Faculty Bibliography

BACKGROUND:Telemedicine use rapidly increased during the COVID-19 pandemic. This study assessed quality aspects of rapid expansion of a virtual urgent care (VUC) telehealth system and the effects of a secondary telephonic screening initiative during the pandemic. METHODS:A retrospective cohort analysis was performed in a single health care network of VUC patients from March 1, 2020, through April 20, 2020. Researchers abstracted demographic data, comorbidities, VUC return visits, emergency department (ED) referrals and ED visits, dispositions, intubations, and deaths. The team also reviewed incomplete visits. For comparison, the study evaluated outcomes of non-admission dispositions from the ED: return visits with and without admission and deaths. We separately analyzed the effects of enhanced callback system targeting higher-risk patients with COVID-like illness during the last two weeks of the study period. RESULTS:A total of 18,278 unique adult patients completed 22,413 VUC visits. Separately, 718 patient-scheduled visits were incomplete; the majority were no-shows. The study found that 50.9% of all patients and 74.1% of patients aged 60 years or older had comorbidities. Of VUC visits, 6.8% had a subsequent VUC encounter within 72 hours; 1.8% had a subsequent ED visit. Of patients with enhanced follow-up, 4.3% were referred for ED evaluation. Mortality was 0.20% overall; 0.21% initially and 0.16% with enhanced follow-up (p = 0.59). Males and black patients were significantly overrepresented in decedents. CONCLUSION/CONCLUSIONS:Appropriately deployed VUC services can provide a pragmatic strategy to care for large numbers of patients. Ongoing surveillance of operational, technical, and clinical factors is critical for patient quality and safety with this modality.

BACKGROUND:The coronavirus disease (COVID)-19 pandemic quickly challenged New York City health care systems. Telemedicine has been suggested to manage acute complaints and divert patients from in-person care. OBJECTIVES/OBJECTIVE:The objective of this study was to describe and assess the impact of a rapidly scaled virtual urgent care platform during the COVID-19 pandemic. METHODS:This was a retrospective cohort study of all patients who presented to a virtual urgent care platform over 1 month during the COVID-19 pandemic surge. We described scaling our telemedicine urgent care capacity, described patient clinical characteristics, assessed for emergency department (ED) referrals, and analyzed postvisit surveys. RESULTS:During the study period, a total of 17,730 patients were seen via virtual urgent care; 454 (2.56%) were referred to an ED. The most frequent diagnoses were COVID-19 related or upper respiratory symptoms. Geospatial analysis indicated a wide catchment area. There were 251 providers onboarded to the platform; at peak, 62 providers supplied 364 h of coverage in 1 day. The average patient satisfaction score was 4.4/5. There were 2668 patients (15.05%) who responded to the postvisit survey; 1236 (49.35%) would have sought care in an ED (11.86%) or in-person urgent care (37.49%). CONCLUSIONS:A virtual urgent care platform was scaled to manage a volume of more than 800 patients a day across a large catchment area during the pandemic surge. About half of the patients would otherwise have presented to an ED or urgent care in person. Virtual urgent care is an option for appropriate patients while minimizing in-person visits during the COVID-19 pandemic.

INTRODUCTION/BACKGROUND:It is difficult to determine illness severity for coronavirus disease 2019 (COVID-19) patients, especially among stable-appearing emergency department (ED) patients. We evaluated patient outcomes among ED patients with a documented ambulatory oxygen saturation measurement. METHODS:This was a retrospective chart review of ED patients seen at New York University Langone Health during the peak of the COVID-19 pandemic in New York City. We identified ED patients who had a documented ambulatory oxygen saturation. We studied the outcomes of high oxygen requirement (defined as >4 liters per minute) and mechanical ventilation among admitted patients and bounceback admissions among discharged patients. We also performed logistic regression and compared the performance of different ambulatory oxygen saturation cutoffs in predicting these outcomes. RESULTS:Between March 15-April 14, 2020, 6194 patients presented with fever, cough, or shortness of breath at our EDs. Of these patients, 648 (11%) had a documented ambulatory oxygen saturation, of which 165 (24%) were admitted. Notably, admitted and discharged patients had similar initial vital signs. However, the average ambulatory oxygen saturation among admitted patients was significantly lower at 89% compared to 96% among discharged patients (p<0.01). Among admitted patients with an ambulatory oxygen saturation, 30% had high oxygen requirements and 8% required mechanical ventilation. These rates were predicted by low ambulatory oxygen saturation (p<0.01). Among discharged patients, 50 (10%) had a subsequent ED visit resulting in admission. Although bounceback admissions were predicted by ambulatory oxygen saturation at the first ED visit (p<0.01), our analysis of cutoffs suggested that this association may not be clinically useful. CONCLUSION/CONCLUSIONS:Measuring ambulatory oxygen saturation can help ED clinicians identify patients who may require high levels of oxygen or mechanical ventilation during admission. However, it is less useful for identifying which patients may deteriorate clinically in the days after ED discharge and require subsequent hospitalization.

OBJECTIVE:s rates of childhood obesity and pediatric type 2 diabetes (T2D) increase, a better understanding is needed of how these two conditions relate, and which subgroups of children are more likely to develop diabetes with and without obesity. METHODS:To compare hotspots of childhood obesity and pediatric T2D in New York City, we performed geospatial clustering analyses on obesity estimates obtained from surveys of school-aged children and diabetes estimates obtained from healthcare claims data, from 2009-2013. Analyses were performed at the Census tract level. We then used multivariable regression analysis to identify sociodemographic and environmental factors associated with these hotspots. RESULTS:We identified obesity hotspots in Census tracts with a higher proportion of Black or Hispanic residents, with low median household income, or located in a food swamp. 51.1% of pediatric T2D hotspots overlapped with obesity hotspots. For pediatric T2D, hotspots were identified in Census tracts with a higher proportion of Black residents and a lower proportion of Hispanic residents. CONCLUSIONS:Non-Hispanic Black neighborhoods had a higher probability of being hotspots of both childhood obesity and pediatric type 2 diabetes. However, we identified a discordance between hotspots of childhood obesity and pediatric diabetes in Hispanic neighborhoods, suggesting either under-detection or under-diagnosis of diabetes, or that obesity may influence diabetes risk differently in these two populations. These findings warrant further investigation of the relationship between childhood obesity and pediatric diabetes among different racial and ethnic groups, and may help guide pediatric public health interventions to specific neighborhoods.

BACKGROUND:In December 2019 the coronavirus disease of 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2, was identified in Wuhan, China. In the ensuing months, the COVID-19 pandemic has spread globally and case load is exponentially increasing across the United States. Emergency departments have adopted screening and triage procedures to identify potential cases and isolate them during evaluation. CASE PRESENTATION/METHODS:We describe a case of COVID-19 pneumonia requiring hospitalization that presented with fever and extensive rash as the primary presenting symptoms. Rash has only been rarely reported in COVID-19 patients, and has not been previously described.

Objective/UNASSIGNED:Given the high mortality and prolonged duration of mechanical ventilation of COVID-19 patients, we evaluated the safety and efficacy of hyperbaric oxygen for COVID-19 patients with respiratory distress. Methods/UNASSIGNED:This is a single-center clinical trial of COVID-19 patients at NYU Winthrop Hospital from March 31 to April 28, 2020. Patients in this trial received hyperbaric oxygen therapy at 2.0 atmospheres of pressure in monoplace hyperbaric chambers for 90 minutes daily for a maximum of five total treatments. Controls were identified using propensity score matching among COVID-19 patients admitted during the same time period. Using competing-risks survival regression, we analyzed our primary outcome of inpatient mortality and secondary outcome of mechanical ventilation. Results/UNASSIGNED:We treated 20 COVID-19 patients with hyperbaric oxygen. Ages ranged from 30 to 79 years with an oxygen requirement ranging from 2 to 15 liters on hospital days 0 to 14. Of these 20 patients, two (10%) were intubated and died, and none remain hospitalized. Among 60 propensity-matched controls based on age, sex, body mass index, coronary artery disease, troponin, D-dimer, hospital day, and oxygen requirement, 18 (30%) were intubated, 13 (22%) have died, and three (5%) remain hospitalized (with one still requiring mechanical ventilation). Assuming no further deaths among controls, we estimate that the adjusted subdistribution hazard ratios were 0.37 for inpatient mortality (p=0.14) and 0.26 for mechanical ventilation (p=0.046). Conclusion/UNASSIGNED:Though limited by its study design, our results demonstrate the safety of hyperbaric oxygen among COVID-19 patients and strongly suggests the need for a well-designed, multicenter randomized control trial.

OBJECTIVES/OBJECTIVE:Some of the most pressing health problems are found in rural America. However, the surveillance needed to track and prevent disease in these regions is lacking. Our objective was to perform a comprehensive health survey of a single rural county to assess the validity of using emergency claims data to estimate rural disease prevalence at a sub-county level. DESIGN/METHODS:We performed a cross-sectional study of chronic disease prevalence estimates using emergency department (ED) claims data versus mailed health surveys designed to capture a substantial proportion of residents in New York's rural Sullivan County. SETTING/METHODS:Sullivan County, a rural county ranked second-to-last for health outcomes in New York State. PARTICIPANTS/METHODS:Adult residents of Sullivan County aged 25 years and older who responded to the health survey in 2017-2018 or had at least one ED visit in 2011-2015. OUTCOME MEASURES/METHODS:We compared age and gender-adjusted prevalence of hypertension, hyperlipidaemia, diabetes, cancer, asthma and chronic obstructive pulmonary disease/emphysema among nine sub-county areas. RESULTS:Our county-wide mailed survey obtained 6675 completed responses for a response rate of 30.4%. This sample represented more than 12% of the estimated 53 020 adults in Sullivan County. Using emergency claims data, we identified 34 576 adults from Sullivan County who visited an ED at least once during 2011-2015. At a sub-county level, prevalence estimates from mailed surveys and emergency claims data correlated especially well for diabetes (r=0.90) and asthma (r=0.85). Other conditions were not well correlated (range: 0.23-0.46). Using emergency claims data, we created more geographically detailed maps of disease prevalence using geocoded addresses. CONCLUSIONS:For select conditions, emergency claims data may be useful for tracking disease prevalence in rural areas and providing more geographically detailed estimates. For rural regions lacking robust health surveillance, emergency claims data can inform how to geographically target efforts to prevent chronic disease.

INTRODUCTION/BACKGROUND:Although screening for diabetes is recommended at age 45, some populations may be at greater risk at earlier ages. Our objective was to quantify age disparities among patients with type 2 diabetes in New York City. METHODS:Using all-payer hospital claims data for New York City, we performed a cross-sectional analysis of patients with type 2 diabetes identified from emergency department visits during the 5-year period 2011-2015. We estimated type 2 diabetes prevalence at each year of life, the age distribution of patients stratified by decade, and the average age of patients by sex, race/ethnicity, and geographic location. RESULTS:We identified 576,306 unique patients with type 2 diabetes. These patients represented more than half of all people with type 2 diabetes in New York City. Patients in racial/ethnic minority groups were on average 5.5 to 8.4 years younger than non-Hispanic white patients. At age 45, type 2 diabetes prevalence was 10.9% among non-Hispanic black patients and 5.2% among non-Hispanic white patients. In our geospatial analyses, patients with type 2 diabetes were on average 6 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was also 1 to 2 years younger in hotspots of microvascular diabetic complications. CONCLUSION/CONCLUSIONS:We identified profound age disparities among patients with type 2 diabetes in racial/ethnic minority groups and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetic complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control.

Background: Current guidelines for diabetes screening start at age 45, but disparities in certain subgroups exist and poor diabetic outcomes are known to cluster in specific neighborhoods. The objective of this study was to quantify disparities in the age distribution of patients with type 2 diabetes by sex, race/ethnicity, and geographic location. We also studied how patient age relates to diabetes-related hospital use and development of diabetic complications.
Method(s): Using all-payer hospital claims data, we performed a cross-sectional analysis of patients with type 2 diabetes. Our study included patients in New York City as identified by geocoded home address. Patients aged 10 to 100 years old were identified as having type 2 diabetes based on diagnosis codes from emergency claims data from 2011-2015. Our main measures included the estimated prevalence of type 2 diabetes at each year of life, the age distribution of patients as stratified by decade, and the comparison of patient age in geographic hotspots of frequent diabetes-related hospital use and diabetic complications.
Result(s): We identified 576,306 unique patients diagnosed with type 2 diabetes, which represented over half of all cases in New York City. Minority subgroups were on average 5.5 to 8.4 years younger than non-Hispanic White patients. Males with type 2 diabetes were 2.6 years younger than females. At 45 years of age, the estimated prevalence of type 2 diabetes was 10.9% among Black patients compared to 5.2% among White patients. In our geospatial analyses, patients with type 2 diabetes were on average 5.9 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was 1.5 to 2.2 years younger in hotspots of microvascular diabetic complications.
Conclusion(s): We identified profound disparities in the age of patients with type 2 diabetes among minorities and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetes-related complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control to reduce disparities in diabetes burden. [Figure Presented] Age Distribution of Patients with Type 2 Diabetes by Race and Ethnicity

Background: Emergency department (ED) care decisions often hinge on the result of a diagnostic test. Frequently there is a lag time between a test result becoming available for review, and physician decision-making based on that result. Push notifications to physician smartphones have demonstrated improvement in this lag time in chest pain patients, but have not been studied in other ED patients. We implemented a system by which ED providers can subscribe to electronic alerts when test results are available for review via a smartphone or smartwatch push notification, and hypothesized that this would reduce the time to make clinical decisions. Method(s): This was a retrospective, multicenter, observational study in three emergency departments of an urban health system. We assessed push notification impact on time to disposition or time to follow-up order in six clinical scenarios of interest: chest x-ray (CXR) to disposition, basic metabolic panel (BMP) to disposition, urinalysis (UA) to disposition, respiratory pathogen panel (RPP) to disposition, hemoglobin (Hb) to blood transfusion order, and D-dimer to computed tomography pulmonary angiography (CTPA) order. All adult ED patients during a one-year period of push notification availability were included in the study. The primary outcome was median time from result availability to disposition order or defined follow-up order. Median times with interquartile ranges were determined in each scenario and the Mann Whitney (Wilcoxon) test for unpaired data was used to determine statistical significance. Result(s): During the study period there were 6,115 push notifications from 4,183 eligible ED encounters (2.7% of all ED encounters). All six scenarios studied were associated with a decrease in median time from test result availability to patient disposition, or from test result availability to follow-up order, when push notifications were employed: CXR to disposition (24 minutes, p<0.01), BMP to disposition (12 minutes, p<0.01), UA to disposition (50 minutes, p<0.01), RPP to disposition (43 minutes, p<0.01), D-dimer to CTPA (8 minutes, p<0.01), Hb to blood transfusion (19 minutes, p=0.73). Conclusion(s): Implementation of a push notification system for test result availability in the ED was associated with a decrease in lag time between test result availability and physician decision-making