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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.
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Informática , Sono , Canadá , HumanosRESUMO
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 72â¯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 (râ¯=â¯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.
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Qualidade de Vida , Transtornos do Sono-Vigília , Depressão/diagnóstico , Depressão/epidemiologia , Humanos , Saúde Mental , Convulsões/diagnóstico , Convulsões/epidemiologia , Sono , Transtornos do Sono-Vigília/diagnóstico , Transtornos do Sono-Vigília/epidemiologia , Transtornos do Sono-Vigília/etiologia , Inquéritos e QuestionáriosRESUMO
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.
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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.
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Acessibilidade aos Serviços de Saúde , Transtornos do Sono-Vigília/epidemiologia , Telemedicina , Veteranos/estatística & dados numéricos , Lesões Encefálicas Traumáticas , Comorbidade , Humanos , Obesidade , Prevalência , Distúrbios do Início e da Manutenção do Sono/epidemiologia , Distúrbios do Início e da Manutenção do Sono/terapia , Transtornos do Sono-Vigília/terapia , Transtornos de Estresse Pós-Traumáticos , Estados Unidos/epidemiologia , United States Department of Veterans AffairsRESUMO
STUDY OBJECTIVES: (1) Review the prevalence and comorbidity of sleep disorders among United States military personnel and veterans. (2) Describe the status of sleep care services at Veterans Health Administration (VHA) facilities. (3) Characterize the demand for sleep care among veterans and the availability of sleep care across the VHA. (4) Describe the VA TeleSleep Program that was developed to address this demand. METHODS: PubMed and Medline databases (National Center for Biotechnology Information, United States National Library of Medicine) were searched for terms related to sleep disorders and sleep care in United States military and veteran populations. Information related to the status of sleep care services at VHA facilities was provided by clinical staff members at each location. Additional data were obtained from the VA Corporate Data Warehouse. RESULTS: Among United States military personnel, medical encounters for insomnia increased 372% between 2005-2014; encounters for obstructive sleep apnea (OSA) increased 517% during the same period. The age-adjusted prevalence of sleep disorder diagnoses among veterans increased nearly 6-fold between 2000-2010; the prevalence of OSA more than doubled in this population from 2005-2014. CONCLUSIONS: Most VA sleep programs are understaffed for their workload and have lengthy wait times for appointments. The VA Office of Rural Health determined that the dilemma of limited VHA sleep health care availability and accessibility might be solved, at least in part, by implementing a comprehensive telehealth program in VA medical facilities. The VA TeleSleep Program is an expansion of telemedicine services to address this need, especially for veterans in rural or remote regions. CITATION: Sarmiento KF, Folmer RL, Stepnowsky CJ, Whooley MA, Boudreau EA, Kuna ST, Atwood CW, Smith CJ, Yarbrough WC. National expansion of sleep telemedicine for veterans: the telesleep program. J Clin Sleep Med. 2019;15(9):1355-1364.
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Militares/estatística & dados numéricos , Transtornos do Sono-Vigília/diagnóstico , Transtornos do Sono-Vigília/terapia , Telemedicina/métodos , Veteranos/estatística & dados numéricos , Acessibilidade aos Serviços de Saúde , Humanos , Transtornos do Sono-Vigília/epidemiologia , Estados Unidos/epidemiologia , United States Department of Veterans AffairsRESUMO
OBJECTIVES: The long-term outcome of patients with psychogenic nonepileptic seizures (PNES) is of importance given the disabling symptoms and tendency to affect patients early in their productive years. Health care utilization (HCU) is an important outcome measure reflecting overall health status and costs. There is little information regarding long-term HCU following diagnosis of PNES. METHODS: We retrospectively reviewed records of Veterans diagnosed with PNES during epilepsy monitoring unit (EMU) evaluation. For the three-year period following diagnosis of PNES, we reviewed emergency department (ED) visits, hospitalizations, outpatient clinic visits, and radiology procedures. We compared the three years following PNES diagnosis with the three years preceding diagnosis. We also compared patients with PNES and patients with epileptic seizures (ES). RESULTS: Emergency department visits and hospitalizations were more frequent in patients with PNES compared with those in patients with ES (p=0.01). There was no overall improvement in HCU during the three-year interval following diagnosis of PNES. A transient decrease during the year following diagnosis was not sustained over three-year follow-up. Pain complaints rather than seizures were the most common reason for presentation, whereas the opposite was true for patients with ES (p<0.01). There was a sharp decrease in neurology outpatient visits (p<0.001) and a decrease in primary care visits (p<0.05) after PNES was diagnosed. Total outpatient visits were unchanged. CONCLUSIONS: Overall HCU did not improve during the three years following diagnosis of PNES, compared with three years preceding diagnosis. The results add to studies documenting poor seizure outcomes following diagnosis of PNES and underscore the need for more effective and comprehensive treatments, addressing comorbid symptoms.