BACKGROUND: The responsibility of care for Veterans and Service Members (V/SMs) with traumatic brain injury (TBI) often defaults to informal family caregivers. Caregiving demands considerable knowledge, skill, and support to facilitate the health and well-being of V/SMs and themselves. Persistent and common TBI caregiver issues include strain, depression, and anxiety. While evidence-based, brief interventions have been developed and implemented for family caregivers in Veteran neurodegenerative populations, few interventions have been developed, adapted, or tested to support the unique needs of caregivers of V/SMs with TBI.
OBJECTIVE: This study will adapt and test an evidence-based, personalized, 6-session telehealth caregiver intervention, \"Resources for Enhancing All Caregivers\' Health\" (REACH), to meet the unique needs of caregivers of V/SMs with TBI. If successful, a community-based participatory research team will develop an implementation plan to roll out REACH TBI across the national Veterans Affairs Polytrauma System of Care.
METHODS: This mixed methods, crossover waitlist control clinical trial will use a Type 1 Hybrid Effectiveness-Implementation approach to adapt and then test the effects of REACH TBI on key TBI caregiver outcomes.
RESULTS: This study was funded by the Department of Defense in September 2023. Participant enrollment and data collection will begin in 2024.
CONCLUSIONS: If effective, REACH TBI will be the first evidence-based intervention for caregivers of V/SMs with TBI that can be scaled to implement across the Veterans Affairs Polytrauma System of Care and fill a notable gap in clinical services.
UNASSIGNED: PRR1-10.2196/57692.

BACKGROUND: The COVID-19 pandemic highlighted the importance of telemedicine in health care. However, video telemedicine requires adequate broadband internet speeds. As video-based telemedicine grows, variations in broadband access must be accurately measured and characterized.
OBJECTIVE: This study aims to compare the Federal Communications Commission (FCC) and Microsoft US broadband use data sources to measure county-level broadband access among veterans receiving mental health care from the Veterans Health Administration (VHA).
METHODS: Retrospective observational cohort study using administrative data to identify mental health visits from January 1, 2019, to December 31, 2020, among 1161 VHA mental health clinics. The exposure is county-level broadband percentages calculated as the percentage of the county population with access to adequate broadband speeds (ie, download >25 megabits per second) as measured by the FCC and Microsoft. All veterans receiving VHA mental health services during the study period were included and categorized based on their use of video mental health visits. Broadband access was compared between and within data sources, stratified by video versus no video telemedicine use.
RESULTS: Over the 2-year study period, 1,474,024 veterans with VHA mental health visits were identified. Average broadband percentages varied by source (FCC mean 91.3%, SD 12.5% vs Microsoft mean 48.2%, SD 18.1%; P<.001). Within each data source, broadband percentages generally increased from 2019 to 2020. Adjusted regression analyses estimated the change after pandemic onset versus before the pandemic in quarterly county-based mental health visit counts at prespecified broadband percentages. Using FCC model estimates, given all other covariates are constant and assuming an FCC percentage set at 70%, the incidence rate ratio (IRR) of county-level quarterly mental video visits during the COVID-19 pandemic was 6.81 times (95% CI 6.49-7.13) the rate before the pandemic. In comparison, the model using Microsoft data exhibited a stronger association (IRR 7.28; 95% CI 6.78-7.81). This relationship held across all broadband access levels assessed.
CONCLUSIONS: This study found FCC broadband data estimated higher and less variable county-level broadband percentages compared to those estimated using Microsoft data. Regardless of the data source, veterans without mental health video visits lived in counties with lower broadband access, highlighting the need for accurate broadband speeds to prioritize infrastructure and intervention development based on the greatest community-level impacts. Future work should link broadband access to differences in clinical outcomes.

Hearing loss is common among Veterans, and extensive hearing care resources are prioritized within the Veterans Administration (VA). Severe hearing loss poses unique communication challenges with speech understanding that may not be overcome with amplification. We analyzed data from the VA Audiometric Repository between 2005 and 2017 and the relationship between hearing loss severity with speech recognition scores. We hypothesized that a significant subset of Veterans with severe or worse hearing loss would have poor unaided speech perception outcomes even with adequate audibility. Sociodemographic characteristics and comorbidities were compiled using electronic medical records as was self-report measures of hearing disability. We identified a cohort of 137,500 unique Veterans with 232,789 audiograms demonstrating bilateral severe or worse hearing loss (four-frequency PTA > 70 dB HL). The median (IQR; range) age of Veterans at their first audiogram with severe or worse hearing loss was 81 years (74 to 87; 21-90+), and a majority were male (136,087 [99%]) and non-Hispanic white (107,798 [78.4%]). Among those with bilateral severe or worse hearing loss, 41,901 (30.5%) also had poor speech recognition scores (<50% words), with greater hearing loss severity correlating with worse speech perception. We observed variability in speech perception abilities in those with moderate-severe and greater levels of hearing loss who may derive limited benefit from amplification. Veterans with communication challenges may warrant alternative approaches and treatment strategies such as cochlear implants to support communication needs.

From 2020 to 2023, the Department of Veterans Affairs (VA) conducted a national pilot of a rideshare program to support homeless patients\' transportation needs to obtain critical resources and attend medical appointments. This study linked Lyft rideshare data in 2022 to VA administrative data to examine characteristics and changes in service use among VA homeless service users. The results showed that VA homeless service users who used the VA Rideshare program were more likely to have psychiatric diagnoses and urgent care visits than those who did not use the program. When we controlled for past VA service use, use of the VA Rideshare program was associated with greater use of VA outpatient and inpatient services and fewer no-show medical appointments six months after the veterans\' index date. VA Rideshare users had three to eight more program visits over the course of six months than non-Rideshare users. These findings indicate benefits associated with providing transportation assistance to vulnerable patients in a nationwide health system.

This case commentary considers unique features of medical-legal partnerships (MLPs) in the Veterans Health Administration that may potentially mediate and minimize ethical tensions that may arise in MLP collaborations involving diagnosing and documenting disability.

Measuring suicide risk fluctuation remains difficult, especially for high-suicide risk patients. Our study addressed this issue by leveraging Dynamic Topic Modeling, a natural language processing method that evaluates topic changes over time, to analyze high-suicide risk Veterans Affairs patients\' unstructured electronic health records. Our sample included all high-risk patients that died (cases) or did not (controls) by suicide in 2017 and 2018. Cases and controls shared the same risk, location, and treatment intervals and received nine months of mental health care during the year before the relevant end date. Each case was matched with five controls. We analyzed case records from diagnosis until death and control records from diagnosis until matched case\'s death date. Our final sample included 218 cases and 943 controls. We analyzed the corpus using a Python-based Dynamic Topic Modeling algorithm. We identified five distinct topics, \"Medication,\" \"Intervention,\" \"Treatment Goals,\" \"Suicide,\" and \"Treatment Focus.\" We observed divergent change patterns over time, with pathology-focused care increasing for cases and supportive care increasing for controls. The case topics tended to fluctuate more than the control topics, suggesting the importance of monitoring lability. Our study provides a method for monitoring risk fluctuation and strengthens the groundwork for time-sensitive risk measurement.

UNASSIGNED: During the COVID-19 pandemic, the Veterans Health Administration (VHA) expanded telehealth infrastructure. Understanding telehealth initiation and sustained engagement could inform future resource allocation for high-need populations.
UNASSIGNED: To describe and examine primary care use, including initiation, use, and engagement factors, of telehealth modalities (telephone, video visits, and secure messaging) from 2020 to 2022.
UNASSIGNED: This cohort study was conducted among 1 383 070 patients in the 75th or higher percentile for 90-day risk of hospitalization or mortality (using previously validated Care Assessment Need scores) engaged in VHA primary care from March 11, 2019, to March 10, 2022.
UNASSIGNED: Patient sociodemographic characteristics (age, sex, race and ethnicity, and marital and housing status), health characteristics (chronic condition count, military service disability, serious mental illness, or substance use disorder diagnoses), geographic characteristics (driving distance to clinic and rural or urban location), and Federal Communications Commission-reported broadband speed among subgroups of patients at high risk categorized by telehealth use from 2020 to 2022.
UNASSIGNED: Primary care utilization by modality.
UNASSIGNED: A total of 1 383 070 patients at high risk were engaged in VHA primary care in March 2020 (median age, 73.0 years [IQR, 65-80 years]; 92.4% male; 77.7% regular telehealth users in 2019). With the onset of the COVID-19 pandemic from March 2020 to March 2021, 92.7% of patients at high risk (1 158 804 of 1 250 438 retained in care) became regular telehealth users. The following year, most patients continued as telehealth users (83.4% [942 151 of 1 129 683 retained]), including 38.2% retention of users at high risk newly engaged in 2020. Between 2019 and 2022 among those living and engaged in VHA primary care, adjusted exploratory multinomial logit models estimated that new telehealth users in 2020 (both sustained or only transiently engaged) were more often Black non-Hispanic individuals with greater comorbidity burdens than those who never engaged in telehealth use (Black non-Hispanic with new persistent telehealth use: adjusted relative risk ratio [ARR], 1.18 [95% CI, 1.16-1.20]; Black non-Hispanic with transient telehealth use: ARR, 1.11 [95% CI, 1.08-1.13]; ≥5 chronic conditions with new persistent telehealth use: ARR, 1.92 [95% CI, 1.88-1.96]; ≥5 chronic conditions with transient telehealth use: ARR, 1.43 [95% CI, 1.40-1.46]).
UNASSIGNED: This cohort study suggests that primary care telehealth initiation, use and sustained engagement differed among subgroups of patients at high risk throughout the COVID-19 pandemic. Those never or only transiently engaged with telehealth had lower illness burdens and were less likely to identify as members of racial or ethnic minority groups. Variation in telehealth use among subgroups of patients at high risk during this period could inform future resource allocation.

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Hospitals within the Veterans Affairs (VA) health care system exhibited growing use of observation care. It is unknown how this affected VA hospital performance since observation care is not included in acute inpatient measures. To examine changes in VA hospitalization outcomes and whether it was affected by shifting acute inpatient care to observation care. Longitudinal analysis of 986,355 acute hospitalizations and observation stays in 11 states 2011 to 2017. We estimated temporal changes in 30-day mortality, 30-day readmissions, costs, and length of stay (LOS) for all hospitalizations and 6 conditions in adjusted models. Changes in mortality and readmissions were compared including and excluding observation care. A 9% drop in acute hospitalizations was offset by a 157% increase in observation stays 2011 to 2017. A 30-day mortality decreased but readmissions did not when observation stays were included (all P < .05). Mean costs increased modestly; mean LOS was unchanged. There were differences by condition. VA hospital mortality decreased; there was no change in readmissions.

暂无摘要。