IntroductionObstructive sleep apnea (OSA), a disorder caused by repeated collapse of the upper airway resulting in pauses in breathing, is highly prevalent among United States (US) Veterans. Prior to the COVID pandemic, telehealth for clinical appointments and diagnostic testing for OSA was used within the U.S. Department of Veterans Affairs (VA); however, experience was limited with telehealth for initiation of PAP (Positive Airway Pressure), mailing the device to the Veteran, and educating on use through a phone or video visit. Limited literature is available evaluating patients’ experience with this “tele-PAP” setup. The aim of this study is to understand the experiences of Veterans with OSA with Tele-PAP or face-to-face PAP setup (“FTF-PAP”) in the US using qualitative methods.MethodsWe conducted semi-structured phone interviews with a convenience sample of 40 Veterans. Interviews included six domains: delivery of PAP device, knowledge of OSA, equipment setup process, challenges using the device, preferred setup modality, and suggestions for improvement. Four investigators coded transcripts using qualitative analysis software. Themes were identified through iterative discussion and consensus. Each transcript was independently coded by at least two coders, and illustrative quotes were identified.ResultsForty Veterans with an even mix of PAP initiation modalities (Tele-PAP; FTF-PAP) were interviewed. While both delivery and training modalities were generally well received, we identified several patient factors associated with a preference for one modality over the other. These included patients’ preferred learning style, the cost of traveling to the clinic, preexisting otolaryngological problems, and concurrent psychological factors such as post-traumatic stress disorder (PTSD) and claustrophobia. Regardless of modality, many Veterans had trouble recalling who to contact for troubleshooting or refills.DiscussionBased on Veteran interviews, tele-PAP initiation to treat OSA improved accessibility to sleep medicine and reduced costs for Veterans. Successful PAP therapy initiation depends on several factors that should be identified early in the PAP initiation process to enable selection of the optimal mode of care (Tele-PAP vs. FTF-PAP). Our qualitative data, while limited in number and focused on the Veteran population, document patients’ acceptance of tele-PAP and illustrate that the approach is a viable alternative to F2F-PAP.

Abstract Introduction The prevalence of obstructive sleep apnea (OSA) among Veterans is rising, placing increasing demand on the Veterans Health Administration (VHA) and its limited sleep medicine resources. Because access to sleep specialists often constrains timely care, innovative models are needed to streamline OSA diagnosis and treatment. Currently, Medicare and most insurers mandate an in-person or virtual evaluation by a physician or licensed provider before home sleep testing and/or initiation of therapy. The “De-implementation of the Initial Provider Encounter for Diagnosis and Treatment of Obstructive Sleep Apnea: The DREAM (Direct Referral for Apnea Monitoring) Project” evaluates whether replacing the initial sleep provider visit with an electronic chart review or e-consult (the DREAM pathway) improves timeliness to diagnostic testing and initiation of positive airway pressure (PAP) therapy compared with the traditional care pathway. Methods This pragmatic study was conducted across three VA sleep medicine programs (San Francisco, CA; Portland, OR; and Pittsburgh, PA). Veterans referred for evaluation of suspected OSA were followed from the point of referral through diagnostic testing and PAP initiation. Participants were assigned to either the Traditional pathway, which included an initial sleep provider visit, or the DREAM pathway, which omitted this step and substituted an electronic chart review or e-consult. The primary outcomes were time from referral to sleep testing and time from referral to PAP initiation. Group comparisons were made using appropriate statistical tests. Results A total of 1,215 Veterans were included: 921 in the DREAM pathway and 294 in the Traditional pathway. The mean time from referral to sleep testing was 120.4 days (SD = 107.8) for DREAM versus 216.1 days (SD = 136.9) for Traditional care (p < 0.0001). The mean time from referral to PAP initiation was 192.6 days (SD = 108.1) for DREAM and 252.7 days (SD = 121.4) for Traditional care (p < 0.0001). Conclusion Preliminary findings demonstrate that substituting the initial sleep provider encounter with an electronic chart review or e-consult substantially improves timeliness to both diagnostic testing and PAP therapy initiation. Ongoing analyses will examine site-level variation, PAP adherence, and patient satisfaction to inform broader implementation within the VHA network. Support (if any) This work was supported by VA HSR&D Service Merit Award #IIR 15-339.

Objective: By personalizing healthcare to an individual's specific requirements, precision health promises to maximize benefit and minimize harm, thereby maximizing value. We describe here, how in Phase 2 of the Million Veteran Program Computational Health Analytics for Medical Precision to Improve Outcomes Now (MVP CHAMPION), artificial intelligence (AI) and high performance computing (HPC) have been applied to Veteran's electronic health records (EHRs) and genetic data to advance real world precision health. Materials and Methods: Eight concept projects were selected on the basis of potential impact on high burden conditions among Veterans, including heart failure, suicide, lung cancer, diabetes, post COVID 19 sequelae, medication toxicity, and obstructive sleep apnea. Results: Achievements include new and more discriminating risk prediction models to inform medical decision making, multimorbidity aware analytic frameworks, and development and deployment of reusable computational tools. The identification of novel risk factors from genetic data and unstructured text in the EHR has both informed risk prediction and offered new insights for medication repurposing and development. Discussion: We not only confirmed the need for shared infrastructure, data management, and novel AI based workflows to inform precision health, but also found that such programmatic improvements result in valuable mechanistic insights. Conclusion: By building on these foundations through expanded deployment, adaptive modeling, and broader partnerships, the VA DOE collaboration is poised to transform not only the future of Veterans' healthcare, but the broader national landscape of precision health. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols ### Funding Statement This study was funded by MVP000. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used ONLY openly available human data that were originally located at the Department of Veteran's Affairs Electronic Health Record system. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Obstructive sleep apnea (OSA) is a prevalent condition among Veterans affecting 24% and ranking among the top five most common diagnoses in the Veterans Health Administration (VHA). Epidemiologic studies demonstrate a strong association between OSA and cardiometabolic disease. This study describes the temporal distribution of common cardiometabolic comorbidities in relationship to the first sleep test within VHA. This study is a sub-analysis of data from a larger project leveraging Artificial Intelligence (AI) to predict which Veterans with OSA are most likely to develop cardiometabolic comorbidities. Data from 24 million Veteran records collected between 1999 and 2022 were analyzed using Current Procedural Terminology for diagnostic sleep testing, and International Classification of Disease 9 and 10 codes for OSA and cardiometabolic comorbidities. Prevalence of comorbidities was documented within two years prior to the first sleep study (T0) and for up to 22 years afterwards. A preliminary logistic regression model was used to predict the likelihood of developing an additional comorbidity after T0. The analysis identified 1.3 million Veterans who underwent sleep testing within VHA, with 939,954 having at least one comorbidity. Within two years prior to T0 the following comorbidities were observed: hypertension 54%, diabetes mellitus 29%, coronary artery disease 22%, heart failure 8.5%, stroke 8.9%, and atrial fibrillation 7.4%. After T0 the number of Veterans with these comorbidities increased: hypertension 60%, diabetes mellitus 42%, coronary artery disease 33%, heart failure 18%, stroke 16%, and atrial fibrillation 15%. At T0 44% had at least two comorbidities, 21% had at least three comorbidities, 9% had at least four comorbidities. An initial logistic regression predictive model has an AUROC of 0.74 with OSA having an odds ratio of 2.13 for developing a new comorbidity after T0. These findings suggest many Veterans have already developed significant cardiometabolic comorbidities by the time of OSA diagnoses, with additional diagnoses occurring subsequently. This may reflect increased healthcare engagement leading to the diagnosis of comorbidities or potentially indicate a causal relationship. Additional research is needed to better define the relationship between OSA and incident comorbidities. Million Veteran Program MVP063.

Forty percent of Veterans express concern about military toxic exposures (TEs) which may include airborne hazards. Veterans with overseas wartime service and TEs show increased rates of cardiometabolic disorders, including heart disease, stroke, and type 2 diabetes mellitus (T2DM). Additionally, 24% of Veterans have been diagnosed with Obstructive Sleep Apnea (OSA), which is epidemiologically linked to cardiometabolic disease. However, the extent to which OSA modifies the risk of developing cardiometabolic comorbidities after military TEs remains unknown Using data from the VA Corporate Data Warehouse (CDW), we identified Veterans receiving care in the past five years with a wartime record indicating service overseas in an area where TEs were reported. These Veterans were further stratified based on OSA diagnosis and cardiometabolic comorbidities. Of the 8.53 million Veterans receiving care within VA between 2019 and 2024 and who had an overseas wartime service record, 1.32 million (16%) had potential TEs. Among these, 452,140 (34%) had a diagnosis of OSA. In the group with both potential TEs plus OSA, 205,646 (45%) had one or more cardiometabolic comorbidities compared to only 210,468 (25%) in those with no OSA. Veterans with an overseas deployment and potential TEs had higher rates of OSA compared to the general VA population. Furthermore, they were more likely to have at least one or more comorbidities compared to those with an overseas wartime deployment but no OSA. This data suggests that the combination of OSA and military TEs is associated with a higher incidence of cardiometabolic comorbidities, warranting further investigation in this area. Million Veteran Program MVP063

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population. Study Design: Retrospective. Setting: Clinical data in the National COVID Cohort Collaborative database (N3C). Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period. Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29–2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48–3.78; P < 0.001), delta (OR, 3.03; CI, 2.94–3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90–3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35–9.27; P < 0.001). Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings.

Abstract Introduction The VA Telesleep Enterprise Wide Initiative (EWI) operated from 2017 through 2023 and focused on increasing sleep medicine care to rural Veterans. Part of the Telesleep EWI was promotion of telehealth visits to improve access to sleep medicine care for rural Veterans. This report examines the significant growth of telesleep visits during the COVID-19 pandemic and the strong sustainment in Telesleep care in EWI sites post-pandemic. EWI sites participated in weekly clinical support meetings and best practices sharing to foster uptake and improvement of telesleep clinical work. Non EWI sites did not have access this support network. Methods Data regarding clinical visits for sleep medicine at a national level were obtained from the VA Corporate Data Warehouse by trained and experienced data analysts. Data from 2019 through fiscal year 2023 were obtained which spans the pre-pandemic to the post-pandemic time frame. The data were analyzed by medical center based on whether the site was part of the Telesleep EWI or not part of the EWI. In this report only rural Veterans were analyzed. Results From 2019 to 2023, for rural Veterans, the proportion of total sleep medicine visits performed using telehealth modalities increased from 25% to 56% for sites in the Telesleep EWI compared to 16% to 36% in the non EWI sites. Comparing Telesleep visits at the peak of pandemic in 2021-22 to post-pandemic 2023, Telesleep visits peaked at 61% and decreased to 56% in 2023 for the EWI sites and peaked at 52% and decreased to 36% in non EWI sites. Conclusion The COVID -19 pandemic resulted in rapid changes in healthcare delivery for many clinical services including sleep medicine. Post-COVID-19 many clinicians returned to previous care delivery models. In VA, where telesleep medicine virtual care was strongly supported in the EWI, sites showed greater sustainment of virtual care compared to non EWI sites. We speculate that ongoing support of clinicians through training and expert support in the EWI accounted for this better sustainment of virtual care. Support (if any) VA Office of Rural Health; VA Office of Connected Care; VA HSR&D Merit Review

BackgroundIn fiscal year 2021, the Veterans Health Administration (VHA) provided care for sleep disorders to 599,966 Veterans, including 189,932 rural Veterans. To further improve rural access, the VA Office of Rural Health developed the TeleSleep Enterprise-Wide Initiative (EWI). TeleSleep's telemedicine strategies include tests for sleep apnea at the Veteran's home rather than in a sleep lab; Clinical Video Telehealth applications; and other forms of virtual care. In 2017 and 2020, VHA provided 3-year start-up funding to launch new TeleSleep programs at rural-serving VA medical facilities.MethodsIn early 2022, we surveyed leaders of 24 sites that received TeleSleep funding to identify successes, failures, facilitators, and barriers relevant to sustaining TeleSleep implementations upon expiration of startup funding. We tabulated frequencies on the multiple choice questions in the survey, and, using the survey's critical incident framework, summarized the responses to open-ended questions. TeleSleep program leaders discussed the responses and synthesized recommendations for improvement.Results18 sites reported sustainment, while six were “on track.” Sustainment involved medical centers or regional entities incorporating TeleSleep into their budgets. Facilitators included: demonstrating value; aligning with local priorities; and collaborating with spoke sites serving rural Veterans. Barriers included: misalignment with local priorities; and hiring delays. COVID was a facilitator, as it stimulated adoption of telehealth practices; and also a barrier, as it consumed attention and resources. Recommendations included: longer startup funding; dedicated funding for human resources to accelerate hiring; funders communicating with local facility leaders regarding how TeleSleep aligns with organizational priorities; hiring into job classifications aligned with market pay; and obtaining, from finance departments, projections and outcomes for the return on investment in TeleSleep.

Background Travel is a major barrier to healthcare access for Veteran Affairs (VA) patients, and disproportionately affects rural Veterans (approximately one quarter of Veterans). The CHOICE/MISSION acts’ intent is to increase timeliness of care and decrease travel, although not clearly demonstrated. The impact on outcomes remains unclear. Increased community care increases VA costs and increases care fragmentation. Retaining Veterans within the VA is a high priority, and reduction of travel burdens will help achieve this goal. Sleep medicine is presented as a use case to quantify travel related barriers. Objective The Observed and Excess Travel Distances are proposed as two measures of healthcare access, allowing for quantification of healthcare delivery related to travel burden. A telehealth initiative that reduced travel burden is presented. Design Retrospective, observational, utilizing administrative data. Subjects VA patients with sleep related care between 2017 and 2021. In-person encounters: Office visits and polysomnograms; telehealth encounters: virtual visits and home sleep apnea tests (HSAT). Main Measures Observed distance: distance between Veteran’s home and treating VA facility. Excess distance: difference between where Veteran received care and nearest VA facility offering the service of interest. Avoided distance: distance between Veteran’s home and nearest VA facility offering in-person equivalent of telehealth service. Key Results In-person encounters peaked between 2018 and 2019, and have down trended since, while telehealth encounters have increased. During the 5-year period, Veterans traveled an excess 14.1 million miles, while 10.9 million miles of travel were avoided due to telehealth encounters, and 48.4 million miles were avoided due to HSAT devices. Conclusions Veterans often experience a substantial travel burden when seeking medical care. Observed and excess travel distances are valuable measures to quantify this major healthcare access barrier. These measures allow for assessment of novel healthcare approaches to improve Veteran healthcare access and identify specific regions that may benefit from additional resources.

The Veterans Health Administration cares for many veterans with sleep disorders who live in rural areas. The Veterans Health Administration’s Office of Rural Health funded the TeleSleep Enterprise-Wide Initiative (EWI) to improve access to sleep care for rural veterans through creation of national telehealth networks. The TeleSleep EWI consists of (1) virtual synchronous care, (2) home sleep apnea testing, and (3) REVAMP (Remote Veterans Apnea Management Platform), a patient- and provider-facing web application that enabled veterans to actively engage with their sleep care and sleep care team. The TeleSleep EWI was designed as a hub-and-spoke model, where larger sites with established sleep centers care for smaller, rural sites with a shortage of providers. Structured formative evaluation for the TeleSleep EWI is supported by the Veterans Health Administration’s Quality Enhancement Research Initiative and was critical in assessing outcomes and effectiveness of the program. The TeleSleep EWI launched with 7 hubs and 34 spokes (2017) and rapidly expanded to 13 hubs and 63 spokes (2020). The TeleSleep EWI resulted in a significant increase in rural veterans accessing sleep care by utilizing home sleep apnea testing to establish a diagnosis of obstructive sleep apnea and virtual care for follow-up. Rates of virtual care utilization were greater in hubs and spokes participating in the TeleSleep EWI compared with non-EWI sleep programs. Additionally, veterans expressed satisfaction with their virtual care TeleSleep experiences. The TeleSleep EWI successfully increased sleep care access for rural veterans, promoted adoption of virtual care services, and resulted in high patient satisfaction.

PURPOSE:To describe and compare demographic characteristics and comorbidities of rural and urban Veterans diagnosed with sleep disorders, and to evaluate whether rurality is a disparity for sleep care among Veterans.METHODS:Numbers of Veterans with sleep disorders and comorbid conditions were determined using the Department of Veterans Affairs (VA's) Corporate Data Warehouse, a database that contains detailed clinical information for all Veterans who receive VA health care. Comparisons between urban and rural Veterans were conducted for fiscal years (FY) 2010-2021.FINDINGS:The prevalence of diagnosed sleep disorders was similar among rural and urban Veterans from FY2010 to 2021 and increased for both groups during this time period. The prevalence of chronic pulmonary disease, congestive heart failure, and diabetes mellitus was higher for rural Veterans with sleep disorders compared to their urban counterparts. From 2012 to 2021, the percentage of rural Veterans who received sleep care at VA facilities was lower than the percentage of urban Veterans who received VA sleep care during the same time span.CONCLUSIONS:Although rural Veterans exhibited a higher prevalence of 3 comorbid conditions associated with sleep disorders, the prevalence of sleep disorder diagnoses was similar between rural and urban Veterans. Therefore, it is possible that sleep disorders are underdiagnosed among rural Veterans. The fact that rural Veterans received VA sleep care at a lower rate compared to urban Veterans indicates that rurality is a disparity in access to care in this population. VA is addressing this disparity through a variety of programs, including telehealth initiatives.

Background Obstructive sleep apnea (OSA) is a very common and serious health condition which is highly prevalent among U.S. military Veterans. Because the demand for sleep medicine services often overwhelms the availability of such services, it is necessary to streamline diagnosis and treatment protocols. The goals of this study are to, (1) assess the efficacy of de-implementing the initial provider encounter for diagnosis and treatment of OSA; (2) determine the negative predictive value (NPV) of home sleep apnea testing (HSAT); (3) develop HSAT usage recommendations for various at-risk patient populations. Methods This is a large, pragmatic study that will take place in 3 VA sleep medicine programs: San Francisco, CA; Portland, OR; and Pittsburgh, PA. All Veterans referred for new sleep apnea evaluations at these sites will be included in this four-year study. Outcomes will include time from referral for OSA to sleep testing and treatment; positive airway pressure (PAP) treatment adherence measures; patient-reported clinical outcomes and measures of satisfaction; determination of the NPV of HSAT; HSAT usage recommendations for at-risk patient populations. Discussion The DREAM (Direct Referral for Apnea Monitoring) Project will inform sleep medicine providers and clinical organizations regarding strategies to streamline diagnosis and treatment protocols for OSA. Results of this study should have significant impact on clinical practices and professional guidelines. Trial registration The majority of this project is an observational study of clinical procedures. Therefore, clinical trial registration is not required.

Abstract Introduction Obstructive Sleep Apnea (OSA) is very prevalent in the Veterans Administrations (VA) clinical population, affecting about 24% of Veterans. Sleep medicine services in VA suffers from uneven distribution, which especially affects Veterans in rural populations, where care is often not available except by long distance travel. Travel burden is increasingly recognized as a burden on Veteran care that can be ameliorated by telemedicine. Little is known about travel burden and few attempts have been made to quantify it. We have attempted to quantify travel burden for rural Veterans using data from VA's Office of Rural Health supported Enterprise Wide Initiative for Telesleep Medicine. In this project we focus on travel from a Veteran's home to a facility-based sleep clinic visit (traditional face-face visit) vs. how much travel would be avoided if visits were performed using video-based telemedicine with the Veteran at his/her residence. Methods Purpose built geocoding software (validated in prior studies) was used to quantify the driving distance from the Veterans home zipcode to the zipcode of the facility where the visits would were performed. The data were taken from the VA's national corporate data warehouse (CDW). Over 4 million sleep encounters were coded. CPT4 codes were used to define the clinic visit encounters from 2016 through 2020. We set the travel range where telemedicine is reasonable based on distance at greater than 40 miles from the VA medical center which is how VA currently defines "distant travel". Results No. of Encounters (thous) 2016, 557; 2017, 623; 2018, 678; 2019, 667; 2020, 420Miles ObsTravel (mil) 2016, 38; 2017, 42; 2018, 45; 2019, 43; 2020, 27 Miles Travel if telemed used (mil) 2016, 25; 2017, 27; 2018, 29; 2019, 27: 2020, 17Difference (mil miles) 2016, 13; 2017, 15; 2018, 16; 2019, 16 2020, 10Between 10 and 16 million miles could be saved each year for sleep medicine visits if all travel > 40 miles was converted to video home visits. Conclusion Travel burden in this analysis, defined by miles driven to and from a sleep medicine encounter, could be dramatically reduced if telemedicine visits were used for sleep apnea evaluation and management. This reduction in travel equates to a reduction in automobile related use-costs, lower carbon footprint, fewer automobile crashes with injury and death. Assuming that clinical effectiveness of home telemedicine is comparable to traditional visits, these data support the vigorous adoption of telemedicine for sleep medicine services. Support (If Any) VA Office of Rural Health; Measurement QUERI, San Francisco VA Medical

The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.

ABSTRACTImportanceSince late 2019, the novel coronavirus SARS-CoV-2 has given rise to a global pandemic and introduced many health challenges with economic, social, and political consequences. In addition to a complex acute presentation that can affect multiple organ systems, there is mounting evidence of various persistent long-term sequelae. The worldwide scientific community is characterizing a diverse range of seemingly common long-term outcomes associated with SARS-CoV-2 infection, but the underlying assumptions in these studies vary widely making comparisons difficult. Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 infection (PASC or “long COVID”), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations of long COVID.ObservationsWe identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts of individuals three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to Human Phenotype Ontology (HPO) terms.Conclusions and RelevancePatients and clinicians often use different terms to describe the same symptom or condition. Addressing the heterogeneous and inconsistent language used to describe the clinical manifestations of long COVID combined with the lack of standardized terminologies for long COVID will provide a necessary foundation for comparison and meta-analysis of different studies. Translating long COVID manifestations into computable HPO terms will improve the analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared or pooled more effectively. Furthermore, mapping lay terminology to HPO for long COVID manifestations will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, which may improve the stratification and thereby diagnosis and treatment of long COVID.

Abstract Introduction Rurality is a known contributor to health disparities, including Sleep medicine. Over 1 million (>350,000 rural, >650,000 non-rural) Veterans who received care from VHA in 2020 have obstructive sleep apnea (OSA). VHA’s Office of Rural Health (ORH) TeleSleep Program (FY17-20) aimed to increase access to sleep care for rural veterans by establishing telehealth services at 12 hubs and 63 spokes across the country. The TeleSleep program has three components: (1) Telemedicine; (2) Home Sleep Apnea Testing (HSAT); and (3) REVAMP (Remote Veterans Apnea Management Platform), a web-application for comprehensive sleep apnea care. Methods Each of the three TeleSleep components was evaluated independently using specific metrics. We report here on the impact of leveraging telemedicine to improve access to sleep care. Patient care encounters are defined by VA-specific stop codes and are thus identifiable as telehealth or in-person visits. Data used in the evaluation were obtained from the VA Corporate Data Warehouse. Results During FY20, 33,743 rural Veterans had 74,458 sleep encounters within the TeleSleep network. Visits included in-person care, virtual initial and follow up visits, electronic consultations, asynchronous telehealth (remote monitoring of PAP data and HSAT), remote PAP initiation by video or phone, and email exchanges between patients and providers. Between FY17-20, the number of rural Veterans seen for sleep-related disorders at TeleSleep sites tripled (from 10,702 to 33,743), and the number of encounters for sleep-related disorders more than doubled (from 32,894 to 74,458). In FY20, 72% (up from 53% in FY18) of rural Veterans at the TeleSleep hubs or spokes had at least one virtual sleep visit. This was significantly higher than non-TeleSleep VA sites where only 64% of rural Veterans had virtual visits (72% vs. 64%; p<0.001). In addition, the proportion of Veterans who had face-to-face only visits (28% at TeleSleep sites vs. 36% at non-TeleSleep sites; p<0.001) indicates that the TeleSleep program was highly successful in promoting virtual (instead of face-to-face) visits. Conclusion The ORH TeleSleep Program has improved access to comprehensive sleep care for rural Veterans by increasing the proportion and type of sleep visits conducted virtually vs. in person. Support (if any) Funding provided by VHA Office of Rural Health

RATIONALE:Patients with seizure disorders have relatively high rates of comorbid psychological and sleep disorders. Because these can profoundly affect quality of life, early recognition and treatment are of potential benefit. As a quality improvement project, we evaluated the performance and utility of a set of mental health and sleep quality screening questionnaires in patients admitted to a VA seizure monitoring unit (SMU). METHODS:Questionnaires, including the Beck Depression Inventory-II (BDI-II), the post-traumatic stress disorder (PTSD) checklist (PCL), the Quality of Life in Epilepsy Inventory-31 (QOLIE-31), and the Pittsburgh Sleep Quality Index (PSQI), were administered to 100 patients admitted to the Portland VAMC SMU. Scored results were entered into the electronic medical record (EMR) within 72 h of hospital admission. We assessed how many patients exceeded questionnaire cutoff scores, and whether these patients had prior mental health or sleep diagnoses or evaluations within the six months preceding admission. Following hospital discharge, providers completed a survey regarding the utility of the questionnaire results. We also reviewed EMR documented mental health and sleep visits during the six months following the SMU admission. RESULTS:Forty-seven patients (47.5%) exceeded the cutoff score for the BDI-II, including 15 without an admission diagnosis of depression, and 14 who had not seen a mental health provider in the previous six months. Similarly, 33 patients (33.3%) exceeded the cutoff score for the PCL, including nine without a diagnosis of PTSD. Scores on the BDI-II and PCL were highly correlated with the QOLIE-31 total score (r = 0.7). Seventy patients (70.7%) exceeded the cutoff score for poor sleep quality, and 37 did not have a sleep disorder diagnosis. Providers indicated that the questionnaire results were moderately or very helpful in most cases and influenced discharge recommendations to patients and referring providers in more than 50% of cases. Discharge recommendations for mental health or sleep follow-up were associated with EMR documented consultations within the six months following SMU admission. CONCLUSIONS:The results suggest that a standard set of screening questionnaires can identify SMU patients at risk for mental health and sleep disorders, including patients not currently diagnosed or recently evaluated. Questionnaire results were perceived as helpful by providers and influenced discharge recommendations. Given that these disorders are treatable and have a major influence on health-related quality of life, the effort to collect and document this information is well justified.

The prevalence of diagnosed sleep disorders among Veterans treated at Veterans Affairs (VA) medical facilities increased significantly during fiscal years (FY) 2012 through 2018. Specifically, the prevalence of sleep-related breathing disorders (SRBD) increased from 5.5% in FY2012 to 22.2% in FY2018, and the prevalence of insomnia diagnoses increased from 7.4% in FY2012 to 11.8% in FY2018. Consequently, Veterans' demand for sleep medicine services also increased significantly between FY2012-2018, with steady increases in the annual number of VA sleep clinic appointments during this period (<250,000 in FY 2012; >720,000 in FY2018). Common co-morbid conditions among Veterans diagnosed with sleep disorders include obesity, diabetes, congestive heart failure, depression, post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI). To address this healthcare crisis, the Veterans Health Administration (VHA) developed and/or implemented numerous innovations to improve the quality and accessibility of sleep care services for Veterans. These innovations include a TeleSleep Enterprise-Wide Initiative to improve rural Veterans’ access to sleep care; telehealth applications such as the Remote Veteran Apnea Management Platform (REVAMP), Clinical Video Telehealth, and CBT-i Coach; increased use of home sleep apnea testing (HSAT); and programs for Veterans who experience sleep disorders associated with obesity, PTSD, TBI and other conditions.

BACKGROUND:Computer-based documentation (CBD) is used commonly throughout the world to track patient care and clinical workloads. However, if capture of clinical services within the electronic health record (EHR) is not implemented properly, patient care services and workload credit will be inaccurate, which impacts business decisions related to demand for care and resources allocated to meet the demand. Understaffing of medical personnel can contribute to delays in treatment, missed treatments, and workforce turnover.OBJECTIVE:To illustrate the impact of CBD procedures on health care workload assessment and resource allocation, this article uses data from the US Department of Veterans Affairs Corporate Data Warehouse to provide examples from the Veterans Health Administration (VHA) sleep medicine programs.DISCUSSION:Inaccurate CBD led to underreporting of sleep medicine services provided at VHA facilities nationwide and contributed to insufficient allocation of resources and personnel. Recent modifications in CBD protocols (Stop Codes) improved the accuracy of data capture and reporting while providing VHA sleep programs with data they can use to advocate for workforce expansion to meet patient care needs.CONCLUSIONS:Inaccurate CBD of clinical workloads can result in inadequate allocation of health care personnel and resources to meet the needs of patients. Untreated sleep disorders are associated with increased risk of depression, anxiety, impaired neurocognitive functions, cardiovascular disease, motor vehicle accidents, and premature death. Educating health care providers and administrators on the importance of accurate designation of clinical services within the EHR is necessary to facilitate improvements in health care availability and delivery.

Musculoskeletal loss in actual or simulated microgravity occurs at a high rate. Bed rest studies are a reliable ground-based spaceflight analogue that allow for direct comparison of intervention and control participants. The aim of this review was to investigate the impact of exercise compared to no intervention on bone mineral density (BMD) and muscle cross-sectional area (muscle CSA) in bed rest studies relative to other terrestrial models. Eligible bed rest studies with healthy participants had an intervention arm with an exercise countermeasure and a control arm. A search strategy was implemented for MEDLINE. After screening, eight studies were identified for inclusion. Interventions included resistive exercise (RE), resistive vibration exercise (RVE), flywheel resistive exercise, treadmill exercise with lower body negative pressure (LBNP) and a zero-gravity locomotion simulator (ZLS). Lower limb skeletal sites had the most significant BMD losses, particularly at the hip which reduced in density by 4.59% (p < 0.05) and the tibial epiphysis by 6% (p < 0.05). Exercise attenuated bone loss at the hip and distal tibia compared to controls (p < 0.05). Muscle CSA changes indicated that the calf and quadriceps were most affected by bed rest. Exercise interventions significantly attenuated loss of muscle mass. ZLS, LBNP treadmill and RE significantly attenuated bone and muscle loss at the hip compared to baseline and controls. Despite exercise intervention, high rates of bone loss were still observed. Future studies should consider adding bisphosphonates and pharmacological/nutrition-based interventions for consideration of longer-duration missions. These findings correlate to terrestrial bed rest settings, for example, stroke or spinal-injury patients.