A spatial needs assessment of indigent acute psychiatric discharges in California

Sociodemographic Correlates of Affordable Community Behavioral Health Treatment Facility Availability in Florida: A Cross-Sectional Study

Behavioral health disorders such as mental disorders (MD) and substance use disorders (SUD) are epidemics in the US; however, the availability of treatment and prevention services remains low. This study assessed neighborhood-level sociodemographic attributes to characterize the availability of behavioral health treatment facilities in Florida. The American Community Survey and SAMHSA's Behavioral Health Treatment Locator were used to identify behavioral health treatment facilities in Florida and calculate their density by census tract. Spatial lag regression models were used to assess census tract-level correlates of facility density for 390 MD treatment facilities, 518 SUD facilities, and subsets of affordable MD and SUD facilities. Behavioral health treatment facility density was negatively associated with rurality and positively associated with the proportion of non-Latino Black, Latino, insured, and college-educated populations. Stark rural-urban disparities in behavioral health treatment availability present opportunities to prioritize telehealth and mobile interventions and improve treatment utilization.

Mental Health Care Access Using Geographic Information Systems: An Integrative Review

A decade after the Mental Health Parity and Addiction Equity Act was implemented to ensure access to mental health and substance abuse services for U.S. citizens, accessing mental health care still is problematic for many needing services. More than 123 million Americans reside in federally-designated Mental Health Professional Shortage Areas (MHPSA) compared to 84 million living in similarly-designated primary care shortage areas and 62 million in dental health shortage areas. Health professional shortage areas are geographic areas that have a shortage of primary medical, dental, or mental health providers. Geographic Information Systems (GIS) with spatial analysis approaches provide tools to understand the ever-changing distribution of health care, outcomes, and delivery to improve care. The aim of this integrative review is to describe and synthesize the literature on GIS approaches to improve access to mental health care services. GIS Bibliography, PubMed, CINAHL, PsycINFO, Academic Search Premier, Social Sciences Citation Index, and Oalster were searched for articles between January 1, 1998 and January 1, 2018 that met established inclusion/exclusion criteria. Among the 138 articles reviewed, 18 met criteria and were included in the review. GIS approaches to improve access to mental health care can be categorized as (1) type of care (integrated, community), (2) contributions to access (distance, time, cost, perception of traveling, inequalities), and (3) the utilization of services. Results from the literature suggest closer examination of measures used to assess geographic variations in accessibility is needed for ultimately improving quality of care for people in MHPSA.

Disability concentration and access to rehabilitation services: a pilot spatial assessment applying geographic information system analysis

Purpose: Due to geographical disparities, many people with profound or severe disabilities experience considerable delays in rehabilitation treatment, resulting in threats to quality of life. This pilot study aims to identify areas in Greater Brisbane, Australia, with a higher concentration of people with profound or severe disabilities and to evaluate access to rehabilitation services in these areas. Methods: Data came from the 2016 Australian Census of Population and Housing and the National Health Services Directory. Four frequently used rehabilitation services by individuals with profound or severe disabilities (i.e., occupational therapy, physiotherapy, speech pathology and psychology) were the focus of the analysis. The data were analyzed using geospatial analysis methods (e.g., spatial scan statistic and network analysis). Results: A higher concentration of rehabilitation services was found in the regions with lower disability prevalence and lower potential demand for rehabilitation services. In contrast, the regions with higher disability prevalence and higher potential demand for rehabilitation services experienced poorer access to rehabilitation services. Conclusion: The findings are expected to inform policy decisions about the prioritization of rehabilitation resources and derive evidence for planning more responsive service delivery. Implications for rehabilitation The current study has demonstrated the utilization of geographic information system methods to facilitate rehabilitation service planning. Identification of disability concentration may inform locally responsive rehabilitation service delivery. Spatial assessment of mismatch between supply and potential demand may assist policy makers and service providers in the prioritization of rehabilitation resources. The current study contributes to the World Health Organization's call for action to ensure adequate access to rehabilitation services by people with profound or severe disabilities.

Evidence-Based Program Service Deserts: A Geographic Information Systems (GIS) Approach to Identifying Service Gaps for State-Level Implementation Planning

The long term effects of untreated mental health need for individuals, families and society has prompted a number of federal policy statements encouraging the use of evidence-based programs (EBP) in children's healthcare. However, among other challenges of evidence-based practice implementation, states often do not know where to make investments based on population need. In this paper we present the use of a Geographic Information System approach to undertake a mental health needs assessment for Washington State. Our study found that this technology can be beneficially applied to conducting needs assessment for EBP implementation, and we provide recommendations for future applications.

Spatial patterns of epilepsy-related emergency department visits in california

Background

Socio-demographic factors are associated with increased emergency department (ED) use among patients with epilepsy. However, there has been limited spatial analysis of such visits.

Design and methods

California ED visit at the patient ZIP Code level were examined using Kulldorf’s spatial scan statistic to identify clusters of increased risk for epilepsy-related visits. Logistic regression was used to examine the relative importance of patient socio-demographics, Census-based and hospital measures.

Results

During 2009-2011 there were 29,715,009 ED visits at 330 hospitals, of which 139,235 (0.5%) had epilepsy (International Classification of Disease-9 345.xx) as the primary diagnosis. Three large urban clusters of high epilepsy-related ED visits were centred in the cities of Los Angeles, Oakland and Stockton and a large rural cluster centred in Kern County. No consistent pattern by age, race/ethnicity, household structure, and income was observed among all clusters. Regression found only the Los Angeles cluster significant after adjusting for other measures.

Conclusions

Geospatial analysis within a large and geographically diverse region identified a cluster within its most populous city having an increased risk of ED visits for epilepsy independent of selected socio-demographic and hospital measures. Additional research is necessary to determine whether elevated rates of ED visits represent increased prevalence of epilepsy or an inequitable system of epilepsy care.

Medication deserts: survey of neighborhood disparities in availability of prescription medications

Background

Only a small amount of research has focused on the relationship between socio-economic status (SES) and geographic access to prescription medications at community pharmacies in North America and Europe. To examine the relationship between a community’s socio-economic context and its residents’ geographic access to common medications in pharmacies, we hypothesized that differences are present in access to pharmacies across communities with different socio-economic environments, and in availability of commonly prescribed medications within pharmacies located in communities with different socio-economic status.

Methods

We visited 408 pharmacies located in 168 socio-economically diverse communities to assess the availability of commonly prescribed medications. We collected the following information at each pharmacy visited: hours of operation, pharmacy type, in-store medication availability, and the cash price of the 13 most commonly prescribed medications. We calculated descriptive statistics for the sample and fitted a series of hierarchical linear models to test our hypothesis that the in-stock availability of medications differs by the socio-economic conditions of the community. This was accomplished by modeling medication availability in pharmacies on the socio-economic factors operating at the community level in a socio-economically devise urban area.

Results

Pharmacies in poor communities had significantly higher odds of medications being out of stock, OR=1.24, 95% CI [1.02, 1.52]. There was also a significant difference in density of smaller, independent pharmacies with very limited stock and hours of operation, and larger, chain pharmacies in poor communities as compared to the middle and low-poverty communities.

Conclusions

The findings suggest that geographic access to a neighborhood pharmacy, the type of pharmacy, and availability of commonly prescribed medications varies significantly across communities. In extreme cases, entire communities could be deemed “medication deserts” because geographic access to pharmacies and the availability of the most prescribed medications within them were very poor. To our knowledge, this study is first to report on the relationship between SES and geographic access to medications using small area econometric analysis techniques. Our findings should be reasonably generalizable to other urban areas in North America and Europe and suggest that more research is required to better understand the relationship of socio-economic environments and access to medications to develop strategies to achieve equitable medication access.

Inpatient charges and mental illness: Findings from the Nationwide Inpatient Sample 1999-2007

Inpatient costs related to mental illness are substantial, though declining as a percentage of overall mental health treatment costs. The public sector has become increasingly involved in funding and providing mental health services. Nationwide Inpatient Sample data for the years 1999–2007 were used to: 1) examine Medicare, Medicaid, and private insurance charges related to mental illness hospitalizations, including trends over time; and 2) examine trends in mental comorbidity with physical illness and its effect on charges. There were an estimated 12.4 million mental illness discharges during the 9-year period, with Medicare being the primary payer for 4.3 million discharges, Medicaid for 3.3 million, private insurance for 3.2 million, and 1.6 million for all other payers. Mean inflation-adjusted charges per hospitalization were US$17,528, US$15,651, US$10,539, and US$11,663, respectively. Charges to public sources increased for schizophrenia and dementia-related discharges, with little private/public change noted for mood disorders. Comorbid mood disorders increased dramatically from 1.5 million discharges in 1999 to 3.4 million discharges in 2007. Comorbid illness was noted in 14.0% of the 342 million inpatient discharges during the study period and was associated with increased charges for some medical conditions and decreased charges for other medical conditions.

Using population attributable risk to understand geographic disease clusters

This paper describes the use of population attributable risk percent (PAR%) in the study of morbidity and mortality clusters, and in particular, shows how this method of risk characterization can usefully distinguish between multiple geographic clusters of potential interest. Incident lung cancer data in persons 60 years and over from the province of Ontario, Canada, are analyzed for spatial clusters, and each cluster is characterized in terms of statistical significance, relative risk and PAR%. We observe that although relative risk is probably highest in Northern Ontario, highest PAR% is in Eastern Ontario, and in particular, the Ottawa area. These results illustrate the usefulness of attributable risk as a metric to help characterize and understand spatial clusters, which could be important for place-based public health interventions.