Benchmarks for Needed Psychiatric Beds for the United States: A Test of a Predictive Analytics Model.

The ideal balanced mental health service system presupposes that planners can determine the need for various required services. The history of deinstitutionalization has shown that one of the most difficult such determinations involves the number of needed psychiatric beds for various localities. Historically, such assessments have been made on the basis of waiting and vacancy lists, expert estimates, or social indicator approaches that do not take into account local conditions. Specifically, this study aims to generate benchmarks or estimated rates of needed psychiatric beds for the 50 U.S. states by employing a predictive analytics methodology that uses nonlinear regression. Data used were secured primarily from the U.S. Census' American Community Survey and from the Substance Abuse and Mental Health Administration. Key predictors used were indicators of community mental health (CMH) service coverage, mental health disability in the adult population, longevity from birth, and the percentage of the 15+ who were married in 2018. The model was then used to calculate predicted bed rates based on the 'what-if' assumption of an optimal level of CMH service availability. The final model revealed an overall rate of needed beds of 34.9 per 100,000 population, or between 28.1 and 41.7. In total, 32% of the states provide inpatient psychiatric care at a level less than the estimated need; 28% at a level in excess of the need; with the remainder at a level within 95% confidence limits of the estimated need. These projections are in the low range of prior estimates, ranging from 33.8 to 64.1 since the 1980s. The study demonstrates the possibility of using predictive analytics to generate individualized estimates for a variety of service modalities for a range of localities.

The impact of geographic isolation on mental disability in the United States.

Geographic isolation has long been hypothesized to have a role in the origins and development of mental disabilities. A considerable body of research has established such a correlation. However, study designs have limited researchers' ability to establish a causal connection and rule out rival hypotheses. This study, therefore, aims to assess the strength of the geographic isolation - mental disability relationship and to disentangle it from alternative possibilities, namely that it reflects socioeconomic status, social isolation, economic inequality, or reverse causation. The study employs an analysis of variations in the rates of mental disability throughout 2960 U.S. counties using both Census and CDC data. In addition to partial correlation and ordinary least square analyses, the study employs two-stage least squares regression with instrumental variables (2SLS-IV), a procedure that permits resolution of the problem of endogeneity involving the potential effects of unmeasured variables and reverse causation. Results reveal that the initial bivariate effects of geographic isolation on rates of mental disability are robust after controls for socioeconomic status, income inequality, social isolation, and other predictors are introduced and when tested with the 2SLS-IV procedure. Most variation (54.4%) in county mental disability rates is accounted for by the independent effects of geographic isolation, socioeconomic status, income inequality, and other variables. The results presented, although not conclusive, supports more targeted service planning and more equitable resource investments in rural parts of the United States and other nations.

Deinstitutionalization of mental hospitals and rates of psychiatric disability: An international study.

This study tests several hypotheses regarding the impact of deinstitutionalization of inpatient care on levels of psychiatric disability. It employs a secondary analysis of existing datasets from the World Health Organization's mental health program, the Global Burden of Disease study, as well as supplemental datasets on the national environments examined. The primary model accounts for 87.1% of the variation in global disability levels, but only a quarter or 28.3% of the recent changes in these levels between 1990 and 2015. One of the most important predictors of declines in mental disability is the proportion of a nation's health budget that is invested in mental health services.

Formation of metallacarboxylic acids through Hieber base reaction. A density functional theory study.

Using density functional theory (B97-D/ECP2/PCM//RI-BP86/ECP1 level), we have studied the effects of ligand variation on OH- uptake by transition-metal carbonyls (Hieber base reaction), i.e., LnM(CO) + OH- → [LnM(CO2H)]-, M = Fe, Ru, Os, L = CO, PMe3, PF3, py, bipy, Cl, H. The viability of this step depends notably on the nature of the co-ligands, and a large span of driving forces is predicted, ranging from ΔG = -144 kJ/mol to +122 kJ/mol. Based on evaluation of atomic charges from natural population analysis, it is the ability of the co-ligands to delocalize the additional negative charge (through their π-acidity) that is the key factor affecting the driving force for OH- uptake. Implications for the design of new catalysts for water gas shift reaction are discussed. Graphical abstract ᅟ.

Five-year rehospitalization experience of a state-wide cohort of persons with schizophrenia.

PURPOSE: This study has the objective of assessing the psychiatric rehospitalization experience of a large cohort of persons with schizophrenia and modeling the effects of personal and systemic conditions on rehospitalization risk. METHODS: The study employs a secondary analysis of US data from Massachusetts' casemix database of all patients discharged from acute general hospital units. It focuses on 11,291 patients during 1994-2000 who were discharged from acute adult psychiatric units. Predictors used include basic demographics, length of stay, continuity of care with doctors and facilities, diagnoses, discharge referral, type of insurance, and distance to and selected socioeconomic characteristics of the patient's home zip code. Data are analyzed with descriptive statistics and modeled with the Cox proportional hazard model. The model was assessed through split-half reliability testing, the generalized R2, and Harrell's Concordance Index. RESULTS: Overall, 13.4% of patients were rehospitalized within 1 month; 38.9% within 1 year; and 64.1% within 5 years. Predictors that are most strongly associated with lower rehospitalization rates include continuity of care, discharge to a chronic hospital, and density of home zipcode, whereas discharge to another acute psychiatric unit had the greatest effect on increasing risk of rehospitalization. Overall the Cox model has generalized R2 of 0.343 and a Concordance Index of 0.734. CONCLUSIONS: The results highlight the need to enhance the continuity of the relationships with providers, whether these are with the assigned psychiatrists or other therapists and case managers, as well as workplace issues involving staff turnover and hospital assignment and admitting policies.

Behavioral Mental Health: An Emerging Field of Service or an Oxymoron?

Proliferation in the use of the terminology around behavioral mental health suggests, on one hand, an emerging field of service that integrates psychiatric, substance abuse, and related services. On the other hand, this development also raises questions about the coherence of this approach. This review explores the history, definitional issues, current trends, and available data on the impact of this field. It considers a variety of critiques of behavioral mental health, such as possibility that the field attempts to integrate fundamentally incompatible domains, that the term "behavioral mental health" is thus an oxymoron, and that it represents a co-optation by the insurance industry of traditional ideals of mental health and of behavioral medicine or as code for the implementation of a medical model that emphasizes short-term, behavioral, and psychopharmacological treatments at the expense of a truly biopsychosocial orientation. Other concerns include the focus on individual change and the effectiveness of behavioral health as a strategy for destigmatizing mental health. Recommendations for addressing the various barriers to realizing the ideals of behavioral mental health include revamping the role of managed care in oversight of treatment decisions, broadening the implementation of evidence-based treatment, and the development of treatment models that build on traditional social work practice models.

Sustainability at the edge of chaos: its limits and possibilities in public health.

This paper critically reviews the expanding literature on applications of sustainability to healthcare policy and planning. It argues that the concept has been overgeneralized and has become a buzzword masking disparate agendas. It ignores the insights of the newest generation of systems theory on complex systems on the ubiquity of far-from-equilibrium conditions. Yet, a central meaning often ascribed to sustainability is the level continuation of healthcare programs and their institutionalization. Sustainability is only coherent in health care when it is more narrowly delimited to involve public health and treated as only one of several evaluative criteria that informs not only the continuation of programs but more often their expansion or contraction as needs dynamically change.

Modeling the geographic distribution of serious mental illness in New Zealand.

PURPOSE: This study aims to estimate, apply, and validate a model of the risk of serious mental illness (SMI) in local service areas throughout New Zealand. METHODS: The study employs a secondary analysis of data from the Te Rau Hinengaro Mental Health Survey of 12,992 adults aged 16 years and over from the household population. It uses small area estimation (SAE) methods involving: (1) estimation of a logistic model of risk of SMI; (2) use of the foregoing model for computing estimates, using census data, for District Board areas; (3) validation of estimates against an alternative indicator of SMI prevalence. RESULTS: The model uses age, ethnicity, marital status, employment, and income to predict 92.2 % of respondents' SMI statuses, with a specificity of 95.9 %, sensitivity of 16.9 %, and an AUC of 0.73. The resulting estimates for the District Board areas ranged between 4.1 and 5.7 %, with confidence intervals from ±0.3 to ±1.1 %. The estimates demonstrated a correlation of 0.51 (p = 0.028) with rates of psychiatric hospitalization. CONCLUSIONS: The use of SAE methods demonstrated the capacity for deriving local prevalence rates of SMI, which can be validated against an available indicator.

Disparities in the geography of mental health: implications for social work.

This article reviews recent theory and research on geographic disparities in mental health and their implications for social work. It focuses on work emerging from the fields of mental health geography, psychiatric epidemiology, and social work, arguing that a wide range of spatial disparities in mental health are important to understand but that of greatest relevance are inequities, or disparities, that violate fundamental norms of fairness and social justice. Research is reviewed on geographic variations in subjective well-being and mental health, on personality (using the five-factor model), and on psychopathology as well as several studies on the disparate implementation of mental health policy and services. Critical is the need to simultaneously assess, on the one hand, differential patterns of mental health conditions and, on the other, the services and policies designed to address them--the fact that considering only one dimension often leads to unintended consequences. Many of the most outstanding disparities have been found to exist at the local level, between towns and neighborhoods, and are based on socioeconomic conditions. This review concludes by discussing the implications of geographic disparities in mental health for allocation decisions and for social work practice, including decisions about the most efficacious mix of services at both the community and clinical practice levels.

Declines in mental illness over the adult years: an enduring finding or methodological artifact?

OBJECTIVES: Epidemiological surveys have revealed dramatic declines in the prevalence of serious mental illness (SMI) as adults age. Analyses of these datasets have not determined whether this is attributable, on one hand, to declining incidence, shorter duration of condition, and lesser severity with age, or on the other hand, confounding variables and methodological biases. This study, thus, aims to test several such competing hypotheses. METHODS: This study employs a secondary analysis of data from the 2001/2002 US National Comorbidity Replication Survey of 9282 adults, 18 and older, living in the household population of the 48 contiguous states, as well as supplemental datasets from Israel, New Zealand, and other sources. RESULTS: One-year SMI prevalence rates in the US drop from 8.0% of adults 18-29 to 1.4% of the 65+, and to similar degrees in Israel and New Zealand. The drop in the US can be explained by the early onset of most mental illnesses, and declines in both incidence and duration of condition with age. Comorbidity also drops with age; however, the remaining diagnoses show a gradually increasing severity. Institutionalization explains a small portion of the declines, as does premature mortality of the seriously mentally ill that accounts for 16.3% of the decline. CONCLUSION: The results reveal that a substantial portion of the declines are explainable in terms of declining incidence and improving recovery rates, with some reduction also attributable to institutionalization and premature mortality which removes some older and more seriously disabled adults from the epidemiological survey populations.

Disparities in the geography of serious mental illness in Israel.

OBJECTIVE: The aim of this research is to test and apply a model of the disparities and variations in serious mental illness (SMI) to estimating prevalence in local areas throughout Israel. METHODS: This study employs a secondary analysis of data from the 2003/2004 Israel National Health Survey of 4859 adults aged 21 and over from the household population of legal residents and citizens. It uses small area estimation methods (SAE), specifically to: (i) estimate and test a multivariate logistic model of disparities in the risk of serious mental illness; (ii) use the foregoing model for computing estimates, using census data, for local areas; (iii) validate these estimates against the rate of psychiatric hospitalizations. RESULTS: The model uses standard demographic and socioeconomic variables to successfully predict 92.5% of respondents' statuses as SMI, with a sensitivity of 26.9%, specificity of 95.9%, and an AUC index of .797. The resulting estimates of the percentage of adults with an SMI in the 16 subdistricts ranged between 3.7% and 7.7%, with a national mean of 5.0%. The estimates have a partial correlation of .63 with rates of psychiatric hospitalization in Jewish localities, but elevated rates have not been validated in Arab localities. CONCLUSION: The use of small area estimation methods demonstrated the capacity for deriving local prevalence rates of serious mental illness, ones that can be validated against psychiatric hospitalization for the majority population group in Israel.

A comparison of acute psychiatric care under Medicaid carve-outs, HMOs, and fee-for-service.

This study compares the use of acute psychiatric hospitalization; selected outcomes, including rehospitalization; as well as costs associated with the health maintenance organization (HMO), carve-out, and fee-for-service models as implemented in the Massachusetts Medicaid program between FY1994 and FY2000. This is a longitudinal analysis that primarily uses unduplicated individual data from the Massachusetts Case Mix database. Analyses focus on 56,518 individuals who were psychiatrically hospitalized on acute units within 57 hospitals. They employ Cox regression to compare rehospitalization among the three programs. The hypotheses were strongly supported: HMOs have the most substantial impacts in minimizing service provision, with the carve-out program having an impact intermediate between the HMO and fee-for-service programs. Lower utilization rates were associated with lower overall rates of hospitalization, shorter lengths of stay, fewer repeated stays, and less geographic access and greater displacement of psychiatric patients to medical units. The final model of rehospitalization has an overall predictive accuracy of 59.6%.

The geography of adult homelessness in the US: Validation of state and county estimates.

This study models geographic variations in the US in lifetime occurrence of homelessness, length of homeless experience, and point-in-time estimates based on socioeconomic, demographic, and disability indicators, among 13,931 respondents in the National Comorbidity Replication and the National Latino Asian American surveys. It uses a small area estimation methodology to estimate county and state levels of homelessness. This study demonstrates high validity for the state estimates, but not for counties. Overall, the model generates a point-in-time estimate of adult homeless persons at 377,000, and an adult lifetime rate of 4.7% of the household adult population.

A predictive model of the development of national mental health systems.

BACKGROUND: An emerging body of research in the field of international mental health, in part stimulated by the World Mental Health Survey Initiative, has made only limited progress in understanding variations in levels of development in mental health services across nations. However, the World Health Organization's recent initiatives involving the Assessment Instrument for Mental Health Systems (WHO-AIMS) and its publication of the Mental Health Atlas now present new opportunities for understanding transnational mental health policy development. AIMS OF THE STUDY: This study, thus, aims to increase understanding of the dimensions and conditions associated with the differential levels of development of national mental health. Specifically, it addresses two questions: Are there one or multiple dimensions characteristic of this development? What are the relative contributions of demographic, economic, political, social, cultural, and geographic conditions in predicting the levels of various nations on these dimensions? METHODS: This study employs a secondary analysis of existing data derived from both WHO's Mental Health Atlas and other archival sources to address the above questions. Analyses of patterns of missing data supported decisions to restrict the sample to 138 nations. The first question on dimensions of development was addressed with a Varimax factor analysis using a matrix of polychoric, tetrachoric, and Pearson correlations. Factor scores were calculated for the resulting three factors, and to address the second question on predictors, these were each analyzed with multiple regression models. RESULTS: Three orthogonal or uncorrelated dimensions were identified that are characteristic of the 138 nations: (i) General Mental Health Services (professionals and inpatient beds), (ii) Public Mental Health Program; and (iii) Community Mental Health that collectively accounted for 45% of the variance in the database of WHO predictors. Only one, General Mental Health Services, was substantially explained (Adj. R2 = .641) by the predictors, specifically, by democratization, distance from Paris, gross domestic product, and Inglehart's measure of self-expression (versus survival) values. DISCUSSION: This analysis reveals a complexity and diversity of developmental patterns that are not apparent in statistical results that have been previously reported. Specifically, these results show that there is no unilinear pathway of development or of associated environmental conditions, but rather national mental health systems vary dramatically in respect to three dimensions -- General Mental Health Services, Public Mental Health Programs, and Community Mental Health -- which are unrelated to one another. IMPLICATIONS FOR HEALTH POLICY: The multiple dimensions of mental health development identified in this study reinforce the importance of a multi-pronged strategy for the continuation of multiple developmental efforts. Mental health manpower development, including both education and training, regulation and standard setting, public mental health services, both inpatient and the range of community mental health services, are among some of the most vital elements of a comprehensive strategy on the part of both national and international authorities IMPLICATIONS FOR FURTHER RESEARCH: Limitations of this study that include the unknown reliability and validity of the WHO Mental Health Atlas data suggest the need for such data collection initiatives to utilize multiple informants for each nation. As better data is gathered, it will become increasingly feasible to undertake multi-level studies of variations not only between nations, but within them.

Validation of a model for estimating state and local prevalence of serious mental illness.

This study addresses an ongoing problem in mental health needs assessment. This involves estimating the prevalence of an identified problem, specifically serious mental illness (SMI), for local areas in a reliable, valid, and cost-effective manner. The aim of the study is the application and testing of a recently introduced methodology from the field of small area estimation to determining SMI rates in the 48 contiguous US states, and in local areas of Massachusetts. It uses 'regression synthetic estimation fitted using area-level covariates', to estimate a model using data from the 2001-2002 replication of the National Comorbidity Study (n = 5593) and apply it, using 2000 STF-3C Census data, to various state and local areas in the United States. The estimates are then compared with independently collected SMI indicators. The estimates show not only face validity and internal consistency, but also predictive validity. The multiple logistic model has a sensitivity of 21.1% and a specificity of 95.1%, based largely on socio-economic disparities. Pearson r validity coefficients for the area estimates range from 0.43 to 0.75. The model generates a national estimate of SMI adults of 5.5%; for the 48 states, rates ranging from 4.7% to 7.0%; and for Massachusetts towns and cities, 1.1% to 7.5%.

Patterns of acute psychiatric hospitalization in Massachusetts.

This study identifies long-term patterns of patient utilization in acute hospitals in Massachusetts based on the 47,787 psychiatric patients. Cluster analyses are used to identify six patterns of hospitalization based on the number and length of episodes, variety of institutions, length of stay, and time between stays. The study demonstrates that while the 74% of one-time patients with short stays use only a fifth (18.0%) of the bed days, the highest users were not the long-term users, but instead the 22.9% occasional extended-stay patients who use 70.0% of the total bed days. The study also finds that extending the length of the initial stay has little impact on limiting subsequent hospitalization.

Socioeconomic status and mental illness: tests of the social causation and selection hypotheses.

This study tests several hypotheses about the underlying causal structure of the inverse correlation between socioeconomic status (SES) and mental illness. It does this through the analysis of a longitudinal statewide database on acute psychiatric hospitalization in Massachusetts for the fiscal years 1994-2000 as well as supplemental census data. The modeling strategy used techniques of structural equation modeling and found that SES impacted directly on rates of mental illness as well as indirectly through the impact of economic hardship on low and middle income groups.

Trends in acute psychiatric inpatient care in Massachusetts.

This report presents the preliminary results of a longitudinal study of acute psychiatric hospitalization in the Commonwealth of Massachusetts for fiscal years 1994 to 2000. The study was a secondary analysis of data obtained through the Commonwealth's mandated case-mix reporting system, covering 42 acute psychiatric facilities and 119,284 patients. Results include a 58.4 percent increase in the patient population, accompanied by declines in both length of stay and readmission rates; increases in the number of diagnoses of depression and in the number of patient deaths; and shifts to an older population increasingly supported by Medicaid and Medicare, especially managed care programs.