Interventions to Increase Leukocyte Testing during Treatment with Dimethyl Fumarate

Dimethyl fumarate (DMF), a treatment for multiple sclerosis, may cause leukopenia and infection. Accordingly, periodic white blood cell (WBC) monitoring is recommended. We sought to evaluate the US Department of Veteran Affairs’ safety program which provides facilities with a list of patients prescribed DMF therapy without a documented white blood cell count (WBC). We identified 118 sites with patients treated with DMF from 1/1/2016 through 9/30/2016. Each site was asked if any of seven interventions were used to improve WBC monitoring (academic detailing, provider education without academic detailing, electronic clinical reminders, request for provider action plan, draft orders for WBC monitoring, patient mailings, and patient calls). The survey response rate was 78%. For the 92 responding sites (78%) included sites (1115 patients) the mean rate of WBC monitoring was 54%. In multivariate analysis, academic detailing increased the rate by 17% (95% CI 4 to 30%, p = 0.011) and provider education increased the rate by 9% (95% CI 0.6 to 18%, p = 0.037). The WBC monitoring rate increased by 3.8% for each additional intervention used (95% CI 1.2–6.4%, p = 0.005). Interventions focused on the physician, including academic detailing, were associated with improved WBC monitoring for patients at risk for leukopenia from DMF treatment.

710 Association of Social Isolation, Perceived Stress, and CPAP Use in Sleep Medicine Patients during the COVID-19 Pandemic

Introduction Due to the COVID-19 pandemic, many individuals are likely experiencing increased stress and social isolation. This study aimed to examine the effect of perceived stress and social isolation on self-reported continuous positive airway pressure (CPAP) use and treatment adherence among sleep medicine clinic patients during the pandemic. Methods Between June-November 2020, 81 sleep medicine clinic patients (54.8±15.9y, 44% male, 69% Caucasian) completed an online survey that included self-reported changes in CPAP use and using CPAP as advised; and PROMIS Social Isolation and Perceived Stress Scale (PSS). CPAP measures were categorized based on reported changes during the pandemic. Stepwise logistic regression was performed using SAS to determine if Social Isolation and PSS predicted change in CPAP measures. Results Among participants, 53% reported using CPAP. Out of those, 61% reported change, 16% reported no change, and 23% reported they do not know if there is a change in using CPAP as advised during the pandemic. Social Isolation predicted an increase in odds of CPAP use by a factor of 1.15 (p=0.024). PSS predicted a decrease in odds of using CPAP therapy as advised by a factor of 0.86 (p=0.049). Conclusion Increases in perceived stress predicted lower odds of utilizing CPAP as advised. Increases in self-reported social isolation predicted greater odds of CPAP use in sleep medicine clinic patients during the COVID-19 pandemic. Addressing stressors/coping and social isolation/support as part of routine clinical care in sleep medicine clinic patients is advised. Support (if any) This work is supported by National Institutes of Health Grant # R01NR018342 (PI: Nowakowski) and by the Department of Veteran Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13–413).

Intimate partner violence within Australian Defence Force families: an exploratory study

International studies indicate a growing problem of intimate partner violence within military families. Despite this, there has been little research into intimate partner violence perpetrated by Australian Defence Force personnel or veterans. A thematic analysis of secondary data was conducted to explore the organisational and social drivers that influence intimate partner violence occurrences by Australian Defence Force personnel, and how the Australian Defence Force enforces its zero-tolerance policy on domestic violence perpetration. Results revealed that the Australian Defence Force and Department of Veteran Affairs made no statements regarding intimate partner violence as a problem for military personnel, despite this study indicating that this population are at a greater risk of perpetration. The Australian Defence Force attributed intimate partner violence causation to ‘abnormal’ individuals or situations. This ignores the culture of hypermasculinity and emphasis on operational effectiveness that was enforced during Australian Defence Force training, and that emerged as a continuous theme throughout the results.

1180 The Use Of Natural Language Processing To Extract Data From Psg Sleep Study Reports Using National Vha Electronic Medical Record Data

Introduction In 2007, Congress asked the Department of Veteran Affairs to pay closer attention to the incidence of sleep disorders among veterans. We aimed to use natural language processing (NLP), a method that applies algorithms to understand the meaning and structure of sentences within Electronic Health Record (EHR) patient free-text notes, to identify the number of attended polysomnography (PSG) studies conducted in the Veterans Health Administration (VHA) and to evaluate the performance of NLP in extracting sleep data from the notes. Methods We identified 481,115 sleep studies using CPT code 95810 from 2000-19 in the national VHA. We used rule-based regular expression method (phrases: “sleep stage” and “arousal index”) to identify attended PSG reports in the patient free-text notes in the EHR, of which 69,847 records met the rule-based criteria. We randomly selected 178 notes to compare the accuracy of the algorithm in mining sleep parameters: total sleep time (TST), sleep efficiency (SE) and sleep onset latency (SOL) compared to human manual chart review. Results The number of documented PSG studies increased each year from 963 in 2000 to 14,209 in 2018. System performance of NLP compared to manually annotated reference standard in detecting sleep parameters was 83% for TST, 87% for SE, and 81% for SOL (accuracy benchmark ≥ 80%). Conclusion This study showed that NLP is a useful technique to mine EHR and extract data from patients’ free-text notes. Reasons that NLP is not 100% accurate included, the note authors used different phrasing (e.g., “recording duration”) which the NLP algorithm did not detect/extract or authors omitting sleep continuity variables from the notes. Nevertheless, this automated strategy to identify and extract sleep data can serve as an effective tool in large health care systems to be used for research and evaluation to improve sleep medicine patient care and outcomes. Support This material is based upon work supported in part by the Department of Veteran Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). Dr. Nowakowski is also supported by a National Institutes of Health (NIH) Grant (R01NR018342).

1156 Polysomnographic Total Sleep Time: A Novel Biomarker For Dementia

Introduction Neuroprotection, early diagnosis, and behavioral intervention are national priorities for dementia research. Sleep duration is emerging as an important potential remediable risk factor. In this study, we examined whether total sleep time (TST) derived from attended overnight polysomnography (PSG) studies is associated with an increased prevalence of dementia diagnosis and determined the optimal cut-point. Methods We identified 69,847 PSG sleep studies using CPT code 95810 from 2000-19 in the US Department of Veteran Affairs (VA) national database of patient care. We used natural language processing to verify PSG reports and extract TST values from the patient free-text notes. We examined a TST of 240-420 minutes in 10-minute increments using a run chart (time series) approach to determine the optimal cut-point for determining greater odds of dementia. Results Patients had a mean age of 55.4±13.8, 91.5% were male, and 64% were Caucasian. PSG studies revealed a mean TST of 310.6±79.5 minutes. The run chart time series analysis revealing < 360 minutes being the optimal cut-point for increased odds of dementia (OR: 1.64, 95% CI: 1.36-1.99, p<.05). Conclusion Lower TST predicted higher prevalence of dementia diagnosis. TST of 360 minutes may serve as the optimal cut-point to determine greater odds of dementia. This is an important study examining PSG sleep duration and the prevalence of dementia across 19 years in the largest integrated healthcare system in the US. TST may function as a potential biomarker for developing dementia. Support This material is based upon work supported in part by the Department of Veteran Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). Dr. Nowakowski is also supported by a National Institutes of Health (NIH) Grant (R01NR018342).

1157 Comparison Of Polysomnography Total Sleep Time In Veterans With A Dementia Diagnosis, Incipient Dementia, And No Dementia

Introduction Neuroprotection, early diagnosis, and behavioral intervention are national priorities for dementia research. Sleep duration is emerging as an important potential remediable risk factor. In this study, we examined the total sleep time derived from overnight polysomnography (PSG) studies in veterans with a current dementia diagnosis at the time of PSG study (dementia), future diagnosis of dementia following the PSG study (incipient dementia), and no diagnosis of dementia at any time point (no dementia) over a 19-year period. Methods We identified 69,847 PSG sleep studies using CPT code 95810 and all-cause dementia diagnosis using ICD 9/10 codes (e.g., F03.90) from 2000-19 in the US Department of Veteran Affairs (VA) national database. To be included patients must have ≥ 1 VA visits in 12 months leading up to PSG. Dementia diagnosis must be documented on two separate visits between 12 months prior to 6 months following PSG for current dementia group and anytime after the PSG for incipient dementia. We used natural language processing to extract TST values from the patient free-text notes. Analysis of variance was used to compare PSG TST of the three groups. Results Patients had a mean age of 55.4±13.8 at the time of PSG study, 91.5% were male, and 64% were Caucasian. TST of dementia patients (N=1,031) was m=257±110m (d=0.33, p<.05), incipient dementia (N=1,875) was m=253±116m (d=0.35, p<.05) versus no dementia (61,871) m=292±104mins. Conclusion Patients with a diagnosis of dementia at the time of PSG study and patients that went on to receive a diagnosis following their PSG study had a significantly lower total sleep time compared to patients that have never received a dementia diagnosis. This is an important study that compares sleep duration during overnight PSG studies and dementia diagnosis across 19 years in the largest integrated healthcare system in the US. Support This material is based upon work supported in part by the Department of Veteran Affairs, Veterans Health Administration, Office of Research and Development, and the Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). Dr. Nowakowski is also supported by a National Institutes of Health (NIH) Grant (R01NR018342).

Medication Use among Veterans across Health Care Systems

SummaryIntroduction: Dual healthcare system use can create gaps and fragments of information for patient care. The Department of Veteran Affairs is implementing a health information exchange (HIE) program called the Virtual Lifetime Electronic Record (VLER), which allows providers to access and share information across healthcare systems. HIE has the potential to improve the safety of medication use. However, data regarding the pattern of outpatient medication use across systems of care is largely unknown. Therefore, the objective of this study is to describe the prevalence of medication dispensing across VA and non-VA health care systems among a cohort Veteran population Methods: This study included all Veterans who had two outpatient visits or one inpatient visit at the Indianapolis VA during a 1-year period prior to VLER enrollment. Source of medication data was assessed at the subject level, and categorized as VA, INPC (non-VA), or both. The primary target was identification of sources for medication data. Then, we compared the mean number of prescriptions, as well as overall and pairwise differences in medication dispensing.Results: Out of 52,444 Veterans, 17.4% of subjects had medication data available in a regional HIE. On average, 40 prescriptions per year were prescribed for Veterans who used both sources compared to 29 prescriptions per year from VA only and 25 prescriptions per year from INPC only sources. The annualized prescription rate of Veterans in the dual use group was 36% higher than those who had only VA data available and 61% higher than those who had only INPC data available.Conclusions: Our data demonstrated that 17.4% of subjects had medication use identified from non-VA sources, including prescriptions for antibiotics, antineoplastics, and anticoagulants. These data support the need for HIE programs to improve coordination of information, with the potential to reduce adverse medication interactions and improve medication safety.