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BackgroundInformation about the effectiveness of oral antivirals in preventing short- and long-term COVID-19-related outcomes in the setting of Omicron variant transmission and COVID-19 vaccination is limited.ObjectiveTo measure the effectiveness of nirmatrelvir-ritonavir and molnupiravir for outpatient treatment of COVID-19.DesignThree retrospective target trial emulation studies comparing matched cohorts of nirmatrelvir-ritonavir versus no treatment, molnupiravir versus no treatment, and nirmatrelvir-ritonavir versus molnupiravir.SettingVeterans Health Administration (VHA).ParticipantsNonhospitalized veterans in VHA care who were at risk for severe COVID-19 and tested positive for SARS-CoV-2 during January through July 2022.InterventionNirmatrelvir-ritonavir or molnupiravir pharmacotherapy.MeasurementsIncidence of any hospitalization or all-cause mortality at 30 days and from 31 to 180 days.ResultsEighty-seven percent of participants were male; the median age was 66 years, and 18% were unvaccinated. Compared with matched untreated control participants, those treated with nirmatrelvir-ritonavir (n = 9607) had lower 30-day risk for hospitalization (22.07 vs. 30.32 per 1000 participants; risk difference [RD], -8.25 [95% CI, -12.27 to -4.23] per 1000 participants) and death (1.25 vs. 5.47 per 1000 participants; RD, -4.22 [CI, -5.45 to -3.00] per 1000 participants). Among persons alive at day 31, reductions were seen in 31- to 180-day incidence of death (hazard ratio, 0.66 [CI, 0.49 to 0.89]) but not hospitalization (subhazard ratio, 0.90 [CI, 0.79 to 1.02]). Molnupiravir-treated participants (n = 3504) had lower 30-day and 31- to 180-day risks for death (3.14 vs. 13.56 per 1000 participants at 30 days; RD, -10.42 [CI, -13.49 to -7.35] per 1000 participants; hazard ratio at 31 to 180 days, 0.67 [CI, 0.48 to 0.95]) but not hospitalization. A difference in 30-day or 31- to 180-day risk for hospitalization or death was not observed between matched nirmatrelvir- or molnupiravir-treated participants.LimitationThe date of COVID-19 symptom onset for most veterans was unknown.ConclusionNirmatrelvir-ritonavir was effective in reducing 30-day hospitalization and death. Molnupiravir was associated with a benefit for 30-day mortality but not hospitalization. Further reductions in mortality from 31 to 180 days were observed with both antivirals.Primary funding sourceU.S. Department of Veterans Affairs.

BackgroundPatient adherence to medication regimens is critical in most chronic disease treatment plans. This study uses a patient-centered tablet app, “My Interventional Drug-Eluting Stent Educational App (MyIDEA).” This is an educational program designed to improve patient medication adherence. ObjectiveOur goal is to describe the design, methodology, limitations, and results of the MyIDEA tablet app. We created a mobile technology-based patient education app to improve dual antiplatelet therapy adherence in patients who underwent a percutaneous coronary intervention and received a drug-eluting stent. MethodsPatient advisers were involved in the development process of MyIDEA from the initial wireframe to the final launch of the product. The program was restructured and redesigned based on the patient advisers’ suggestions as well as those from multidisciplinary team members. To accommodate those with low health literacy, we modified the language and employed attractive color schemes to improve ease of use. We assumed that the target patient population may have little to no experience with electronic tablets, and therefore, we designed the interface to be as intuitive as possible. ResultsThe MyIDEA app has been successfully deployed to a low-health-literate elderly patient population in the hospital setting. A total of 6 patients have interacted with MyIDEA for an average of 17.6 minutes/session. ConclusionsIncluding patient advisers in the early phases of a mobile patient education development process is critical. A number of changes in text order, language, and color schemes occurred to improve ease of use. The MyIDEA program has been successfully deployed to a low-health-literate elderly patient population. Leveraging patient advisers throughout the development process helps to ensure implementation success.

This perspective paper seeks to lay out an efficient approach for health care providers, researchers, and other stakeholders involved in interventions aimed at improving care coordination to partner in locating and using applicable care coordination theory. The objective is to learn from relevant theory-based literature about fit between intervention options and coordination needs, thereby bringing insights from theory to enhance intervention design, implementation, and troubleshooting. To take this idea from an abstract notion to tangible application, our workgroup on models and measures from the Veterans Health Administration (VA) State of the Art (SOTA) conference on care coordination first summarizes our distillation of care coordination theoretical frameworks (models) into three common conceptual domains-context of an intervention, locus in which an intervention is applied, and specific design features of the intervention. Then we apply these three conceptual domains to four cases of care coordination interventions ("use cases") chosen to represent various scopes and stages of interventions to improve care coordination for veterans. Taken together, these examples make theory more accessible and practical by demonstrating how it can be applied to specific cases. Drawing from theory offers one method to anticipate which intervention options match a particular coordination situation.

Objective: The epidemiology of COVID-19 has substantially changed since its emergence given the availability of effective vaccines, circulation of different viral variants, and re-infections. We aimed to develop models to predict 30-day COVID-19 hospitalization and death in the Omicron era for contemporary clinical and research applications. Methods: We used comprehensive electronic health records from a national cohort of patients in the Veterans Health Administration (VHA) who tested positive for SARS-CoV-2 between March 1, 2022, and March 31, 2023. Full models incorporated 84 predictors, including demographics, comorbidities, and receipt of COVID-19 vaccinations and anti-SARS-CoV-2 treatments. Parsimonious models included 19 predictors. We created models for 30-day hospitalization or death, 30-day hospitalization, and 30-day all-cause mortality. We used the Super Learner ensemble machine learning algorithm to fit prediction models. Model performance was assessed with the area under the receiver operating characteristic curve (AUC), Brier scores, and calibration intercepts and slopes in a 20% holdout dataset. Results: Models were trained and tested on 198,174 patients, of whom 8% were hospitalized or died within 30 days of testing positive. AUCs for the full models ranged from 0.80 (hospitalization) to 0.91 (death). Brier scores were close to 0, with the lowest error in the mortality model (Brier score: 0.01). All three models were well calibrated with calibration intercepts <0.23 and slopes <1.05. Parsimonious models performed comparably to full models. Conclusions: We developed prediction models that accurately estimate COVID-19 hospitalization and mortality risk following emergence of the Omicron variant and in the setting of COVID-19 vaccinations and antiviral treatments. These models may be used for risk stratification to inform COVID-19 treatment and to identify high-risk patients for inclusion in clinical trials. [ABSTRACT FROM AUTHOR]

Many Veterans receive Department of Veterans Affairs (VA)-purchased care from non-VA facilities but little is known about factors that Veterans consider for this choice. Between May 2020 and August 2021, we surveyed VA-purchased care-eligible VA patients about barriers and facilitators to choosing where to receive care. We examined the association between travel time to their VA facility and their choice of VA-purchased care (VA-paid health care received in non-VA settings) versus VA facility and whether this association was modified by distrust. We received 1,662 responses and 692 (42%) chose a VA facility. Eighty percent reported quality care was in their top three factors that influenced their decision. Respondents with the highest distrust and who lived >1 hr from the nearest VA facility had the lowest predicted probability (PP) of choosing VA (PP 15%; 95% confidence interval: 10%–20%). Veterans value quality of care. VA and other health care systems should consider patient-centered ways to improve and publicize quality and reduce distrust. [ABSTRACT FROM AUTHOR]

Background: Positive correlations have been reported between wastewater SARS-CoV-2 concentrations and a community's burden of infection, disease or both. However, previous studies mostly compared wastewater to clinical case counts or nonrepresentative convenience samples, limiting their quantitative potential. Objectives: This study examined whether wastewater SARS-CoV-2 concentrations could provide better estimations for SARS-CoV-2 community prevalence than reported cases of COVID-19. In addition, this study tested whether wastewater-based epidemiology methods could identify neighborhood-level COVID-19 hotspots and SARS-CoV-2 variants. Methods: Community SARS-CoV-2 prevalence was estimated from eight randomized door-to-door nasal swab sampling events in six Oregon communities of disparate size, location, and demography over a 10-month period. Simultaneously, wastewater SARS-CoV-2 concentrations were quantified at each community's wastewater treatment plant and from 22 Newport, Oregon, neighborhoods. SARS-CoV-2 RNA was sequenced from all positive wastewater and nasal swab samples. Clinically reported case counts were obtained from the Oregon Health Authority. Results: Estimated community SARS-CoV-2 prevalence ranged from 8 to 1,687/10,000 persons. Community wastewater SARS- CoV-2 concentrations ranged from 2.9 to 5.1 [log.sub.10] gene copies per liter. Wastewater SARS-CoV-2 concentrations were more highly correlated (Pearson's r = 0.96; [R.sup.2] = 0.91) with community prevalence than were clinically reported cases of COVID-19 (Pearson's r = 0.85; [R.sup.2] = 0.73). Monte Carlo simulations indicated that wastewater SARS-CoV-2 concentrations were significantly better than clinically reported cases at estimating prevalence (p < 0.05). In addition, wastewater analyses determined neighborhood-level COVID-19 hot spots and identified SARS-CoV-2 variants (B.1 and B.1.399) at the neighborhood and city scales. Discussion: The greater reliability of wastewater SARS-CoV-2 concentrations over clinically reported case counts was likely due to systematic biases that affect reported case counts, including variations in access to testing and underreporting of asymptomatic cases. With these advantages, combined with scalability and low costs, wastewater-based epidemiology can be a key component in public health surveillance of COVID-19 and other communicable infections. https://doi.org/10.1289/EHP10289, Introduction Wastewater-based epidemiology (WBE) has emerged as an effective and sensitive approach for monitoring COVID-19 presence in a community through the detection of the novel coronavirus (SARS-CoV-2) shed by infected [...]

Background We examined whether key sociodemographic and clinical risk factors for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and mortality changed over time in a population-based cohort study. Methods and findings In a cohort of 9,127,673 persons enrolled in the United States Veterans Affairs (VA) healthcare system, we evaluated the independent associations of sociodemographic and clinical characteristics with SARS-CoV-2 infection (n = 216,046), SARS-CoV-2-related mortality (n = 10,230), and case fatality at monthly intervals between February 1, 2020 and March 31, 2021. VA enrollees had a mean age of 61 years (SD 17.7) and were predominantly male (90.9%) and White (64.5%), with 14.6% of Black race and 6.3% of Hispanic ethnicity. Black (versus White) race was strongly associated with SARS-CoV-2 infection (adjusted odds ratio [AOR] 5.10, [95% CI 4.65 to 5.59], p-value Conclusions In this study, we found that strongly positive associations of Black and AI/AN (versus White) race and urban (versus rural) residence with SARS-CoV-2 infection, mortality, and case fatality observed early in the pandemic were ameliorated or reversed by March 2021., Author(s): George N. Ioannou 1,2,*, Jacqueline M. Ferguson 3, Ann M. O'Hare 4, Amy S. B. Bohnert 5, Lisa I. Backus 6, Edward J. Boyko 7, Thomas F. Osborne 8, [...]

Background: Veterans Affairs (VA) home‐based primary care (HBPC) provides comprehensive longitudinal care to patients with complex, chronic disabling disease. While enrollment is associated with lower hospitalization rates and costs, detailed trajectories have not been well described. Methods: We performed a longitudinal descriptive study of patients newly enrolled in VA HBPC in fiscal year (FY) 2015. We extracted demographics, comorbidities, functional status, and social supports from VA and Medicare data and examined patterns of care and clinical outcomes, including hospital, nursing home (NH), hospice use and mortality from FY2015–2017. We present results using descriptive statistics, alluvial plots, and heat maps. Results: We identified 10,571 HBPC enrollees in FY2015; mean age was 77.7. HBPC patients commonly had chronic medical conditions with high self‐management burden (e.g., diabetes 48.2%) and disabling conditions such as dementia (39.3%). Over half had ≥2 deficits in activities of daily living, 46% had caregivers with functional limitations or no caregiver, and 25% resided in a socially deprived area. Patients experienced variable care trajectories. Mean time enrolled in HBPC was 331 days, 8.3% of patients were discharged after 3 months, and 22.8% stayed enrolled for over 2 years. Institutional health care use declined in the 6 months after initial enrollment: (e.g., hospital: 41%–25%, NH: 34%–11%). At 2 years, 36% of patients had died; among decedents, 58% received hospice and 72% died in a non‐institutional setting. In the last 180 days of life, 84% of time was spent at home, and once enrolled in hospice, 97% of time was spent outside of institutional care. Conclusions: HBPC patients experience highly variable care trajectories but on average have reductions in acute care use and spend a majority of time in non‐institutional settings. These data allow for a nuanced understanding of HBPC, providing a platform for monitoring, evaluating, and improving program function. [ABSTRACT FROM AUTHOR]