County variation in use of inpatient and ambulatory psychiatric care in New York State 1999–2001: Need and supply influences in a structural model

Mental health service areas in Switzerland

OBJECTIVES

Small area analysis is a health services research technique that facilitates geographical comparison of services supply and utilization rates between health service areas (HSAs). HSAs are functionally relevant regions around medical facilities within which most residents undergo treatment. We aimed to identify HSAs for psychiatric outpatient care (HSA-PSY) in Switzerland.

METHODS

We used HSAr, a new and automated methodological approach, and comprehensive psychiatric service use data from insurances to identify HSA-PSY based on travel patterns between patients' residences and service sites. Resulting HSA-PSY were compared geographically, demographically and regarding the use of inpatient and outpatient psychiatric services.

RESULTS

We identified 68 HSA-PSY, which were reviewed and validated by local mental health services experts. The population-based rate of inpatient and outpatient service utilization varied considerably between HSA-PSY. Utilization of inpatient and outpatient services tended to be positively associated across HSA-PSY.

CONCLUSIONS

Wide variation of service use between HSA-PSY can hardly be fully explained by underlying differences in the prevalence or incidence of disorders. Whether other factors such as the amount of services supply did add to the high variation should be addressed in further studies, for which our functional mapping on a small-scale regional level provides a good analytical framework.

The relationship between area levels of involuntary psychiatric care and patient outcomes: a longitudinal national register study from Norway

BACKGROUND

Mental health legislation permits involuntary care of patients with severe mental disorders who meet set legal criteria. The Norwegian Mental Health Act assumes this will improve health and reduce risk of deterioration and death. Professionals have warned against potentially adverse effects of recent initiatives to heighten involuntary care thresholds, but no studies have investigated whether high thresholds have adverse effects.

AIM

To test the hypothesis that areas with lower levels of involuntary care show higher levels of morbidity and mortality in their severe mental disorder populations over time compared to areas with higher levels. Data availability precluded analyses of the effect on health and safety of others.

METHODS

Using national data, we calculated standardized (by age, sex, and urbanicity) involuntary care ratios across Community Mental Health Center areas in Norway. For patients diagnosed with severe mental disorders (ICD10 F20-31), we tested whether lower area ratios in 2015 was associated with 1) case fatality over four years, 2) an increase in inpatient days, and 3) time to first episode of involuntary care over the following two years. We also assessed 4) whether area ratios in 2015 predicted an increase in the number of patients diagnosed with F20-31 in the subsequent two years and whether 5) standardized involuntary care area ratios in 2014-2017 predicted an increase in the standardized suicide ratios in 2014-2018. Analyses were prespecified (ClinicalTrials.gov NCT04655287).

RESULTS

We found no adverse effects on patients' health in areas with lower standardized involuntary care ratios. The standardization variables age, sex, and urbanicity explained 70.5% of the variance in raw rates of involuntary care.

CONCLUSIONS

Lower standardized involuntary care ratios are not associated with adverse effects for patients with severe mental disorders in Norway. This finding merits further research of the way involuntary care works.

Small Area Analysis of Veterans Affairs Mental Health Services Data

OBJECTIVE

To identify geographic variation in mental health service use in the Department of Veterans Affairs (VA), the authors constructed utilization-based VA mental health service areas (MHSAs) for outpatient treatment and mental health referral regions (MHRRs) for residential and acute inpatient treatment.

METHODS

MHSAs are empirically derived geographic groupings of one or more counties containing one or more VA outpatient mental health clinics. For each county within an MHSA, patients received most of their VA-provided outpatient mental health care within that MHSA. MHSAs were aggregated into MHRRs according to where VA users in each MHSA received most of their residential and acute inpatient mental health care. Attribution loyalty was evaluated with the localization index-the fraction of VA users living in each geographic area who used their designated MHSA and MHRR facility. Variation in outpatient mental health visits and in acute inpatient and residential mental health stays was determined for the 2008-2018 period.

RESULTS

A total of 441 MHSAs were aggregated to 115 MHRRs (representing 3,909,080 patients with 52,372,303 outpatient mental health visits). The mean±SD localization index was 59.3%±16.4% for MHSAs and 67.8%±12.7% for MHRRs. Adjusted outpatient mental health visits varied from a mean of 0.88 per year in the lowest quintile of MHSAs to 3.14 in the highest. Combined residential and acute inpatient days varied from 0.29 to 1.79 between the lowest and highest quintiles.

CONCLUSIONS

MHSAs and MHRRs validly represented mental health utilization patterns in the VA and displayed considerable variation in mental health service provision across different locations.

Understanding geographic variations in psychiatric inpatient admission rates: width of the variations and associations with the supply of health and social care in France

BACKGROUND

Inpatient care accounts for the majority of mental health care costs and is not always beneficial. It can indeed have detrimental consequences if not used appropriately, and is unpopular among patients. As a consequence, its reduction is supported by international recommendations. Varying rates of psychiatric inpatient admissions therefore deserve to draw attention of researchers, clinicians and policy makers alike as such variations can challenge quality, equity and efficiency of care. In this context, our objectives were first to describe variations in psychiatric inpatient admission rates across the whole territory of mainland France, and second to identify their association with characteristics of the supply of care, which can be targeted by dedicated health policies.

METHODS

Our study was carried out in French psychiatric sectors' catchment areas for the year 2012. Inpatient admission rates per 100,000 adult inhabitants were calculated using data from the national psychiatric discharge database. Their variations were described numerically and graphically. We then carried out a negative binomial regression to identify characteristics of the supply of care (public and private care, health and social care, hospital and community-based care, specialised and non-specialised care) which were associated with these variations while adjusting our analysis for other relevant factors, in particular epidemiological differences.

RESULTS

Considerable variations in inpatient admission rates were observed between psychiatric sectors' catchment areas and were widespread on the French territory. Institutional characteristics of the hospital to which each sector was linked (private non-profit status, specialisation in psychiatry and participation to teaching activities and to emergency care) were associated with inpatient admission rates. Similarly, an increase in the availability of community-based private psychiatrists was associated with a decrease in the inpatient admission rate while an increase in the capacity of housing institutions for disabled individuals was associated with an increase in this rate.

CONCLUSIONS

Our results advocate for a homogenous repartition of health and social care for mental disorders in lines with the health needs of the population served. This should apply particularly to community-based private psychiatrists, whose heterogeneity of repartition has often been underscored.

A multi-level study of the determinants of mental health service utilization

BACKGROUND

Until now, research has focused on neighbourhood variations in mental health services and their relationships with local attributes, such as healthcare supply and socio-economic deprivation, without controlling for individual characteristics (age, sex, income, or education, for instance). Hence, this study is a major attempt to clarify the role played by individual and local attributes in the utilization of mental health services. The aim of this study was to disentangle individual and neighbourhood effects on mental health service use.

METHODS

In this cross-sectional study, individual-level data on 423 participants with a frequent mental health disorder was recruited from the general population and linked to neighbourhood-level data at the census tract level from the 2006 Canadian Census. Neighbourhood variables included socio-economic deprivation, mean income, residential stability and the proportion of recent immigrants. Individual characteristics included gender, age, marital status, self-rated mental health and the number of diagnoses. Multi-level logistic regression was used to assess the effects of individual and neighbourhood characteristics simultaneously on mental health service use.

RESULTS

The intraclass correlation coefficient indicated that 12.26% of the variance of mental health service utilization is at the neighbourhood level. Final analysis showed that at the individual level, being female, married, or self-rating mental health less than excellent increased healthcare use. At the neighbourhood level, deprived socio-economic neighbourhood decreased health service use (OR=0.71, P<0.05), while residential stability increased use (OR=1.24, P<0.05).

CONCLUSIONS

Individual and neighbourhood characteristics determine mental health service utilization. Taking both into consideration allows better targeting of health service policy and planning and enables more accurate needs-based resource allocation. However, future research should continue to investigate the pathway through which neighbourhood affects health service utilization.

Supplier-induced demand for psychiatric admissions in Northern New England

BACKGROUND

The development of hospital service areas (HSAs) using small area analysis has been useful in examining variation in medical and surgical care; however, the techniques of small area analysis are underdeveloped in understanding psychiatric admission rates. We sought to develop these techniques in order to understand the relationship between psychiatric bed supply and admission rates in Northern New England. Our primary hypotheses were that there would be substantial variation in psychiatric admission across geographic settings and that bed availability would be positively correlated with admission rates, reflecting a supplier-induced demand phenomenon. Our secondary hypothesis was that the construction of psychiatric HSAs (PHSAs) would yield more meaningful results than the use of existing general medical hospital service areas.

METHODS

To address our hypotheses, we followed a four-step analytic process: 1) we used small area analytic techniques to define our PHSAs, 2) we calculated the localization index for PHSAs and compared that to the localization index for general medical HSAs, 3) we used the number of psychiatric hospital beds, the number of psychiatric admissions, and census data to calculate population-based bed-supply and psychiatric admission rates for each PHSA, and 4) we correlated population-based admission rates to population-based psychiatric bed supply.

RESULTS

The admission rate for psychiatric diagnosis varied considerably among the PHSAs, with rates varying from 2.4 per 100,000 in Portsmouth, NH to 13.4 per 100,000 in Augusta, ME. There was a positive correlation of 0.71 between a PHSA's supply of beds and admission rate. Using our PSHAs produced a substantially higher localization index than using general medical hospital services areas (0.69 vs. 0.23), meaning that our model correctly predicted geographic utilization at three times the rate of the existing model.

CONCLUSIONS

The positive correlation between admission and bed supply suggests that psychiatric bed availability may partially explain the variation in admission rates. Development of PHSAs, rather than relying on the use of established general medical HSAs, improves the relevance and accuracy of small area analysis in understanding mental health services utilization.