Dataset Information

Mental health and high-cost health care utilization: new evidence from Axis II disorders.

ABSTRACT:

Objective

To analyze the associations between Axis II (A2) disorders and two measures of health care utilization with relatively high cost: emergency department (ED) episodes and hospital admissions.

Data source/study setting

Wave I (2001/2002) and Wave II (2004/2005) of the National Longitudinal Survey on Alcohol and Related Conditions (NESARC).

Study design

A national probability sample of adults. Gender-stratified regression analysis adjusted for a range of covariates associated with health care utilization.

Data collection

The target population of the NESARC is the civilian noninstitutionalized population aged 18 years and older residing in the United States. The cumulative survey response rate is 70.2 percent with a response rate of 81 percent (N=43,093) in Wave I and 86.7 percent (N=34,653) in Wave II.

Principal findings

Both men and women with A2 disorders are at elevated risk for ED episodes and hospital admissions. Associations are robust after adjusting for a rich set of confounding factors, including Axis I (clinical) psychiatric disorders. We find evidence of a dose-response relationship, while antisocial and borderline disorders exhibit the strongest associations with both measures of health care utilization.

Conclusions

This study provides the first published estimates of the associations between A2 disorders and high-cost health care utilization in a large, nationally representative survey. The findings underscore the potential implications of these disorders on health care expenditures.

SUBMITTER: Maclean JC

PROVIDER: S-EPMC3976193 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mental health and high-cost health care utilization: new evidence from Axis II disorders.

Maclean Johanna Catherine JC Xu Haiyong H French Michael T MT Ettner Susan L SL

Health services research 20131003 2

<h4>Objective</h4>To analyze the associations between Axis II (A2) disorders and two measures of health care utilization with relatively high cost: emergency department (ED) episodes and hospital admissions.<h4>Data source/study setting</h4>Wave I (2001/2002) and Wave II (2004/2005) of the National Longitudinal Survey on Alcohol and Related Conditions (NESARC).<h4>Study design</h4>A national probability sample of adults. Gender-stratified regression analysis adjusted for a range of covariates as ...[more]

PMID: 24117342

Similar Datasets

Project description:ImportanceA population-based study using validated algorithms to estimate the costs of treating people with chronic disease with and without mental health disorders is needed.ObjectiveTo determine the association of mental health disorders with health care costs among people with chronic diseases.Design, setting, and participantsThis population-based cohort study in the Canadian province of Alberta collected data from April 1, 2012, to March 31, 2015, among 991?445 adults 18 years and older with a chronic disease (ie, asthma, congestive heart failure, myocardial infarction, diabetes, epilepsy, hypertension, chronic pulmonary disease, or chronic kidney disease). Data analysis was conducted from October 2017 to August 2018.ExposuresMental health disorder (ie, depression, schizophrenia, alcohol use disorder, or drug use disorder).Main outcomes and measuresResource use, mean total unadjusted and adjusted 3-year health care costs, and mean total unadjusted 3-year costs for hospitalization and emergency department visits for ambulatory care-sensitive conditions.ResultsAmong 991?445 participants, 156?296 (15.8%) had a mental health disorder. Those with no mental health disorder were older (mean [SD] age, 58.1 [17.6] years vs 55.4 [17.0] years; P?<?.001) and less likely to be women (50.4% [95% CI, 50.3%-50.5%] vs 57.7% [95% CI, 57.4%-58.0%]; P?<?.001) than those with mental health disorders. For those with a mental health disorder, mean total 3-year adjusted costs were $38?250 (95% CI, $36?476-$39?935), and for those without a mental health disorder, mean total 3-year adjusted costs were $22?280 (95% CI, $21?780-$22?760). Having a mental health disorder was associated with significantly higher resource use, including hospitalization and emergency department visit rates, length of stay, and hospitalization for ambulatory care-sensitive conditions. Higher resource use by patients with mental health disorders was not associated with health care presentations owing to chronic diseases compared with patients without a mental health disorder (chronic disease hospitalization rate per 1000 patient days, 0.11 [95% CI, 0.11-0.12] vs 0.06 [95% CI, 0.06-0.06]; P?<?.001; overall hospitalization rate per 1000 patient days, 0.88 [95% CI, 0.87-0.88] vs 0.43 [95% CI, 0.43-0.43]; P?<?.001).Conclusions and relevanceThis study suggests that mental health disorders are associated with substantially higher resource utilization and health care costs among patients with chronic diseases. These findings have clinical and health policy implications.

Project description:BACKGROUND:Community residential aftercare (step-down) services can ease the transition after a mental health hospital stay for patients with severe mental illness (SMI). AIMS:To investigate use of community and specialised mental health care services and costs in patients with SMI the first 12 months after discharge from a mental health hospital (MHH), comparing community residential aftercare (CRA) and treatment as usual. METHODS:An open parallel group randomised controlled trial with 41 participants. Data on use of specialist services (hospital, ambulant treatment and outpatient treatment) and community services (residential stays, home help, home care nursing, mental health consultation) were collected from specialist and community registers and health records. RESULTS:For the primary outcome, utilisation of community mental health services, the intervention group used, on average, 29% fewer hours (mean differences -?21.6 h, 95% CI -93.1 to 44.9, p?=?.096) with a cost saving of 29% (mean differences -?1845 EUR, 95% CI -8267 to 4171, p?=?.102), but the estimates were imprecise. For the secondary outcome, the study groups had the same total number of inpatient days (66 days), but the intervention group had on average of 13.4 fewer inpatient days in the mental health hospital (95% CI -29.9 to 0.9. p?=?.008). The number of inpatient admissions (mean difference?-?0.9 admissions, 95% CI -3.5 to 1.5, p?=?.224) and readmissions (-?0.8, 95% CI -2.5 to 0.9. p?=?.440) was lower in the intervention group. The intervention group had on average a total cost saving of 38.5% (mean differences -?23,071 EUR, 95% CI -45,450 to 3027. p?=?.057). A post hoc multivariable regression analysis controlling for baseline characteristics gave a reduction in total cost in favour of the intervention group of -?19,781 EUR (95% CI -44,072 to 4509, p=,107). CONCLUSION:In this study, it was not possible to draw a definite conclusion about the effect, due to the small sample and imprecision of the estimates. The direction of the results and size of the point estimate, in addition to findings in other studies, indicates that transferring patients ready for discharge from mental hospital to community residential aftercare can have the potential to reduce total consumption of health services and costs without increased hospital admissions. TRIAL REGISTRATION:Registered in clinicaltrials.gov ( NCT01719354 ).

Project description:BackgroundIn order to respond to the dearth of mental health data in Rwanda where large-scale prevalence studies were not existing, Rwanda Mental Health Survey was conducted to measure the prevalence of mental disorders, associated co-morbidities and knowledge and utilization of mental health services nationwide within Rwanda.MethodsThis cross-sectional study was conducted between July and August 2018, among the general population, including survivors of the 1994 Genocide against the Tutsi. Participants (14-65 years) completed the Mini-International Neuropsychiatric Interview (Version 7.0.2), sociodemographic and epilepsy-related questionnaires. General population participants were selected first by random sampling of 240 clusters, followed by systematic sampling of 30 households per cluster. Genocide survivors within each cluster were identified using the 2007-2008 Genocide Survivors Census.ResultsOf 19,110 general survey participants, most were female (n = 11,233; 58.8%). Mental disorders were more prevalent among women (23.2%) than men (16.6%) (p < 0.05). The most prevalent mental disorders were major depressive episode (12.0%), panic disorder (8.1%) and post-traumatic stress disorder (PTSD) (3.6%). Overall, 61.7% had awareness of mental health services while only 5.3% reported to have used existing services. Of the 1271 genocide survivors interviewed, 74.7% (n = 949) were female; prevalence of any mental disorder was 53.3% for women and 48.8% for men. Most prevalent disorders were major depressive episode (35.0%), PTSD (27.9%) and panic disorder (26.8%). Among genocide survivors, 76.2% were aware of availability of mental health services, with 14.1% reported having used mental health services.ConclusionsDespite high prevalence of mental disorders among the general population and genocide survivors, utilization of available mental health services was low. A comprehensive approach to mental health is needed for prevention of mental illness and to promote mental healthcare services.

Project description:BackgroundPosttraumatic acute respiratory distress syndrome (ARDS) is associated with prolonged mechanical ventilation and longer hospitalizations. The relationship between posttraumatic ARDS severity and financial burden has not been previously studied. We hypothesized that increasing ARDS severity is associated with incrementally higher health care costs.MethodsAdults arriving as the highest level of trauma activation were enrolled in an ongoing prospective cohort study. Patients who survived 6 hours or longer are included in the analysis. Blinded review of chest radiographs was performed by two independent physicians for any intubated patient with PaO2:FIO2 ratio of 300 mmHg or lower during the first 8 days of admission. The severity of ARDS was classified by the Berlin criteria. Hospital charge data were used to perform standard costing analysis.ResultsAcute respiratory distress syndrome occurred in 13% (203 of 1,586). The distribution of disease severity was 33% mild, 42% moderate, and 25% severe. Patients with ARDS were older (41 years vs. 35 years, p < 0.01), had higher median Injury Severity Score (30 vs. 10, p < 0.01), more chest injury (Abbreviated Injury Scale score, ≥ 3: 51% vs. 21%, p < 0.01), and blunt mechanisms (85% vs. 53%, p < 0.01). By ARDS severity, there was no significant difference in age, mechanism, or rate of traumatic brain injury. Increasing ARDS severity was associated with higher Injury Severity Score and higher mortality rates. Standardized total hospital charges were fourfold higher for patients who developed ARDS compared with those who did not develop ARDS (US $434,000 vs. US $96,000; p < 0.01). Furthermore, the daily hospital charges significantly increased across categories of worsening ARDS severity (mild, US $20,451; moderate, US $23,994; severe, US $33,316; p < 0.01).ConclusionThe development of posttraumatic ARDS is associated with higher health care costs. Among trauma patients who develop ARDS, total hospital charges per day increase with worsening severity of disease. Prevention, early recognition, and treatment of ARDS after trauma are potentially important objectives for efforts to control health care costs in this population.Level of evidenceEconomic and value-based evaluations, level IV.

Dataset Information

Mental health and high-cost health care utilization: new evidence from Axis II disorders.

Objective

Data source/study setting

Study design

Data collection

Principal findings

Conclusions

Publications

Mental health and high-cost health care utilization: new evidence from Axis II disorders.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets