Allocation Of Mental Health Resources Research Articles

Investigating the spatiotemporal patterns and clustering of attendances for mental health services to inform policy and resource allocation in Thailand

BackgroundMental illness poses a substantial global public health challenge, including in Thailand, where exploration of access to mental health services is limited. The spatial and temporal dimensions of mental illness in the country are not extensively studied, despite the recognized association between poor mental health and socioeconomic inequalities. Gaining insights into these dimensions is crucial for effective public health interventions and resource allocation.MethodsThis retrospective study analyzed mental health service utilization data in Thailand from 2015 to 2023. Temporal trends in annual numbers of individuals visiting mental health services by diagnosis were examined, while spatial pattern analysis employed Moran’s I statistics to assess autocorrelation, identify small-area clustering, and hotspots. The implications of our findings for mental health resource allocation and policy were discussed.ResultsBetween 2015 and 2023, mental health facilities documented a total of 13,793,884 visits. The study found anxiety, schizophrenia, and depression emerged as the top three illnesses for mental health visits, with an increase in patient attendance following the onset of the COVID-19 outbreak. Spatial analysis identified areas of significance for various disorders across different regions of Thailand. Positive correlations between certain disorder pairs were found in specific regions, suggesting shared risk factors or comorbidities.ConclusionsThis study highlights spatial and temporal variations in individuals visiting services for different mental disorders in Thailand, shedding light on service gaps and socioeconomic issues. Addressing these disparities requires increased attention to mental health, the development of appropriate interventions, and overcoming barriers to accessibility. The findings provide a baseline for policymakers and stakeholders to allocate resources and implement culturally responsive interventions to improve mental health outcomes.

Psychotropic Medication Prescriptions and Large California Wildfires

Wildfires, intensified by climate change, have known effects on physical health but their effects on mental health are less well characterized. It has been hypothesized that the residential proximity to a large wildfire can exacerbate underlying mental health conditions as evidenced by increased prescriptions of psychotropic medications. To evaluate the association between the occurrence of large wildfires and the prescription rates of psychotropic medications immediately following the start of the fire. This cohortstudy used an interrupted time-series analysis to compare psychotropic medication prescriptions in the 6 weeks before and after each of 25 wildfires. The setting was California counties within metropolitan statistical areas (MSAs) experiencing large wildfires from 2011 through 2018. Participants included individuals residing in California MSAs with prescriptions of psychotropic medications recorded in the Merative MarketScan Research Database (MarketScan) during the study period. Statistical analysis was performed for these 25 large wildfires occurring between September 2011 and November 2018. Residential proximity to large wildfires that burned more than 25 000 acres occurring in a California county within an MSA. Prescriptions of psychotropic medications, including antidepressants, antipsychotics, anxiolytics, hypnotics, and mood-stabilizers, with statins as a negative control outcome. For the study period, prescription data and patient-level attributes were extracted for 7 115 690 unique individuals (annual mean [range]: 889 461 [455 705-1 426 928] individuals) enrolled in MarketScan and residing in fire-affected MSAs. This study found a statistically significant increase in prescriptions of antidepressants (rate ratio [RR], 1.04 [95% CI, 1.01-1.07]), anxiolytics (RR, 1.05 [95% CI, 1.02-1.09]), and mood-stabilizing medications (RR, 1.06 [95% CI, 1.01-1.13]) in the fire period compared with the prefire baseline. However, the prescriptions of antipsychotics, hypnotics, and the negative control outcome, statins, showed no significant association. In this cohort study of large California wildfires, the occurrence of wildfire was associated with increased mental health burden as reflected in increased prescription rates of certain psychotropic medications. The findings underscore the need for further scientific examination into the mental health effects of wildfires and the allocation of mental health resources in disaster responses. California experienced a substantial burden of wildfires from 2011 to 2018, and as wildfires become more intense and frequent in the context of anthropogenic climate change, it is increasingly important to understand and address their mental health effects.

The Mental Health Care Act 2017 and Mental Health Resource Allocation in India

Abstract Mental health policymakers are now tasked with maximizing the efficient and effective use of mental health resources as a result of fundamental changes to mental health laws. A crucial step in this process is ensuring optimal resource allocation across the service. Multiple biases prevent policymakers from allocating resources to mental health, resulting in a violation of the right to health, an increase in suffering, and a heavy economic burden associated with mental illness. This article provides a summary of Indian mental health policy, examines Indian public perceptions of mental health, and assesses the impact of these perceptions on legislation and mental health resource allocation. Understanding resource allocation from the perspective of policymakers can enhance psychiatrists’ ability to influence the process.

Propensity of US Military Personnel to Seek Mental Health Care When Community Psychiatric Capacity Changes

Understanding how the active duty military population's mental health care use is associated with local military and civilian psychiatrist capacity is critical in designing the optimal allocation of mental health resources from both sectors to improve the mental health of military personnel. To evaluate whether the probability of mental health care visits by military personnel changes when psychiatrist capacity changes in their communities, when capacity is measured separately for military treatment facilities and civilian sectors. This cohort study of active duty US military service members between January 1, 2016, and September 30, 2020, combines data from the Defense Health Agency, the National Plan and Provider Enumeration System, and the US Census. Data were collected and analyzed from June 2022 to July 2023. The main outcome was the probability of making at least 1 mental health care visit in a given quarter at military treatment facilities and in civilian settings. Linear probability models with 2-dimensional fixed effects at individual and community levels were implemented to estimate changes in individual outcomes when community psychiatrist capacity changed. This study includes 1 958 421 US service members (83% men; mean [SD] age at baseline, 28.4 [8.0] years). Thirteen percent of service members did not have military treatment facility psychiatrists available within a 30-minute driving time, and 66% lived in communities with a psychiatrist shortage (<1 psychiatrist per 20 000 relevant population), while 9% lived in communities with high (>3 psychiatrists per 20 000 relevant population) military treatment facility psychiatrist capacity. Five percent of service members lived in communities with no civilian psychiatrists within a 30-minute driving time, while 66% lived in communities with high civilian psychiatrist capacity. The mean quarterly mental health care visit rates to military treatment facilities and civilian settings were 7% and 2%, respectively. The probability of a mental health care visit to a military treatment facility increased by 0.95 percentage points (95% CI, 0.79-1.10 percentage points; equivalent to 14%) when the individual experienced a change in military treatment facility capacity from no psychiatrist to high capacity. The probability of a mental health care visit to a civilian setting increased by 0.57 percentage points (95% CI, 0.38-0.76 percentage points; equivalent to 32%) when civilian capacity changed from no psychiatrist to high capacity. The magnitude of responses to military treatment facility capacity changes remained similar in communities that already had high civilian capacity. This cohort study of the US military population suggests that active duty military personnel rely largely on military treatment facilities for their mental health care and that there are meaningful responses to military treatment facility psychiatrist capacity changes even in communities with high civilian psychiatric capacity. Realigning military treatment facility psychiatrists across communities with shortages and high-capacity military treatment facilities, as well as addressing nongeographical barriers in the civilian sector, remain critical to achieve the optimal balance between military and civilian care provision.

The mental health impact of the COVID-19 pandemic on post-secondary students: A longitudinal study

This prospective longitudinal study measured sex-specific changes in depression, anxiety, and stress scores using, validated Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and the Perceived Stress Scale (PSS) in a cohort of 1445 post-secondary students (500 males, 945 females) assessed at three time points from December 2020 to January 2022. Participants were ascertained from a population of 15,585 students with in-person activities on campus at baseline and recruited from December 2020 to January 2021. We also assessed how sociodemographic characteristics influenced students' mental health outcomes. Inverse probability weighting was used to account for missing data and attrition. Linear mixed effects models were used to analyze the relationship between the mental health scores in each questionnaire, demographic and academic data, and public health stringency measured by the local stringency index. No change was observed in questionnaire scores over time for males and females, but the stringency index was significantly associated with increased stress. Being in a non-health-related-field or being white affected males and females differently for stress and anxiety, but not depression. Demographics tended to be more influential on females’ mental health than males. In conclusion, mental health resource allocation in time of emerging pandemic could benefit from targeted interventions.

The Theory of Bureaucratic Caring’s Examination of Psychological Debriefing

The use of psychological debriefing (PD) to stave off the symptoms of posttraumatic stress disorder (PTSD) has long been a controversial topic, hampered by the lack of congruent empirical evidence. This issue, PD within a healthcare setting, will be examined utilizing aspects of the theory of bureaucratic caring. Current findings suggest the popularity and recommendation of PD among the administrative staff of hospitals and individual employees but this is in direct contrast with numerous authors and global health governing bodies who discredit implementation. Overall, support for PD is not substantive, and implementation may increase the prevalence of PTSD among its participants. This dire consequence may, in turn, increase the economic and political burden of the healthcare system and poor health outcomes for participants. Awareness of the conflicting research may offer perspectives on (a) best practice standards, (b) the allocation of mental health resources, and (c) the creation of quality practice environments.

Equity assessment of the distribution of mental health beds in China: based on longitudinal data from 2011 to 2020

BackgroundMental health problems have become a public health problem that needs to be solved in China. However, medical resources for mental healthcare remain insufficient and unevenly distributed. The Chinese central government has taken many measures to address this issue over the last decade. This study aimed to evaluate the changes in equity in mental health bed allocation from 2011 to 2020.MethodsThe data of this study came from the China Health Statistical Yearbook (2012–2021) and the China National Administrative Division Information Platform. The annual growth rate was used to evaluate the time trends of mental health beds. The Lorenz curve, Gini coefficient and Theil index were used to assess equity in the demographic and geographical dimensions. The distribution of mental health beds was visualized on a map using geographic information system (GIS) software.ResultsThe total number of mental health beds in China increased steadily from 2011 to 2020. At the national level, the Gini coefficient and Theil index all exhibited downward trends over time. The mental health bed allocation in terms of the demographic dimension was relatively equitable, with Gini values all less than 0.3; however, the Gini coefficients by geographical area were all more than 0.6, indicating inequity. Intraregional contribution rates were higher than interregional contribution rates, which were all above 60%.ConclusionThe overall distribution equity of mental health beds improved from 2011 to 2020. The equity of mental health beds in terms of population size is superior to that in terms of geographical area. Intraregional differences are the main source of inequity. In particular, differences within the western region need to be given attention. Thus, the findings from this study emphasize that the demographic and geographical distributions and all influencing factors should be considered when the government makes mental health resource allocation policies.

Excess suicide attributable to the COVID-19 pandemic and social disparities in South Korea

The impact of COVID-19 pandemic on suicide remains unclear and might differ according to individuals’ socioeconomic characteristics. We aimed to investigate excess suicide attributable to COVID-19 in South Korea, stratified by the outbreak period and individual characteristics. We obtained daily time-series suicide mortality data for January 2017–December 2020 from the Korea National Statistics Office and performed a two-stage interrupted time-series analysis. We estimated excess suicide in 16 regions of Korea using a quasi-Poisson time-series regression model and pooled the region-specific estimates using a mixed-effects multivariate meta-analysis model in the first and second stages, respectively. From February 18 to December 31, 2020, suicide decreased by 9.5% [95% empirical confidence interval (eCI): 3.8%, 15.6%] compared to the number expected from the pre-pandemic period. The decrease in excess suicide risk from the initial pandemic was pronounced during the pandemic’s first and third waves. Further, we found that the decrease in suicide was more evident in individuals who were male [11.7% (95% eCI: 5.5%, 18.0%)], middle-aged [13.7% (95% eCI: 7.8%, 19.6%)], highly educated [12.6% (95% eCI: 6.4%, 19.4%)], and married [13.6% (95% eCI: 8.0%, 20.3%)] than in the general population, based on the point estimates. Our results provide timely evidence to establish public health policies for suicide prevention and suggest the prioritization of resource allocation for mental health of individuals based on individual characteristics.

Perceived Mental Health Among Adult Residents Living in Region 4 Illinois, U.S., During COVID-19 Pandemic: A Cross-Sectional Study

As of July 22, 2022, there were 3,528,282 total confirmed COVID-19 cases in Illinois, United States. The purpose of this study was to examine how the COVID-19 pandemic has contributed to Illinois Region 4 adult residents’ poor mental health and assess the mental health burden the residents experienced during the pandemic. A cross-sectional survey was administered via Qualtrics. Participants (N=632) living in the Illinois Region 4 counties of Bond, Clinton, Madison, Monroe, Randolph, St. Clair, and Washington were recruited through Facebook. The questionnaire was developed based on the current literature review and was validated by colleagues in public health. Both descriptive statistics and logistic regression were used for data analysis using SPSS. Most of the participants identified as female (86.7%). Many of the participants had an associate’s (23.6%) or a bachelor’s (29.4%) degree. About 84% of the participants reported that COVID-19 had changed things in their daily life (e.g., work, family, and social life). There was significantly more perceived mental health burden during the pandemic than there was before the pandemic (p&lt;0.001). Approximately 68% of participants believed more mental health resources should be made available within their county of residence. Overall, the study findings suggest the perceived mental health burden among Region 4 adults, which highlight the need for mental health issues to be prioritized and the allocation of mental health resources to be optimized.

A simulation–optimization framework for post-disaster allocation of mental health resources

Abstract. Extreme events, such as natural or human-caused disasters, cause mental health stress in affected communities. While the severity of these outcomes varies based on socioeconomic standing, age group, and degree of exposure, disaster planners can mitigate potential stress-induced mental health outcomes by assessing the capacity and scalability of early, intermediate, and long-term treatment interventions by social workers and psychologists. However, local and state authorities are typically underfunded, understaffed, and have ongoing health and social service obligations that constrain mitigation and response activities. In this research, a resource assignment framework is developed as a coupled-state transition and linear optimization model that assists planners in optimally allocating constrained resources and satisfying mental health recovery priorities post-disaster. The resource assignment framework integrates the impact of a simulated disaster on mental health, mental health provider capacities, and the Center for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) to identify vulnerable populations needing additional assistance post-disaster. In this study, we optimally distribute mental health clinicians to treat the affected population based upon rule sets that simulate decision-maker priorities, such as economic and social vulnerability criteria. Finally, the resource assignment framework maps the mental health recovery of the disaster-affected populations over time, providing agencies a means to prepare for and respond to future disasters given existing resource constraints. These capabilities hold the potential to support decision-makers in minimizing long-term mental health impacts of disasters on communities through improved preparation and response activities.

771 Psychiatric Illness Among Burn Patients: Experience at a Single ABA Verified Burn Center

Abstract Introduction Burn injury is uniquely characterized by the initial traumatic event in addition to the psychiatric component associated with physical change and recovery. Recent work has highlighted the importance of pre-existing psychiatric illness on both recovery and final outcomes in burn patients (Tarrier et al 2005, Hudson et al 2017, Wisely et al 2009). We examined the prevalence and association of psychiatric illness in our ABA verified burn unit. Knowledge of this information is critical in allocation of limited resources aimed toward addressing both the physical and mental aspect of burn injury. Methods The burn registry at a single verified burn center was examined from July 2017-July 2018. All consecutive burn patients with psychiatric illness who were admitted were included. Psychiatric illness was broken down into: depression, anxiety, bipolar disorder, schizophrenia and delirium. Need for psychiatric consultation, %TBSA, length of hospital stay, and operative intervention was also examined. Results 416 patients were admitted during the study period—44 pts (10.5%) had a psychiatric diagnosis on admission. Seventy-five percent of pts were male. The average TBSA burned was 15.3%. Seventy-five percent of patients required psychiatric consultation, and 57% required operative intervention (Table 1). The most common psychiatric condition was anxiety (50%), followed by depression (36%), bipolar disorder (27%), schizophrenia (23%), and delirium (18%). Forty-eight percent of patients had multiple (&amp;gt;1) psychiatric conditions. Female patients had a significant less TBSA burn (5.8%) vs. male (18.2%), P=.001, as well as a shorter LOS (12.1 dys vs. 31.5 dys) p=.004. Conclusions The association between burn injury and pre-existing psychiatric illness is well known (Hudson et al 2017, Wisely et al 2009). We found that over 10% of pts admitted to our burn unit had a psychiatric diagnosis, and a large number of these required further inpatient psychiatry consultation. More than half of patients required operative intervention indicating that severity of burn injury was high, with optimization of pre-existing conditions especially important. Additionally, psychiatric illness did not occur in isolation--48% of pts had &amp;gt;1 psychiatric diagnosis —a finding which has implications for resource allocation for mental health/ dedicated psychiatrist for burn patients. Applicability of Research to Practice Implications for resource allocations for dedicated burn psychiatrist/ resources for mental health.

Incidence of major depression diagnoses in the Canadian Armed Forces: longitudinal analysis of clinical and health administrative data

PurposeMajor depression is a leading cause of morbidity in military populations. However, due to a lack of longitudinal data, little is known about the rate at which military personnel experience the onset of new episodes of major depression. We used a new source of clinical and administrative data to estimate the incidence of major depression diagnoses in Canadian Armed Forces (CAF) personnel, and to compare incidence rates between demographic and occupational factors.MethodsWe extracted all data recorded in the electronic medical records of CAF Regular Force personnel, at every primary care and mental health clinical encounter since 2016. Using a 12-month lookback period, we linked data over time, and identified all patients with incident diagnoses of major depression. We then linked clinical data to CAF administrative records, and estimated incidence rates. We used multivariate Poisson regression to compare adjusted incidence rates between demographic and occupational factors.ResultsFrom January to December 2017, CAF Regular Force personnel were diagnosed with major depression at a rate of 29.2 new cases per 1000 person-years at risk. Female sex, age 30 years and older, and non-officer ranks were associated with significantly higher incidence rates.ConclusionsWe completed the largest study to date on diagnoses of major depression in the Canadian military, and have provided the first estimates of incidence rates in CAF personnel. Our results can inform future mental health resource allocation, and ongoing major depression prevention efforts within the Canadian Armed Forces and other military organizations.

Exploring mental health nurses’ perceptions on factors contributing to psychiatric readmissions in Eswatini: A qualitative study

BackgroundSince the year 2012, the National Psychiatric Referral Hospital (NPRH) in Eswatini (formerly Swaziland) has recorded high numbers of readmissions of people living with mental illness (PLWMI). The reasons for the observed increase have not been explored. PurposeWe describe the perceptions of mental health nurses on the factors contributing to the increased number of psychiatric readmissions in Eswatini. MethodsA qualitative, exploratory and descriptive design was employed to collect data using an unstructured interview guide through individual in-depth interviews among eleven (11) purposively selected mental health nurses working at the only psychiatric referral hospital in Eswatini. Thematic analysis was conducted following Creswell’s steps of qualitative data analysis to generate themes. ResultsMajority of the participants (n = 9) held bachelor’s degrees in nursing, with an average working experience of seven years in a mental health setting. Eight (8) themes emerged from the data, namely: i) clients’ negative attitudes towards medication and the illness, ii) substance abuse, iii) stigma and discrimination, iv) low socio-economic status, v) co-morbidity, vi) lack of family support, vii) family belief system and viii) administrative factors. ConclusionMental health nurses perceived comorbidity, clients’ negative attitudes, lifestyle habits, as well as social and administrative factors to be major contributors to readmissions of PLWMI. There is need to empower PLWMI with lifestyle-modification measures after discharge in order to prevent future relapses. Advocacy for increased resource allocation for mental health should be intensified in order to curb the number of readmissions among PLWMI.

Predictors of mental health-related acute service utilisation and treatment costs in the 12 months following an acute psychiatric admission.

A key step in informing mental health resource allocation is to identify the predictors of service utilisation and costs. This project aims to identify the predictors of mental health-related acute service utilisation and treatment costs in the year following an acute public psychiatric hospital admission. A dataset containing administrative and routinely measured outcome data for 1 year before and after an acute psychiatric admission for 1757 public mental health patients was analysed. Multivariate regression models were developed to identify patient- and treatment-related predictors of four measures of service utilisation or cost: (a) duration of index admission; and, in the year after discharge from the index admission (b) acute psychiatric inpatient bed-days; (c) emergency department (ED) presentations; and (d) total acute mental health service costs. Split-sample cross-validation was used. A diagnosis of psychosis, problems with living conditions and prior acute psychiatric inpatient bed-days predicted a longer duration of index admission, while prior ED presentations and self-harm predicted a shorter duration. A greater number of acute psychiatric inpatient bed-days in the year post-discharge were predicted by psychosis diagnosis, problems with living conditions and prior acute psychiatric inpatient admissions. The number of future ED presentations was predicted by past ED presentations. For total acute care costs, diagnosis of psychosis was the strongest predictor. Illness acuity and prior acute psychiatric inpatient admission also predicted higher costs, while self-harm predicted lower costs. The development of effective models for predicting acute mental health treatment costs using existing administrative data is an essential step towards a workable activity-based funding model for mental health. Future studies would benefit from the inclusion of a wider range of variables, including ethnicity, clinical complexity, cognition, mental health legal status, electroconvulsive therapy, problems with activities of daily living and community contacts.

Understanding service demand for mental health among Australians aged 16 to 64 years according to their possible need for treatment

To inform decisions about mental health resource allocation, planners require reliable estimates of people who report service demand (i.e. people who use or want mental health services) according to their level of possible need. Using data on 6915 adults aged 16-64 years in Australia's 2007 National Survey of Mental Health and Wellbeing, we examined past-year service demand among respondents grouped into four levels of possible need: (a) 12-month mental disorder; (b) lifetime but no 12-month mental disorder; (c) any other indicator of possible need (12-month symptoms or reaction to stressful event, or lifetime hospitalisation); (d) no indicator of possible need. Multivariate logistic regression analyses examined correlates of service demand, separately for respondents in each of levels 1-3. Sixteen per cent of Australian adults reported service demand, of whom one-third did not meet criteria for a 12-month mental disorder (equivalent to 5.7% of the adult population). Treatment patterns tended to follow a gradient defined by level of possible need. For example, service users with a 12-month disorder received, on average, 1.6-3.9 times more consultations than their counterparts in other levels of possible need, and had 1.9-2.2 times higher rates of psychologist consultation. Service users with a lifetime but not 12-month disorder or any other indicator of need consumed a similar average number of services to people with mild 12-month mental disorders, but received relatively fewer services involving the mental health sector. Service demand was associated with increased suicidality and psychological distress in all levels of possible need examined, and with poorer clinical and functional status for those with 12-month or lifetime disorders. Many Australians reporting service demand do not meet criteria for a current mental disorder, but may require services to maintain recovery following a past episode or because they are experiencing symptoms and significant psychological distress.

In-Person and Video-Based Post-Traumatic Stress Disorder Treatment for Veterans: A Location–Allocation Model

Post-traumatic stress disorder (PTSD) is associated with poor health but there is a gap between need and receipt of care. It is useful to understand where to optimally locate in-person care and where video-based PTSD care would be most useful to minimize access to care barriers, care outside the Veterans Affairs system, and total costs. We developed a service location systems engineering model based on 2010 to 2020 projected care needs for veterans across New England to help determine where to best locate and use in-person and video-based care. This analysis determined specific locations and capacities of each type of PTSD care relative to patient home locations to help inform allocation of mental health resources. Not surprisingly Massachusetts, Connecticut, and Rhode Island are well suited for in-person care, whereas some rural areas of Maine, Vermont, and New Hampshire where in-patient services are infeasible could be better served by video-based care than external care, if the latter is even available. Results in New England alone suggest a potential $3,655,387 reduction in average annual total costs by shifting 9.73% of care to video-based treatment, with an average 12.6 miles travel distance for the remaining in-person care.

A new resolution for global mental health

We commend the 130th session of the WHO Executive Board for adopting a resolution calling for a comprehensive response to the global burden of mental illnesses.1 Mental disorders account for 13% of the global disease burden, and major depression alone is expected to be the largest contributor by 2030.2 The economic effect is great, with mental disorders expected to cost nearly a third of the projected US$47 trillion incurred by all non-communicable diseases by 2030.3 Meanwhile, the burden on people living with mental disorders is incalculable. Many of these disorders are lifelong and cross generations; they also affect neighbours, friends, and beyond in a ripple of concentric circles. A striking example of the effect on family members is the association between maternal depressive symptoms and underweight and stunting in children reported in many countries.4 The resolution for mental health, led by India, the USA, and Switzerland, is the result of a crescendo of political support for addressing mental illnesses and received unanimous support from countries on the WHO Executive Board. The resolution urges countries to protect and promote the rights of persons with mental disorders and to combat stigma against mental illness. Crucially, it prioritises the integration of mental health services within primary care and calls for the development of a plan that will address both health and social services, while seeking key involvement from people with mental disorders in its planning. This resolution is also a necessary first step to bringing mental, neurological, and substance use disorders to the highest level of discussion—a UN General Assembly Special Session.5 Once the resolution is adopted by the World Health Assembly in May 2012, WHO will develop a mental health action plan to be approved by UN member states in 2013. Once approved, this action plan will lead to further resource allocation for mental health. In developing this action plan, we recommend that WHO undertake in-person country and regional consultations to properly assess the needs of people with mental disorders in diverse geographical, cultural, and financial contexts. WHO should also emphasise holistic recovery, including physical, mental, and social wellbeing, and involve relevant social sectors while developing the action plan. Over the past decade, public mental health research has yielded a robust evidence base for interventions on the level of the individual, family, school, community, and nation. Although there is a plethora of evidence on efficacious mental health interventions, little of this evidence has been disseminated or implemented. Studies have demonstrated the merits of screening for depression in primary care;6,7 however, such integration has yet to become routine practice, even in high-income countries. While community-based treatment and recovery services often lie at the intersection of various domains, there is an absence of coordinated care for service users. Individuals living with mental illness not only need pharmaco-therapy, but also effective psychosocial interventions and access to education, employment, and housing. We urge UN member states to safeguard the human rights of persons with mental disorders and go a step further by empowering those who are mentally ill and involving them at all stages of decision making. In this regard, much can be learned from successful advocacy efforts to combat the HIV/AIDS pandemic. Largely because of leadership by people living with HIV/AIDS, there have been significant reductions in mother-to-child transmission, millions more are able to access antiretroviral medications, and new infections have decreased in many countries.8 Understanding this history, we call for the outcomes of the resolution for global mental health to be based heavily on the knowledge, creativity, and experiences of those directly affected by mental illness. Charlene Sunkel, a South African advocate and person living with schizophrenia, underscores the importance of collaboration between health professionals and service users, as exemplified by the EMPOWER9 project and the Guateng Consumer Advocacy Movement in South Africa.10 We encourage service users to engage with their ministries of health, as well as WHO country and regional offices. We call for a coordinated response to this resolution by all interested parties, including WHO, UN member states, service users, and caregivers, as well as civil society groups. At present, one fifth of countries allocate less than 1% of their health budgets to mental health care, while mental, neurological, and substance-use disorders account for a far greater share of the social and financial costs of health problems.2 Let us capitalise on the momentum generated by this resolution and ensure that the world proportionately prioritises mental health.

Mental Illness as an Independent Risk Factor for Unintentional Injury and Injury Recidivism

Twelve percent of Americans are diagnosed and treated for mental illness annually. The relationship between mental illness and intentional injuries such as assault and suicide has previously been described. However, unintentional injury among mentally ill adults has not been characterized. The purpose of this study was to identify relationships between mental illness diagnosis and unintentional injury. We hypothesized that diagnosed mental illness is an independent risk factor for unintentional injury and it increases the risk of recidivism. In this retrospective cohort study, trauma registry data, medical records, and outpatient mental health care data from the San Francisco Department of Public Health Billing Information System (BIS) were used to identify patients admitted with unintentional injury at a Level I urban trauma center in 2003 and 2004. Data collected included mechanism of injury, patient outcome and disposition, mental health diagnoses, substance abuse history, presence of homelessness, number of repeat injury events, and outpatient mental health treatment history. The incidence of unintentional injury requiring admission to a trauma center and the risk of intentional injury recidivism in subjects with a mental illness diagnosis were compared with those in subjects without a mental illness diagnosis. The risk of recidivism in those who had received publicly funded outpatient treatment before their injury was also evaluated. Of the 1,709 patients admitted for unintentional injury, 20% had a diagnosis of mental illness. Individuals with mental illness had twice the rate of unintentional injury requiring admission (2.2-2.4 people in 1,000 vs. 1.0-1.1 in 1,000) and 4.5 times the odds of injury recidivism (odds ratio [OR] = 4.5, 95% confidence interval [CI] 3.3-6.1) as those who did not have a mental illness diagnosis. Mental illness was a more robust predictor of injury recidivism than substance abuse (OR = 3.2, 95% CI 2.3-4.3) or homelessness (OR = 2.3, 95% CI 1.5-3.4). Compared with the nonmentally ill group, subjects with mental illness had a longer hospital stay and were less likely to be discharged home. Also, their injuries were more likely the result of falling or being hit by cars, and less likely the result of motor vehicle collisions than subjects without mental illness. Mental illness is an independent risk factor for unintentional injury and injury recidivism. Individuals with mental illness also have a different pattern of injury and hospitalization. They tended to suffer from different mechanisms of injury, stayed in the hospital longer, and were more likely to be discharged to a skilled nursing facility. Recognition of mental illness as a risk factor for injury may prompt re-examination of resource allocation for mental health and injury prevention and highlights the mentally ill as a prime target population for unintentional injury prevention efforts.

Towards a Needs Based Mental Health Resource Allocation and Service Development in Rural and Remote Australia

To develop a transparent, needs-based mental health resource allocation framework to guide area level service planning in rural and remote settings. Using the Central Australian mental health service region as a case study, a five-step approach was used to analyse and gather relevant data as follows: (i) mapping a regional sociodemographic profile; (ii) estimating the expected level of mental illness within the regional population; (iii) estimating the expected level of specialist mental health service usage; (iv) estimating the expected categories of specialist mental health care required for the regional population; (v) making adjustments to the costs of providing specialist mental health care on the basis of demographic features of the region. These data were then matched with the availability, access and cost of specialist mental health care currently provided at the regional level. The capacity of specialist mental health care in Central Australia was below the expected benchmark for the population residing in this region. The region required approximately double the existing funding allocation to provide an adequate and equitable level of care that meets the needs of the diverse population groups. Children and adolescents were the group most in need, as were adult Aboriginal people living in remote settings. The framework described provides the beginnings of more open and transparent evidence-based decision-making regarding mental health resource allocation and service development for rural and remote residents.

Towards a needs based mental health resource allocation and service development in rural and remote Australia

Objective: To develop a transparent, needs-based mental health resource allocation framework to guide area level service planning in rural and remote settings.Methods: Using the Central Australian mental health service region as a case study, a five-step approach was used to analyse and gather relevant data as follows: (i) mapping a regional sociodemographic profile; (ii) estimating the expected level of mental illness within the regional population; (iii) estimating the expected level of specialist mental health service usage; (iv) estimating the expected categories of specialist mental health care required for the regional population; (v) making adjustments to the costs of providing specialist mental health care on the basis of demographic features of the region. These data were then matched with the availability, access and cost of specialist mental health care currently provided at the regional level.Results: The capacity of specialist mental health care in Central Australia was below the expected ben...