Search

Objective: To estimate a causal relationship between mental health staffing and time to initiation of mental health care for new patients. Data Sources and Study Setting: As the largest integrated health care delivery system in the United States, the Veterans Health Administration (VHA) provides a unique setting for isolating the effects of staffing on initiation of mental health care where demand is high and out‐of‐pocket costs are not a relevant confounder. We use data from the Department of Defense and VHA to obtain patient and facility characteristics and health care use. Study Design: To isolate exogenous variation in mental health staffing, we used an instrumental variables approach—two‐stage residual inclusion with a discrete time hazard model. Our outcome is time to initiation of mental health care after separation from active duty (first appointment) and our exposure is mental health staffing (standardized clinic time per 1000 VHA enrollees per pay period). Data Collection/Extraction Methods: Our cohort consists of all Veterans separating from active duty between July 2014 and September 2017, who were enrolled in the VHA, and had at least one diagnosis of post‐traumatic stress disorder, major depressive disorder, and/or substance use disorder in the year prior to separation from active duty (N = 54,209). Principal Findings: An increase of 1 standard deviation in mental health staffing results in a higher likelihood of initiating mental health care (adjusted hazard ratio: 3.17, 95% confidence interval: 2.62, 3.84, p < 0.001). Models stratified by tertile of mental health staffing exhibit decreasing returns to scale. Conclusions: Increases in mental health staffing led to faster initiation of care and are especially beneficial in facilities where staffing is lower, although initiation of care appears capacity‐limited everywhere. [ABSTRACT FROM AUTHOR]

Inappropriate antibiotic use contributes to antimicrobial resistance, a global public health threat. The non-specific manifestations of dengue, itself a growing public health threat, lead to avoidable empiric antibiotic prescription, particularly in children. In this national pooled population-based cross-sectional study, we evaluated child and physician characteristics associated with antibiotics prescription in confirmed dengue cases in Taiwan. Linking national health care insurance claims and reports of confirmed dengue cases from 2008 to 2015, there were 7086 children with confirmed dengue with 21 744 outpatient visits and 2520 inpatient admissions. We assessed the presence of antibiotic prescription in outpatient and inpatient settings separately a week before or after the confirmation date. Logistic regression models with generalized estimating equations were applied to identify patient, practitioner, and other factors associated with antibiotic prescription. A total of 29.4% of children <18 years old with dengue who did not have a concomitant bacterial infection were prescribed antibiotics during the 14-day assessment period. Antibiotics prescription was reduced from 13.5% to 6.3% and from 43.2% to 19.3% in outpatient and inpatient settings, respectively, after dengue was confirmed. Young children were more likely to receive antibiotics. Significant variations in antibiotic prescribing across physicians were observed only in outpatient settings: physicians ≥60 years old and physicians practicing at clinics and in non-urban facilities were more likely to prescribe antibiotics. Antibiotics were less likely to be prescribed during an exceptional 2-year epidemic than in other years. Antibiotic prescribing for dengue, an arboviral infection affecting half of the global population, was shown to occur in 29% of paediatric cases in Taiwan. That potentially avoidable antibiotic consumption could be reduced by improving antibiotic stewardship, informed by understanding the conditions under which antibiotics are prescribed and the availability of prevention strategies for viral diseases, including dengue. We identified a number of such factors in this national population-based study. [ABSTRACT FROM AUTHOR]