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Although previous work on fiscal federalism and grants has focused on the effects of grants on expenditures, no published research examines the impact of decreasing grants on state financing. This research addresses how decreasing levels of federal grant money to states affect states' long‐term debt issuance, and whether the relationship is symmetric for increasing and decreasing grants. The model is tested with time series, cross‐sectional data from 1984 to 1999. The results show that grants affect debt issuance, the effect is asymmetric, and direction of the effect differs for different types of debt issuance.

Background: Real-time videoconferencing technology such as clinical video telehealth (CVT) offers a means to reach patient populations who face limited access to healthcare. The Veterans Health Administration has invested in CVT to improve care access for U.S. military veterans with spinal cord injuries and disorders (SCI/D); however, no studies have assessed the factors that influence implementation of this technology in clinical practice for individuals with SCI/D.

The Department of Veterans Affairs (VA) Intensive Dysphagia Treatment program serves a critical role in facilitating improvements to quality of care, standardization of outcomes, and increased access to structured therapy for Veterans with dysphagia. It has been implemented at 26 sites nationally and continues expanding. An explanatory sequential mixed-methods design was utilized for program evaluation to identify barriers and facilitators to implementation as reported by speech-language pathologists (SLPs) participating in the program. All 23 IDT program SLPs were invited to participate in an online survey. SLPs were asked to describe etiologies referred for SLP evaluation, most and least clinically useful program aspects, and characteristics of patients recommended for therapy. Qualitative interviews/focus groups were then conducted with 9 SLPs at 3 facilities with varying levels of program experience. Transcripts underwent systems engineering framework informed deductive thematic analysis. Interview/focus groups revealed overall positive feedback. Barriers included data entry challenges and provider understanding of long-term program goals, while facilitators included program structure enabling increased patient follow-up, outcomes tracking, and training in new treatment modalities. Through this evaluation process, program leadership garnered actionable feedback to improve further implementation of the IDT program. Ongoing efforts will further improve data entry, site onboarding procedures, and program communication.

We examined associations between enrollment in Medicare Part D pharmacy benefits and changes in medication acquisition from Department of Veterans Affairs (VA) pharmacies. We included all women and a random 10% sample of men who were VA enrollees, ≥65 years old as of January 1, 2004, and alive through December 2007. We used difference-in-differences models with propensity score weighting to examine changes in medication acquisition between 2005 (before Part D was implemented) and 2007 (after Part D implementation) for veterans who were or were not Part D enrolled. Of 231,716 veterans meeting inclusion criteria, 49,881 (21.5%) were enrolled. While 30-day medication supplies decreased from 26.2 to 23.4 for enrolled veterans, they increased from 36.6 to 37.4 for nonenrolled veterans (difference-in-differences: −4.0, p < .001). Reductions in 30-day supplies were greater among veterans who were required to pay VA copayments for some or all medications and who used VA and Medicare outpatient services.

Reasons for acquiring insurance outside Department of Veterans Affairs (VA) health care coverage among VA enrollees are incompletely understood. To assess Veterans' decision-making and acquisition of non-VA health care insurance in the Affordable Care Act era, we used mailed questionnaires and semistructured interviews in a stratified random sample of VA enrollees <65 years in the Midwest. Of the 3,666 survey participants, 32.1% reported non-VA insurance. Frequently reported reasons included wanting coverage for emergency situations or family members. Those without non-VA insurance cited unaffordability as the main obstacle. Analysis of the semistructured interview data revealed similar findings. In multivariable logistic regression analyses, characteristics associated with non-VA insurance included higher income (>$50,000 vs. <$10,000, odds ratio [OR] = 5.95, 95% confidence interval [CI]: 3.45–10.3, p < .001). As financial barriers exist for acquisition of non-VA insurance and hence community care, it is critically important that VA enrollees' health care needs are met through VA or community providers financed through VA.