Needs assessment in mental health service planning

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 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.

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%.

Keeping mental health reform on course: selecting indicators of mental health system performance

Mental health reform was introduced as a public-sector policy response to identified deficiencies in the mental health services system. The reform agenda, which is underway in most provinces/territories, calls for greater accountability to mental health consumers, their families, and other stakeholders. This paper summarizes the major policy goals (which are the cornerstones of mental health reform) and suggests a series of high-level indicators to assess performance toward achieving these goals. Issues in the selection and measurement of performance indicators as markers of key goals are discussed. The proposed indicator set, while not a comprehensive framework, can provide a multi-dimensional appraisal of mental health system performance and help keep reform on course.

Predicting level of mental health care among children served in a delivery system in a rural state

The purpose of this study was to establish benchmark data to assist in identifying factors associated with mental health service needs and level of care for children living in a rural state. Clinical and psycho-social needs and strengths were assessed using retrospective chart review for all children and adolescents (n=150) with symptoms or a diagnosis of reactive attachment disorder who presented to a comprehensive treatment facility between January 1997 and December 1999. Logistic regression was used to predict factors associated with inpatient admission (n=15) vs. community-based care (n=135). Significant individual contributors to the prediction of inpatient care were more limited clinical/psycho-social strengths, history of inpatient use and history of sexual abuse. Although 80 percent of children admitted to inpatient care had a history of hospitalization, two-thirds had no history of receiving community-based services and presented to current treatment with a two-year or longer history of symptoms. Approximately two-thirds of children admitted to inpatient care had a history of sexual abuse; however, one-third of these children had no history of mental health service use and presented to current treatment with a two-year or longer history of symptoms. Findings raise concerns about current efforts in public health education, community awareness and health prevention and early intervention programs for children with mental/behavioral health challenges and children and families at risk for abuse and/or neglect living in rural areas.