Association between telemedicine use and diabetes risk factor assessment and control in a primary care network.

PURPOSE: Our study examined whether telemedicine use in primary care is associated with risk factor assessment and control for patients with diabetes mellitus. METHODS: This was a retrospective, 1:1 propensity score matched cohort study conducted in a primary care network between February 2020 and December 2020. Participants included patients with diabetes mellitus, ages 18 to 75. Exposure of interest was any telemedicine visit. We determined whether hemoglobin A1c (HbA1c), blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) were assessed for each patient. For each risk factor, we also determined whether the risk factor was controlled when they were assessed (i.e., last HbA1c < 8.0%, BP < 130/80 mmHg, LDL-C < 100 mg/dL). RESULTS: After 1:1 propensity score matching, we identified 1,824 patients with diabetes during the study period. Telemedicine use was associated with a lower proportion of patients with all three risk factors assessed (162/912 [18%], versus 408/912 [45%], p < 0.001). However, when individual risk factors were assessed, telemedicine use did not impact risk factor control. When compared with patients with in-person visit only, the odds ratio (OR) for HbA1c < 8% was 1.04 (95% CI 0.74 to 1.46, p = 0.23) for patients with any telemedicine visit. Similarly, the OR for BP < 130/80 mmHg was 1.08 (95% CI 0.85-1.36 p = 0.53), and the OR for LDL-C < 100 mg/dL was 1.14 (95% CI 0.76-1.72, p = 0.52). CONCLUSIONS: Telemedicine use was associated with gaps in risk factor assessment for patients with diabetes during the COVID-19 pandemic, but had limited impact on whether risk factors were controlled.

Impact of telemedicine use on blood pressure control during the covid-19 pandemic

Background: Telemedicine use vastly expanded during the Covid-19 pandemic, with uncertain impact on cardiovascular care. quality. Objectives: To examine the association between telemedicine use and blood pressure (BP) control. Methods: This is a retrospective cohort study of 32,727 adult patients with hypertension (HTN) seen in primary care and cardiology clinics at an urban, academic medical center from February to December, 2020. The primary outcome was poor BP control, defined as having no BP recorded OR if the last recorded BP was ≥140/90 mmHg. Multivariable logistic regression was used to assess the association between telemedicine use during the study period (none, 1 telemedicine visit, 2+ telemedicine visits) and poor BP control, adjusting for demographic and clinical characteristics. Results: During the study period, no BP was recorded for 486/20,745 (2.3%) patients with in-person visits only, for 1,863/6,878 (27.1%) patients with 1 telemedicine visit, and for 1,277/5,104 (25.0%) patients with 2+ telemedicine visits. After adjustment, telemedicine use was associated with poor BP control (odds ratio [OR], 2.06, 95% confidence interval [CI] 1.94 to 2.18, p<0.001 for 1 telemedicine visit, and OR 2.49, 95% CI 2.31 to 2.68, p<0.001 for 2+ telemedicine visits;reference, in-person visit only). This effect disappears when analysis was restricted to patients with at least one recorded BP (OR 0.89, 95% CI 0.83 to 0.95, p=0.001 for 1 telemedicine visit, and OR 0.91, 95% CI 0.83 to 0.99, p=0.03 for 2+ telemedicine visits). Conclusions: BP is less likely to be recorded during telemedicine visits, but telemedicine use does not negatively impact BP control when BP is recorded.

COVID-19 related worries and sleep disturbances in patients previously hospitalized with COVID-19 illness

Introduction: In patients hospitalized for COVID-19 illness, sleep disturbances after discharge may impact quality of life and prognosis. We examined the relationship of COVID-19-related worries with sleep disturbances in patients three months after COVID-19 hospitalization. Methods: Patients hospitalized for COVID-19 illness completed a survey three months post-discharge (n=153). We measured COVID- 19-related worry along two domains: worry directly related to the disease (COVID-illness worry) and worry related to the socioeconomic impact of the pandemic (COVID-impact worry). COVID-illness worry included worry regarding: 1) getting COVID again, 2) dying from COVID, 3) family members getting COVID, 4) losing a loved one to COVID, 5) unknowingly infecting others with COVID, 6) having significant financial burdens because of COVID. COVID-impact included worry regarding: 1) employment loss, 2) not having enough food, 3) not having access to medical care/medications, 4) not having access to mental health care/medications, 5) reduction in interactions with other people, 6) separation from family members, 7) being lonely. Patients rated how much they worried about each item on a 4-point scale (not at all, a little, moderately, extremely). Scores on each domain were summed to reflect overall severity. Past month sleep was assessed for insomnia symptoms (none, mild, moderate, severe, very severe) and self-reported sleep duration. Binary logistic regression was used to evaluate the association of COVID-illness worry and COVID-impact worry, separately, with sleep measures, adjusting for age, sex, race/ethnicity, and presence of persistent COVID-related symptoms. Results: The prevalence of insomnia (moderate, severe, or very severe symptoms) and short sleep duration (<6 h/day) was 47.0% and 39.2%, respectively. COVID-illness worry severity was significantly associated with presence of insomnia (OR: 1.91, 95% CI: 1.13-3.23, p=0.016) and short sleep (OR: 2.20, 95% CI: 1.25-3.86, p=0.006). In a separate model, COVID-impact worry severity was significantly associated with presence of insomnia (OR: 1.98, 95% CI: 1.23-3.19, p=0.005) and short sleep (OR: 2.11, 95% CI: 1.26-3.55, p=0.005). Conclusion: Sleep disturbances are common among patients previously hospitalized with COVID-19 illness, and COVID-19 related worries are associated with insomnia and short sleep. Additional research is needed to determine whether addressing COVID-19 related worries reduces sleep disturbance, which in turn may promote post- COVID recovery.

When a global crisis closes your clinic: A telemedicine approach for transient ischemic attack and minor stroke care during the COVID-19 pandemic

Introduction: Recent work has demonstrated the safety and feasibility of rapid outpatient evaluation for presentations of TIA and non-disabling stroke. Our outpatient TIA and stroke clinic, Rapid Access Vascular Evaluation-Neurology (RAVEN) clinic, instituted in 2016, encountered unprecedented challenges in operations during the COVID-19 surge in New York City, leading to the creation of a telemedicine approach to minimize patient and staff exposure risk. To date, few virtual TIA/stroke clinics have reported on safety and feasibility outcomes. Hypothesis: We hypothesized that rapid follow-up of patients with suspected TIA and minor stroke via telemedicine would be feasible and safe during the pandemic. Methods/Results: We performed a retrospective chart review of patients with TIA and minor stroke who were referred to the virtual clinic from the emergency department (ED) between March and June 2020 (the local peak of the COVID-19 pandemic) when RAVEN in-person visits were suspended. A total of 24 patients were discharged early from the ED and referred for RAVEN evaluation with 20 patients evaluated as scheduled;4 were lost to RAVEN follow-up. Ultimately, 60% of these patients were diagnosed with TIA or minor stroke after completing their remote evaluation;the rest were diagnosed as stroke mimics (seizure, migraine with aura, neuropathy, peripheral vertigo, stroke recrudescence). The median NIHSS calculated at initial ED evaluation was 1 with a maximum NIHSS of 5. A new medical intervention for secondary prevention was prescribed for 70% of patients prior to ED discharge. Amongst patients contacted by phone 3-5 months post- RAVEN evaluation, 4 of 15 had an increased modified Rankin score. Of the 24 patients referred for RAVEN evaluation, 7 returned to the ED within 90 days, with 3 patients citing neurologic complaints. On follow-up via phone conducted 2-5 months after RAVEN evaluation, 3 of 17 patients selfreported either a positive COVID-19 test or suspected COVID-19 diagnosis over the study period. Conclusion: A telemedicine-based approach to evaluate TIA and stroke in the RAVEN model helped limit patient infection risk, optimize resource allocation, establish accurate, timely diagnoses, and effectively implement secondary prevention strategies.