Telemedicine is associated with reduced socioeconomic disparities in outpatient clinic no-show rates.

INTRODUCTION: The global pandemic caused by coronavirus (COVID-19) sped up the adoption of telemedicine. We aimed to assess whether factors associated with no-show differed between in-person and telemedicine visits. The focus is on understanding how social economic factors affect patient no-show for the two modalities of visits. METHODS: We utilized electronic health records data for outpatient internal medicine visits at a large urban academic medical center, from February 1, 2020 to December 31, 2020. A mixed-effect logistic regression was used. We performed stratified analysis for each modality of visit and a combined analysis with interaction terms between exposure variables and visit modality. RESULTS: A total of 111,725 visits for 72,603 patients were identified. Patient demographics (age, gender, race, income, partner), lead days, and primary insurance were significantly different between the two visit modalities. Our multivariable regression analyses showed that the impact of sociodemographic factors, such as Medicaid insurance (OR 1.23, p < 0.01 for in-person; OR 1.03, p = 0.57 for telemedicine; p < 0.01 for interaction), Medicare insurance (OR 1.11, p = 0.04 for in-person; OR 0.95, p = 0.32 for telemedicine; p = 0.03 for interaction) and Black race (OR 1.36, p < 0.01 for in-person; OR 1.20, p < 0.01 for telemedicine; p = 0.03 for interaction), on increased odds of no-show was less for telemedicine visits than for in-person visits. In addition, inclement weather and younger age had less impact on no-show for telemedicine visits. DISCUSSION: Our findings indicated that if adopted successfully, telemedicine had the potential to reduce no-show rate for vulnerable patient groups and reduce the disparity between patients from different socioeconomic backgrounds.

Quantifying Utilitarian Outcomes to Inform Triage Ethics: Simulated Performance of a Ventilator Triage Protocol under Sars-CoV-2 Pandemic Surge Conditions.

BACKGROUND: Equitable protocols to triage life-saving resources must be specified prior to shortages in order to promote transparency, trust and consistency. How well proposed utilitarian protocols perform to maximize lives saved is unknown. We aimed to estimate the survival rates that would be associated with implementation of the New York State 2015 guidelines for ventilator triage, and to compare them to a first-come-first-served triage method. METHODS: We constructed a simulation model based on a modified version of the New York State 2015 guidelines compared to a first-come-first-served method under various hypothetical ventilator shortages. We included patients with SARs-CoV-2 infection admitted with respiratory failure requiring mechanical ventilation to three acute care hospitals in New York from 3/01/2020 and 5/27/2020. We estimated (1) survival rates, (2) number of excess deaths, (3) number of patients extubated early or not allocated a ventilator due to capacity constraints, (4) survival rates among patients not allocated a ventilator at triage or extubated early due to capacity constraints. RESULTS: 807 patients were included in the study. The simulation model based on a modified New York State policy did not decrease mortality, excess death or exclusion from ventilators compared to the first-come-first-served policy at every ventilator capacity we tested using COVID-19 surge cohort patients. Survival rates were similar at all the survival probabilities estimated. At the lowest ventilator capacity, the modified New York State policy has an estimated survival of 28.5% (CI: 28.4-28.6), compared to 28.1% (CI: 27.7-28.5) for the first-come-first-served policy. CONCLUSIONS: This simulation of a modified New York State guideline-based triage protocol revealed limitations in achieving the utilitarian goals these protocols are designed to fulfill. Quantifying these outcomes can inform a better balance among competing moral aims.

The Impact of High-Flow Nasal Cannula Use on Patient Mortality and the Availability of Mechanical Ventilators in COVID-19.

Rationale: How to provide advanced respiratory support for coronavirus disease (COVID-19) to maximize population-level survival while optimizing mechanical ventilator access is unknown.Objectives: To evaluate the use of high-flow nasal cannula for COVID-19 on population-level mortality and ventilator availability.Methods: We constructed dynamical (deterministic) simulation models of high-flow nasal cannula and mechanical ventilation use for COVID-19 in the United States. Model parameters were estimated through consensus based on published literature, local data, and experience. We had the following two outcomes: 1) cumulative number of deaths and 2) days without any available ventilators. We assessed the impact of various policies for the use of high-flow nasal cannula (with or without "early intubation") versus a scenario in which high-flow nasal cannula was unavailable.Results: The policy associated with the fewest deaths and the least time without available ventilators combined the use of high-flow nasal cannula for patients not urgently needing ventilators with the use of early mechanical ventilation for these patients when at least 10% of ventilator supply was not in use. At the national level, this strategy resulted in 10,000-40,000 fewer deaths than if high-flow nasal cannula were not available. In addition, with moderate national ventilator capacity (30,000-45,000 ventilators), this strategy led to up to 25 (11.8%) fewer days without available ventilators. For a 250-bed hospital with 100 mechanical ventilators, the availability of 13, 20, or 33 high-flow nasal cannulas prevented 81, 102, and 130 deaths, respectively.Conclusions: The use of high-flow nasal cannula coupled with early mechanical ventilation when supply is sufficient results in fewer deaths and greater ventilator availability.