly. However, the increased percentage of patients exposed to coercion is not only due to a decreased percentage of voluntary patients, as the duration of coercive measures per case also increased. The changes that indicate deterioration in treatment quality were probably caused by the multitude of measures to manage the pandemic. The focus of attention and internal rules as well have shifted from prevention of coercion to prevention of infection.
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37.
Long-Term Treatment with Trazodone Once-A-Day Bonelli, Annalisa; Shrashimirova, Milena; Tyanev, Ivan ...
Neuropsychiatric disease and treatment,
05/2023, Volume:
19
Journal Article
Peer reviewed
Purpose: This was an observational, prospective, single-group, multicentre, international study aimed to describe the clinical response, functional impairment, and quality of life (QoL) of patients ...suffering from major depressive disorder (MDD) and in treatment with Trazodone Once-A-Day (TzOAD) monotherapy, over a 24-week period. Patients and Methods: A total of 200 patients with a diagnosis of MDD who had been treated with TzOAD monotherapy were enrolled from 26 sites across 3 European countries (Bulgaria, Czech Republic, and Poland), including psychiatric private practices, and outpatient departments from general and psychiatric hospitals. Study assessments were completed by physicians and patients during routine visits within the normal practice of care. Results: Clinical response was assessed by Clinical Global Impressions - Improvement (CGI-I) responders' percentage at 24 (+ or -4) weeks. The majority of patients (86.5%) reported an improvement on the CGI-I compared to baseline. Results of the study confirm the well-known safety and tolerability of TzOAD, as well as its effectiveness on depressive symptoms, such as improvement in QoL, sleep quality, and overall functioning accompanied by favourable adherence and low drop-out rate. Conclusion: To our knowledge, this is the first observational, long-term study in patients suffering from MDD, conducted with TzOAD. The improvement observed in clinical response, overall functioning, depressive symptoms, and QoL along the 24 weeks (+4) maintenance period and the very good retention rate, suggest that TzOAD may represent an effective and well tolerated treatment option for patients suffering from MDD. Keywords: major depressive disorder, trazodone, patient-reported outcome, real-world evidence, effectiveness, long-term follow-up
The COVID-19 pandemic brought a burden and represented a challenge for the Romanian medical system. This study explored the consequences that COVID epidemiological measures had on the quality of the ...mental health care provided to hospitalized patients in a regional psychiatric hospital in Romania.
Both patient-level and hospital-level indicators were considered for this comparative retrospective study. On the one hand, we extracted patient-level indicators, such as sociodemographics, diagnosis, admission, and discharge dates for 7026 hospitalized patients (3701 women, average age = 55.14) from hospital records. On the other hand, for the hospital-level indicators, we included indicators referring to the aggregated concept of mental health services, such as case mix index, length of stay, bed occupancy rate and patients' degree of satisfaction. Data extracted covered a period of two years (1 March 2019-28 February 2021) before and during the first year of the COVID-19 pandemic.
We found that, compared to the pre-pandemic period, the pandemic period was marked by a drastic decrease in hospitalized patient admissions, coupled with an increase in emergency-based admissions. Other management indicators, such as the case mix index, the number of cases contracted/performed, and the degree of patient satisfaction, decreased. In contrast, the average length of stay and bed occupancy rate increased.
The COVID-19 pandemic, especially in the first year, raised multiple difficult issues for the management of psychiatric hospitals. It imposed an application of strict measures designed to face these new and unprecedented challenges. Our findings offer a detailed snapshot of the first year of the COVID-19 pandemic in terms of its impact on mental health services and suggest some future directions. Implications for hospital management are discussed.
There is a very high suicide rate in the year after psychiatric hospital discharge. Intensive postdischarge case management programs can address this problem but are not cost-effective for all ...patients. This issue can be addressed by developing a risk model to predict which inpatients might need such a program. We developed such a model for the 391,018 short-term psychiatric hospital admissions of US veterans in Veterans Health Administration (VHA) hospitals 2010-2013. Records were linked with the National Death Index to determine suicide within 12 months of hospital discharge (n=771). The Super Learner ensemble machine learning method was used to predict these suicides for time horizon between 1 week and 12 months after discharge in a 70% training sample. Accuracy was validated in the remaining 30% holdout sample. Predictors included VHA administrative variables and small area geocode data linked to patient home addresses. The models had AUC=.79-.82 for time horizons between 1 week and 6 months and AUC=.74 for 12 months. An analysis of operating characteristics showed that 22.4%-32.2% of patients who died by suicide would have been reached if intensive case management was provided to the 5% of patients with highest predicted suicide risk. Positive predictive value (PPV) at this higher threshold ranged from 1.2% over 12 months to 3.8% per case manager year over 1 week. Focusing on the low end of the risk spectrum, the 40% of patients classified as having lowest risk account for 0%-9.7% of suicides across time horizons. Variable importance analysis shows that 51.1% of model performance is due to psychopathological risk factors accounted, 26.2% to social determinants of health, 14.8% to prior history of suicidal behaviors, and 6.6% to physical disorders. The paper closes with a discussion of next steps in refining the model and prospects for developing a parallel precision treatment model.
Substance use disorder is a global mental health issue. Purpose in life, Loneliness and depression are key indicators of poor mental health, and people with substance use disorder are more likely to ...experience low purpose in life, depression, and loneliness. This study aims to further the understanding of purpose in life, depression and loneliness among substance use disorders (SUD) patients in three hospitals in Ghana. It uses a cross-sectional survey design. A total of 425 SUD inpatients were screened. Beck Depression Inventory-II, the revised UCLA Loneliness Scale, and the Purpose in Life Test were utilised to measure depression, loneliness, and purpose in life respectively. Data were analysed using the SPSS version 23 for Windows. Data from 378 participants were collected for this study using a cross sectional survey design; after data cleaning, frequency tables (for categorical variables) and descriptive statistics (for continuous variables) were used to summarise the demographics and the three outcome variables depression, purpose in life, and loneliness. Our findings indicate that overall, participants are more likely to experience low sense of purpose in life, depression, and loneliness compared to the general population. There was no statistically significant relationship between depression and loneliness (r = 0.030, p = 0.567). There was a statistically significant negative relationship between depression and purpose in life (r = -0.514, p < 0.001). There was a statistically significant positive relationship between purpose in life and loneliness (r = 0.147, p = 0.004). There was no gender difference in depression, purpose in life, and loneliness among SUDs patients in psychiatric hospitals. There were no significant differences in purpose in life, depression and loneliness based on marital status. It is anticipated that the findings of this study will inform policies and clinical practice regarding service provision for patients with SUDs.
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