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OBJECTIVES Throughout the pandemic, children with COVID-19 have experienced hospitalization, ICU admission, invasive respiratory support, and death. Using a multisite, national dataset, we investigate risk factors associated with these outcomes in children with COVID-19. METHODS Our data source (Optum deidentified COVID-19 Electronic Health Record Dataset) included children aged 0 to 18 years testing positive for COVID-19 between January 1, 2020, and January 20, 2022. Using ordinal logistic regression, we identified factors associated with an ordinal outcome scale: nonhospitalization, hospitalization, or a severe composite outcome (ICU, intensive respiratory support, death). To contrast hospitalization for COVID-19 and incidental positivity on hospitalization, we secondarily identified patient factors associated with hospitalizations with a primary diagnosis of COVID-19. RESULTS In 165 437 children with COVID-19, 3087 (1.8%) were hospitalized without complication, 2954 (1.8%) experienced ICU admission and/or intensive respiratory support, and 31 (0.02%) died. We grouped patients by age: 0 to 4 years old (35 088), and 5 to 11 years old (75 574), 12 to 18 years old (54 775). Factors positively associated with worse outcomes were preexisting comorbidities and residency in the Southern United States. In 0- to 4-year-old children, there was a nonlinear association between age and worse outcomes, with worse outcomes in 0- to 2-year-old children. In 5- to 18-year-old patients, vaccination was protective. Findings were similar in our secondary analysis of hospitalizations with a primary diagnosis of COVID-19, though region effects were no longer observed. CONCLUSIONS Among children with COVID-19, preexisting comorbidities and residency in the Southern United States were positively associated with worse outcomes, whereas vaccination was negatively associated. Our study population was highly insured; future studies should evaluate underinsured populations to confirm generalizability.

Left atrial ablation to obtain pulmonary vein isolation (PVI) for the treatment of atrial fibrillation (AF) is a technologically intensive procedure utilizing innovative and continually improving technology. Changes in the technology utilized for PVI can in turn lead to changes in procedure costs. Because of the proximity of the esophagus to the posterior wall of the left atrium, various technologies have been utilized to protect against thermal injury during ablation. The impact on hospital costs during PVI ablation from utilization of different technologies for esophageal protection during ablation has not previously been evaluated.To compare the costs of active esophageal cooling to luminal esophageal temperature (LET) monitoring during left atrial ablation.We performed a time-driven activity-based costing (TDABC) analysis to determine costs for PVI procedures. Published data and literature review were utilized to determine differences in procedure time and same-day discharge rates using different esophageal protection technologies, and to determine the cost impacts of same-day discharge versus overnight hospitalization after PVI procedures. The total costs were then compared between cases using active esophageal cooling to those using LET monitoring.The effect of implementing active esophageal cooling was associated with up to a 24.7% reduction in mean total procedure time, and an 18% increase in same-day discharge rate. TDABC analysis identified a $681 reduction in procedure costs associated with the use of active esophageal cooling after including the cost of the esophageal cooling device. Factoring in the 18% increase in same-day discharge resulted in an increased cost savings of $2,135 per procedure.The use of active esophageal cooling is associated with significant cost-savings when compared to traditional LET monitoring, even after accounting for the additional cost of the cooling device. These savings originate from a per-patient procedural time savings and a per-population improvement in same-day discharge rate.

Radiofrequency (RF) ablation of the left atrium of the heart is increasingly used to treat atrial fibrillation (AF). Unfortunately, inadvertent thermal injury to the esophagus can occur during this procedure, potentially creating an atrioesophageal fistula (AEF) which is 80% fatal. The ensoETM (Attune Medical, Chicago, IL), is an esophageal cooling device that has been shown to reduce thermal injury to the esophagus during RF ablation.This review summarizes growing evidence related to active esophageal cooling during RF ablation for the treatment of AF. The review presents data demonstrating improved outcomes related to patient safety and procedural efficiency and suggests directions for future research.The use of active esophageal cooling during RF ablation reduces esophageal injury, reduces or eliminates fluoroscopy requirements, reduces procedure duration and post-operative pain, and increases long-term freedom from arrhythmia. These effects in turn increase patient same-day discharge rates, decrease operator cognitive load, and reduce cost. These findings are likely to further accelerate the adoption of active esophageal cooling.Atrial fibrillation is a condition in which the heart beats irregularly, causing symptoms such as palpitations, dizziness, shortness of breath, and chest pain. Atrial fibrillation increases the risk of stroke, heart failure, dementia, and death. One treatment for atrial fibrillation is a procedure called a catheter ablation. This procedure is minimally invasive and is performed by a specialized cardiologist, called an electrophysiologist. The electrophysiologist, or operator, uses an energy source, such as radiofrequency energy (radio waves), to stop erratic electrical signals from traveling through the heart. One complication of the catheter ablation is an inadvertent injury to the esophagus, the organ that passes food from the mouth to the stomach. If the injury is severe, it may develop into an atrioesophageal fistula, which often results in death. In this review, a new technology is described that helps prevent this type of injury and can provide additional benefits for the patient, operator, and hospital.

Objectives We characterized real-time patient portal test result viewing among emergency department (ED) patients and described patient characteristics overall and among those not enrolled in the portal at ED arrival. Methods Our observational study at an academic ED used portal log data to trend the proportion of adult patients who viewed results during their visit from May 04, 2021 to April 04, 2022. Correlation was assessed visually and with Kendall's τ. Covariate analysis using binary logistic regression assessed result(s) viewed as a function of time accounting for age, sex, ethnicity, race, language, insurance status, disposition, and social vulnerability index (SVI). A second model only included patients not enrolled in the portal at arrival. We used random forest imputation to account for missingness and Huber-White heteroskedasticity-robust standard errors for patients with multiple encounters (α = 0.05). Results There were 60,314 ED encounters (31,164 unique patients). In 7,377 (12.2%) encounters, patients viewed results while still in the ED. Patients were not enrolled for portal use at arrival in 21,158 (35.2%) encounters, and 927 (4.4% of not enrolled, 1.5% overall) subsequently enrolled and viewed results in the ED. Visual inspection suggests an increasing proportion of patients who viewed results from roughly 5 to 15% over the study (Kendall's τ = 0.61 [p Conclusion We observed increased portal-based test result viewing among ED patients over the year since the 21st Century Cures act went into effect, even among those not enrolled at arrival. We observed disparities in those who viewed results.

ObjectiveTo determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions.MethodsWe supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy.ResultsFive clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy.ConclusionAI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.

Background As the risk for concomitant COVID-19 infection in people living with HIV (PLHIV) remains largely unknown, we explored a large national database to identify risk factors for COVID-19 infection among PLHIV. Methods Using the COVID-19 OPTUM de-identified national multicenter database, we identified 29,393 PLHIV with either a positive HIV test or documented HIV ICD9/10 codes. Using a multiple logistic regression model, we compared risk factors among PLHIV, who tested positive for COVID-19 (5,134) and those who tested negative (24,259) from January 20, 2020, to January 20, 2022. We then compared secondary outcomes including hospitalization, Intensive Care Unit (ICU) stay, and death within 30 days of test among the 2 cohorts, adjusting for COVID-19 positivity and covariates. We adjusted all models for the following covariates: age, gender, race, ethnicity, U.S. region, insurance type, adjusted Charlson Comorbidity Index (CCI), Body Mass Index (BMI), and smoking status. Results Among PLHIV, factors associated with higher odds for acquiring COVID-19 (Figure 1) included lower age (compared to age group 18–49, age groups 50–64 and >65 were associated with odds ratios (OR) of 0.8 and 0.75, P= 0.001), female gender (compared to males, OR 1.06, P= 0.07), Hispanic White ethnicity/race (OR 2.75, P= 0.001), Asian (OR 1.35, P= 0.04), and African American (OR 1.23, P= 0.001) [compared to non-Hispanic White], living in the U.S. South (compared to the Northeast, OR 2.18, P= 0.001), being uninsured (compared to commercial insurance, OR 1.46, P= 0.001), higher CCI (OR 1.025, P= 0.001), higher BMI category (compared to having BMI< 30, Obesity category 1 or 2, OR 1.2 and obesity category 3, OR 1.34, P= 0.001), and noncurrent smoking status (compared to current smoker, OR 1.46, P= 0.001). Compared to PLHIV who tested negative for COVID-19, PLHIV who tested positive, had an OR 1.01 for hospitalization (P = 0.79), 1.03 for ICU stay (P=0.73), and 1.47 for death (P=0.001). Conclusion Our study found that among PLHIV, being Hispanic, living in the South, lacking insurance, having higher BMI, and higher CCI scores were associated with increased odds of testing positive for COVID-19. PLHIV who tested positive for COVID-19 had higher odds of death. Disclosures Christoph U. Lehmann, MD, Celanese: Stocks/Bonds|Markel: Stocks/Bonds|Springer: Honoraria|UTSW: Employee Jeremy Y. Chow, M.D., M.S., Gilead Sciences: Grant/Research Support.

Background The percentage of children infected with COVID-19 has outpaced that of adults. As children >5 years are now eligible to receive vaccines, it is necessary to understand the effect of vaccination in the context of demographic characteristics, clinical factors, and variants on pediatric COVID-19 illness severity. Methods We conducted a descriptive study of patients ≤18 years from the Optum® COVID-19 electronic health record dataset. Patients were included if positive for COVID-19 by polymerase chain reaction or antigen testing for the first time from 3/12/2020 to 1/20/2022. We compare race and ethnicity, age, gender, US region of residence, vaccination status, body mass index (BMI), pediatric comorbidity index (PCI) (Sun, Am. J. Epidemiol. 2021), and predominant variant (by time and region) with 2-tailed t-test, multi-category chi-square test, and odds ratios (R version 4.1.2; α = 0.05). PCI is a validated comorbidity index predicting hospitalization in pediatric patients. Results Of all pediatric patients in our dataset, 165,468 (13.2%) tested positive for COVID-19. 3,087 (1.9%) were hospitalized, 1,417 (0.9%) were admitted to the ICU, 1545 (0.9%) received respiratory support, and 31 (0.02%) died, comparable to AAP-reported hospitalization and mortality rates in US children. Patients with severe outcomes were more likely to be younger, non-Caucasian, from the US South, unvaccinated, and have a higher PCI (Figure 1). Excluding non-severe outcomes, rates of death and ICU admission were higher in 0–4-year-olds compared to 5–11 or 12–18-year-olds (Figure 2). All patients receiving at least one dose of the vaccine survived. The odds ratio of a severe outcome is 0.11 (95% CI 0.07–0.16) in fully vaccinated patients compared to unvaccinated patients. The odds ratio of a severe outcome is 0.55 (95% CI 0.49–0.63) in partially vaccinated patients compared to unvaccinated patients. Demographic and clinical characteristics of pediatric patients with COVID-19 Relative proportion of clinically severe outcomes within age groups, excluding non-severe outcomes Conclusion In this large population, incidence rate of severe outcomes from COVID-19 in pediatric patients was higher among non-Caucasian patients, living in the South, with underlying comorbid illness, and those not yet eligible for vaccination. These findings reinforce the need for a vaccine for younger patients and targeted vaccine outreach to racial and ethnic minorities and children with chronic conditions. Disclosures Christoph U. Lehmann, MD, Celanese: Stocks/Bonds|Markel: Stocks/Bonds|Springer: Honoraria|UTSW: Employee.

Background Therapeutic vaccination following SARS-CoV-2 infection might stimulate anti-viral immunity and improve patient outcomes. We investigated, amongst previously unvaccinated patients, whether vaccination with the Pfizer, Moderna, or Johnson & Johnson vaccines within 14 days of a positive SARS-CoV-2 test affected 30-day patient outcomes. Methods Using a deidentified national electronic health record dataset (Optum, Inc.), we identified previously unvaccinated patients who tested positive for COVID-19 between 12/11/2020 and 12/19/2021. Among this cohort, 1,909 patients received a first vaccine dose within 14 days (vaccinated) while 446,309 did not receive a first dose of vaccine within 30 days of their first positive test (unvaccinated). We performed 1:1 propensity score matching based on age, gender, race, ethnicity, region, BMI, insurance, and comorbidities from the Charlson Comorbidity Index. Next, we compared odds of severe outcomes within 30 days between vaccinated and unvaccinated groups using a partial proportional odds model with the following ordinal severity outcome: no hospitalization, hospitalization, ICU stay, or death (Stata version 17.0, α = 0.05). Results 1,909 vaccinated patients were propensity score-matched to 1,909 unvaccinated patients. The final matched cohort was statistically indistinguishable (p > 0.05) for all metrics used in propensity score calculation. This matched cohort (n = 3,818) was 58.6% female, 67.7% white, 12.6% Hispanic, and 56.4% commercially insured, with a mean age of 50.6 years and a similar comorbidity profile. A partial proportional odds model showed that unvaccinated patients were at increased risk for hospitalization and higher ordered outcomes (OR = 1.19, 95% CI: 1.02-1.39), ICU stay and higher ordered outcomes (OR 1.63, 95% CI: 1.21-2.20), and death (OR 4.57, 95% CI: 2.50-8.37). Conclusion Among previously unvaccinated patients, those who received a first dose vaccine within 14 days of a positive COVID-19 test were less likely to experience hospitalization, ICU stay, or death compared to matched peers who did not receive a first dose in the acute phase of infection. The sample size of patients vaccinated during the acute phase is limited, so further studies are indicated to evaluate the safety and efficacy of this practice. Disclosures Christoph U. Lehmann, MD, FAAP, FACMI, FIAHSI, Celanese: Stocks/Bonds|Markel: Stocks/Bonds|Springer: Honoraria.

The 21st century has seen an enormous growth in emergency medical services (EMS) information technology systems, with corresponding accumulation of large volumes of data. Despite this growth, integration efforts between EMS-based systems and electronic health records, and public-sector databases have been limited due to inconsistent data structure, data missingness, and policy and regulatory obstacles. Efforts to integrate EMS systems have benefited from the evolving science of entity resolution and record linkage. In this chapter, we present the history and fundamentals of record linkage techniques, an overview of past uses of this technology in EMS, and a look into the future of record linkage techniques for integrating EMS data systems including the use of machine learning-based techniques.

Study objective Throughout the coronavirus disease 2019 pandemic, many emergency departments have been using passive protective enclosures ("intubation boxes") during intubation. The effectiveness of these enclosures remains uncertain. We sought to quantify their ability to contain aerosols using industry standard test protocols. Methods We tested a commercially available passive protective enclosure representing the most common design and compared this with a modified enclosure that incorporated a vacuum system for active air filtration during simulated intubations and negative-pressure isolation. We evaluated the enclosures by using the same 3 tests air filtration experts use to certify class I biosafety cabinets: visual smoke pattern analysis using neutrally buoyant smoke, aerosol leak testing using a test aerosol that mimics the size of virus-containing particulates, and air velocity measurements. Results Qualitative evaluation revealed smoke escaping from all passive enclosure openings. Aerosol leak testing demonstrated elevated particle concentrations outside the enclosure during simulated intubations. In contrast, vacuum-filter-equipped enclosures fully contained the visible smoke and test aerosol to standards consistent with class I biosafety cabinet certification. Conclusion Passive enclosures for intubation failed to contain aerosols, but the addition of a vacuum and active air filtration reduced aerosol spread during simulated intubation and patient isolation.

OBJECTIVE: In the present study, we quantified the effect of the coronavirus disease 2019 (COVID-19) on the volume of adult and pediatric neurosurgical procedures, inpatient consultations, and clinic visits at an academic medical center. METHODS: Neurosurgical procedures, inpatient consultations, and outpatient appointments at Vanderbilt University Medical Center were identified from March 23, 2020 through May 8, 2020 (during COVID-19) and March 25, 2019 through May 10, 2019 (before COVID-19). The neurosurgical volume was compared between the 2 periods. RESULTS: A 40% reduction in weekly procedural volume was demonstrated during COVID-19 (median before, 75; interquartile range [IQR], 72-80; median during, 45; IQR, 43-47; P < 0.001). A 42% reduction occurred in weekly adult procedures (median before, 62; IQR, 54-70; median during, 36; IQR, 34-39; P < 0.001), and a 31% reduction occurred in weekly pediatric procedures (median before, 13; IQR, 12-14; median during, 9; IQR, 8-10; P = 0.004). Among adult procedures, the most significant decreases were seen for spine (P < 0.001) and endovascular (P < 0.001) procedures and cranioplasty (P < 0.001). A significant change was not found in the adult open vascular (P = 0.291), functional (P = 0.263), cranial tumor (P = 0.143), or hydrocephalus (P = 0.173) procedural volume. Weekly inpatient consultations to neurosurgery decreased by 24% (median before, 99; IQR, 94-114; median during, 75; IQR, 68-84; P = 0.008) for adults. Weekly in-person adult and pediatric outpatient clinic visits witnessed a 91% decrease (median before, 329; IQR, 326-374; median during, 29; IQR, 26-39; P < 0.001). In contrast, weekly telehealth encounters increased from a median of 0 (IQR, 0-0) before to a median of 151 (IQR, 126-156) during COVID-19 (P < 0.001). CONCLUSIONS: Significant reductions occurred in neurosurgical operations, clinic visits, and inpatient consultations during COVID-19. Telehealth was increasingly used for assessments. The long-term effects of the reduced neurosurgical volume and increased telehealth usage on patient outcomes should be explored.

Coronavirus disease 2019 (COVID-19) vaccination is the core strategy for pandemic management. We hypothesized that a vaccination gap might exist between emergency department (ED) patients admitted for trauma and other ED patients.This was an observational quality improvement study using electronic health record data at an academic level-1 trauma center. Participants were all patients presenting to the adult ED with a Tennessee home address between January 1 and June 1, 2021. We measured the proportional difference in vaccination between admitted trauma patients and other ED patients over time (by week) and association via Spearman's rank correlation coefficient. Binary logistic regression facilitated covariate analysis to account for age, sex, race, home county, and ethnicity without and then with interaction between trauma admission and time. Geographic visual analysis compared county-level vaccination rates with odds of trauma admission by home county using a bivariate chloropleth map.The proportional difference in vaccination between trauma-admitted and other ED patients increased over time (Spearman's = 0.699). Adjusting for age, sex, race, home county, and ethnicity, there was a statistically significant vaccination difference between trauma-admitted and other ED patients (odds ratio = 0.53, 95% CI 0.43-0.65, p0.0001). Geographic analysis revealed increased trauma admission odds and lower vaccination rates in surrounding counties compared with Davidson County.We observed a widening COVID-19 vaccination gap between trauma-admitted and other ED patients. Vaccine outreach during trauma admission may provide a valuable point of contact for unvaccinated patients.

ImportanceThe 21st Century Cures Act Final Rule mandates the immediate electronic availability of test results to patients, likely empowering them to better manage their health. Concerns remain about unintended effects of releasing abnormal test results to patients.ObjectiveTo assess patient and caregiver attitudes and preferences related to receiving immediately released test results through an online patient portal.Design, Setting, and ParticipantsThis large, multisite survey study was conducted at 4 geographically distributed academic medical centers in the US using an instrument adapted from validated surveys. The survey was delivered in May 2022 to adult patients and care partners who had accessed test results via an online patient portal account between April 5, 2021, and April 4, 2022.ExposuresAccess to test results via a patient portal between April 5, 2021, and April 4, 2022.Main Outcomes and MeasuresResponses to questions related to demographics, test type and result, reaction to result, notification experience and future preferences, and effect on health and well-being were aggregated. To evaluate characteristics associated with patient worry, logistic regression and pooled random-effects models were used to assess level of worry as a function of whether test results were perceived by patients as normal or not normal and whether patients were precounseled.ResultsOf 43 380 surveys delivered, there were 8139 respondents (18.8%). Most respondents were female (5129 [63.0%]) and spoke English as their primary language (7690 [94.5%]). The median age was 64 years (IQR, 50-72 years). Most respondents (7520 of 7859 [95.7%]), including 2337 of 2453 individuals (95.3%) who received nonnormal results, preferred to immediately receive test results through the portal. Few respondents (411 of 5473 [7.5%]) reported that reviewing results before they were contacted by a health care practitioner increased worry, though increased worry was more common among respondents who received abnormal results (403 of 2442 [16.5%]) than those whose results were normal (294 of 5918 [5.0%]). The result of the pooled model for worry as a function of test result normality was statistically significant (odds ratio [OR], 2.71; 99% CI, 1.96-3.74), suggesting an association between worry and nonnormal results. The result of the pooled model evaluating the association between worry and precounseling was not significant (OR, 0.70; 99% CI, 0.31-1.59).Conclusions and RelevanceIn this multisite survey study of patient attitudes and preferences toward receiving immediately released test results via a patient portal, most respondents preferred to receive test results via the patient portal despite viewing results prior to discussion with a health care professional. This preference persisted among patients with nonnormal results.

Understanding the differences and potential synergies between traditional clinician assessment and automated machine learning might enable more accurate and useful suicide risk detection.To evaluate the respective and combined abilities of a real-time machine learning model and the Columbia Suicide Severity Rating Scale (C-SSRS) to predict suicide attempt (SA) and suicidal ideation (SI).This cohort study included encounters with adult patients (aged ≥18 years) at a major academic medical center. The C-SSRS was administered during routine care, and a Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) prediction was generated in the electronic health record. Encounters took place in the inpatient, ambulatory surgical, and emergency department settings. Data were collected from June 2019 to September 2020.Primary outcomes were the incidence of SA and SI, encoded as International Classification of Diseases codes, occurring within various time periods after an index visit. We evaluated the retrospective validity of the C-SSRS, VSAIL, and ensemble models combining both. Discrimination metrics included area under the receiver operating curve (AUROC), area under the precision-recall curve (AUPR), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).The cohort included 120 398 unique index visits for 83 394 patients (mean [SD] age, 51.2 [20.6] years; 38 107 [46%] men; 45 273 [54%] women; 13 644 [16%] Black; 63 869 [77%] White). Within 30 days of an index visit, the combined models had higher AUROC (SA: 0.874-0.887; SI: 0.869-0.879) than both the VSAIL (SA: 0.729; SI: 0.773) and C-SSRS (SA: 0.823; SI: 0.777) models. In the highest risk-decile, ensemble methods had PPV of 1.3% to 1.4% for SA and 8.3% to 8.7% for SI and sensitivity of 77.6% to 79.5% for SA and 67.4% to 70.1% for SI, outperforming VSAIL (PPV for SA: 0.4%; PPV for SI: 3.9%; sensitivity for SA: 28.8%; sensitivity for SI: 35.1%) and C-SSRS (PPV for SA: 0.5%; PPV for SI: 3.5%; sensitivity for SA: 76.6%; sensitivity for SI: 68.8%).In this study, suicide risk prediction was optimal when leveraging both in-person screening (for acute measures of risk in patient-reported suicidality) and historical EHR data (for underlying clinical factors that can quantify a patient's passive risk level). To improve suicide risk classification, prediction systems could combine pretrained machine learning with structured clinician assessment without needing to retrain the original model.

Clinical informatics (CI) is a rich field with longstanding ties to resident education in many clinical specialties, although a historic gap persists in emergency medicine. To address this gap, we developed a CI track to facilitate advanced training for senior residents at our 4-year emergency medicine residency. We piloted an affordable project-based approach with strong ties to operational leadership at our institution and describe specific projects and their outcomes. Given the relatively low cost, departmental benefit, and unique educational value, we believe that our model is generalizable to many emergency medicine residencies. We present a pathway to defining a formal curriculum using Kern's framework.

The COVID-19 national emergency has led to surging care demand and the need for unprecedented telehealth expansion. Rapid telehealth expansion can be especially complex for pediatric patients. From the experience of a large academic medical center, this report describes a pathway for efficiently increasing capacity of remote pediatric enrollment for telehealth while fulfilling privacy, security, and convenience concerns. The design and implementation of the process took 2 days. Five process requirements were identified: efficient enrollment, remote ability to establish parentage, minimal additional work for application processing, compliance with guidelines for adolescent autonomy, and compliance with institutional privacy and security policies. Weekly enrollment subsequently increased 10-fold for children (age 0–12 years) and 1.2-fold for adolescents (age 13–17 years). Weekly telehealth visits increased 200-fold for children and 90-fold for adolescents. The obstacles and solutions presented in this report can provide guidance to health systems for similar challenges during the COVID-19 response and future disasters.