Faculty Bibliography

It is without question that the Internet has democratized access to medical information, with estimates that 70% of the American population use it as a resource, particularly for cancer-related information. Such unfettered access to information has led to an increase in health misinformation. Fortunately, the data indicate that health care professionals remain among the most trusted information resources. Therefore, understanding how the Internet has changed engagement with health information and facilitated the spread of misinformation is an important task and challenge for cancer clinicians. In this review, we perform a meta-synthesis of qualitative data and point toward empirical evidence that characterizes misinformation in medicine, specifically in oncology. We present this as a call to action for all clinicians to become more active in ongoing efforts to combat misinformation in oncology.

A geospatial analysis of services that support transgender and gender diverse ("trans") people in New York City (NYC) was conducted to investigate associations with neighborhood-level sociodemographic characteristics. In June 2019, there were 5.3 services for every 100,000 of the general NYC population; controlling for other covariates, they were more commonly located in neighborhoods with larger populations of non-Hispanic Black (rate ratio [RR]=1.02, 95% confidence interval [CI]: 1.00-1.04), Hispanic/Latino (RR=1.03, 95% CI: 1.00-1.06), and gay/lesbian people (RR=1.53, 95% CI: 1.03-2.34). These findings suggest that the distribution of trans-focused services in NYC is proximal to communities that are most in need, but research should examine proximity to trans people specifically and distribution in nonurban areas.

BACKGROUND:Sepsis affects 1.7 million patients in the US annually, is one of the leading causes of mortality, and is a major driver of US healthcare costs. African American/Black and LatinX populations experience higher rates of sepsis complications, deviations from standard care, and readmissions compared with Non-Hispanic White populations. Despite clear evidence of structural racism in sepsis care and outcomes, there are no prospective interventions to mitigate structural racism in sepsis care, nor are we aware of studies that report reductions in racial inequities in sepsis care as an outcome. Therefore, we will deliver and evaluate a coalition-based intervention to equip health systems and their surrounding communities to mitigate structural racism, driving measurable reductions in inequities in sepsis outcomes. This paper presents the theoretical foundation for the study, summarizes key elements of the intervention, and describes the methodology to evaluate the intervention. METHODS:Our aims are to: (1) deliver a coalition-based leadership intervention in eight U.S. health systems and their surrounding communities; (2) evaluate the impact of the intervention on organizational culture using a longitudinal, convergent mixed methods approach, and (3) evaluate the impact of the intervention on reduction of racial inequities in three clinical outcomes: a) early identification (time to antibiotic), b) clinical management (in-hospital sepsis mortality) and c) standards-based follow up (same-hospital, all-cause sepsis readmissions) using interrupted time series analysis. DISCUSSION/CONCLUSIONS:This study is aligned with calls to action by the NIH and the Sepsis Alliance to address inequities in sepsis care and outcomes. It is the first to intervene to mitigate effects of structural racism by developing the domains of organizational culture that are required for anti-racist action, with implications for inequities in complex health outcomes beyond sepsis.

Marketing plays a key role in increasing the popularity of e-cigarettes. We conducted a systematic review of the existing literature published between 2003 and 2019 in eight databases to describe e-cigarette marketing communication messages by communication channels and marketing communication strategies. Forty-one articles were included in the analysis after screening. Ten key messages were identified. Cessation and health-related benefits (each n = 31, 75.6%) were the most reported marketing communication messages, followed by sociability/lifestyle and use experience. The Internet (n = 32, 78.0%) was the most studied communication channel compared to print, TV/movie/radio, and point-of-sales (POS)/retail stores. The most studied marketing communication strategies were advertising (n = 28, 68.3%), followed by public relations and sales promotion. Published research studies reported consistent messages about e-cigarettes across communication channels and marketing communication strategies. Claims of smoking cessation and health-related benefits were widely identified in the existing literature. While therapeutic claims are prohibited, soft sell messages, such as social appeals, for which regulatory reach may be limited, may require educational campaigns. Internet marketing has attracted much attention, with limited studies on messages in print, TV/movie/radio, and POS/retail stores. The lack of studies of direct marketing messaging indicates a big gap between industry spending and academic research; more studies of messaging utilizing this strategy are needed.

BACKGROUND:Telemedicine as a mode of health care work has grown dramatically during the COVID-19 pandemic; the impact of this transition on clinicians' after-hours electronic health record (EHR)-based clinical and administrative work is unclear. OBJECTIVE:This study assesses the impact of the transition to telemedicine during the COVID-19 pandemic on physicians' EHR-based after-hours workload (ie, "work outside work") at a large academic medical center in New York City. METHODS:We conducted an EHR-based retrospective cohort study of ambulatory care physicians providing telemedicine services before the pandemic, during the acute pandemic, and after the acute pandemic, relating EHR-based after-hours work to telemedicine intensity (ie, percentage of care provided via telemedicine) and clinical load (ie, patient load per provider). RESULTS:A total of 2129 physicians were included in this study. During the acute pandemic, the volume of care provided via telemedicine significantly increased for all physicians, whereas patient volume decreased. When normalized by clinical load (ie, average appointments per day by average clinical days per week), telemedicine intensity was positively associated with work outside work across time periods. This association was strongest after the acute pandemic. CONCLUSIONS:Taking physicians' clinical load into account, physicians who devoted a higher proportion of their clinical time to telemedicine throughout various stages of the pandemic engaged in higher levels of EHR-based after-hours work compared to those who used telemedicine less intensively. This suggests that telemedicine, as currently delivered, may be less efficient than in-person-based care and may increase the after-hours work burden of physicians.

BACKGROUND:Growth differentiation factor 15 (GDF-15) is a stress-responsive biomarker associated with several types of cardiovascular diseases. However, conflicting results have been reported regarding its association with incident atrial fibrillation (AF) in the general population. METHODS:In 10 234 White and Black Atherosclerosis Risk in Communities (ARIC) Study participants (mean age 60 years, 20.5% Blacks) free of AF at baseline (1993 to 1995), we quantified the association of GDF-15 with incident AF using Cox regression models. GDF-15 concentration was measured by an aptamer-based proteomic method. AF was defined as AF diagnosis by electrocardiogram at subsequent ARIC visits or AF diagnosis in hospitalization records or death certificates. Harrell's c-statistic and categorical net reclassification improvement were computed for risk discrimination and reclassification. RESULTS:There were 2217 cases of incident AF over a median follow-up of 20.6 years (incidence rate 12.3 cases/1000 person-years). After adjusting for potential confounders, GDF-15 was independently associated with incident AF, with a hazard ratio (HR) of 1.42 (95% CI, 1.24-1.62) for the top vs bottom quartile. The result remained consistent (HR 1.23 [95% CI, 1.07-1.41]) even after further adjusting for 2 cardiac biomarkers, cardiac troponin T and natriuretic peptide. The results were largely consistent across demographic subgroups. The addition of GDF-15 modestly improved the c-statistic by 0.003 (95% CI, 0.001-0.006) beyond known risk factors of AF. CONCLUSIONS:In this community-based biracial cohort, higher concentrations of GDF-15 were independently associated with incident AF, supporting its potential value as a clinical marker of AF risk.

The 30-day hospital readmission rate has been used in provider profiling for evaluating inter-provider care coordination, medical cost effectiveness, and patient quality of life. Current profiling analyzes use logistic regression to model 30-day readmission as a binary outcome, but one disadvantage of this approach is that this outcome is strongly affected by competing risks (e.g., death). Thus, one, perhaps unintended, consequence is that if two facilities have the same rates of readmission, the one with the higher rate of competing risks will have the lower 30-day readmission rate. We propose a discrete time competing risk model wherein the cause-specific readmission hazard is used to assess provider-level effects. This approach takes account of the timing of events and focuses on the readmission rates which are of primary interest. The quality measure, then is a standardized readmission ratio, akin to a standardized mortality ratio. This measure is not systematically affected by the rate of competing risks. To facilitate the estimation and inference of a large number of provider effects, we develop an efficient Blockwise Inversion Newton algorithm, and a stabilized robust score test that overcomes the conservative nature of the classical robust score test. An application to dialysis patients demonstrates improved profiling, model fitting, and outlier detection over existing methods.

BACKGROUND:Genome-wide association studies have identified six genetic variants associated with severe COVID-19, yet the mechanisms through which they may affect disease remains unclear. We investigated proteomic signatures related to COVID-19 risk variants rs657152 (ABO), rs10735079 (OAS1/OAS2/OAS3), rs2109069 (DPP9), rs74956615 (TYK2), rs2236757 (IFNAR2) and rs11385942 (SLC6A20/LZTFL1/CCR9/FYCO1/CXCR6/XCR1) as well as their corresponding downstream pathways that may promote severe COVID-19 in risk allele carriers and their potential relevancies to other infection outcomes. METHODS:A DNA aptamer-based array measured 4870 plasma proteins among 11 471 participants. Linear regression estimated associations between the COVID-19 risk variants and proteins with correction for multiple comparisons, and canonical pathway analysis was conducted. Cox regression assessed associations between proteins identified in the main analysis and risk of incident hospitalized respiratory infections (2570 events) over a 20.7-year follow-up. RESULTS:The ABO variant rs657152 was associated with 84 proteins in 7241 white participants with 24 replicated in 1671 Black participants. The TYK2 variant rs74956615 was associated with ICAM-1 and -5 in white participants with ICAM-5 replicated in Black participants. Of the 84 proteins identified in the main analysis, seven were significantly associated with incident hospitalized respiratory infections including Ephrin type-A receptor 4 (hazard ratio (HR): 0.87; P = 2.3 × 10-11) and von Willebrand factor type A (HR: 1.17; P = 1.6x10-13). CONCLUSIONS:Novel proteomics signatures and pathways for COVID-19-related risk variants TYK2 and ABO were identified. A subset of these proteins predicted greater risk of incident hospitalized pneumonia and respiratory infections. Further studies to examine these proteins in COVID-19 patients are warranted.

Stroke severity is the most important predictor of post-stroke outcome. Most longitudinal cohort studies do not include direct and validated measures of stroke severity, yet these indicators may provide valuable information about post-stroke outcomes, as well as risk factor associations. In the Atherosclerosis Risk in Communities (ARIC) study, stroke severity data were retrospectively collected, and this paper outlines the procedures used and shares them as a model for assessment of stroke severity in other large epidemiologic studies. Trained physician abstractors, who were blinded to other clinical events, reviewed hospital charts of all definite/probable stroke events occurring in ARIC. In this analysis we included 1,198 ischemic stroke events occurring from ARIC baseline (1987-1989) through December 31, 2009. Stroke severity was categorized according to the National Institutes of Health Stroke Scale (NIHSS) score and classified into 5 levels: NIHSS ≤ 5 (minor), NIHSS 6-10 (mild), NIHSS 11-15 (moderate), NIHSS 16-20 (severe), and NIHSS > 20 (very severe). We assessed interrater reliability in a subgroup of 180 stroke events, reviewed independently by the lead abstraction physician and one of the four secondary physician abstractors. Interrater correlation coefficients for continuous NIHSS score as well as percentage of absolute agreement and Cohen Kappa Statistic for NIHSS categories were presented. Determination of stroke severity by the NIHSS, based on data abstracted from hospital charts, was possible for 97% of all ischemic stroke events. Median (25%-75%) NIHSS score was 5 (2-8). The distribution of NIHSS category was NIHSS ≤ 5 = 58.3%, NIHSS 6-10 = 24.5%, NIHSS 11-15 = 8.9%, NIHSS 16-20 = 4.7%, NIHSS > 20 = 3.6%. Overall agreement in the classification of severity by NIHSS category was present in 145/180 events (80.56%). Cohen's simple Kappa statistic (95% CI) was 0.64 (0.55-0.74) and weighted Kappa was 0.79 (0.72-0.86). Mean (SD) NIHSS score was 5.84 (5.88), with a median score of 4 and range 0-31 for the lead reviewer (rater 1) and mean (SD) 6.16 (6.10), median 4.5 and range 0-36 in the second independent assessment (rater 2). There was a very high correlation between the scores reported in both assessments (Pearson r = 0.90). Based on our findings, we conclude that hospital chart-based retrospective assessment of stroke severity using the NIHSS is feasible and reliable.

Introduction The COVID-19 pandemic is forcing changes to clinical practice within traditional addiction treatment programmes, including the increased use of telehealth, reduced restrictions on methadone administration (eg, increased availability of take-home doses and decreased requirements for in-person visits), reduced reliance on group counselling and less urine drug screening. This paper describes the protocol for a mixed-methods study analysing organisational-level factors that are associated with changes in clinic-level practice changes and treatment retention. Methods and analysis We will employ an explanatory sequential mixed-methods design to study the treatment practices for opioid use disorder (OUD) patients in New York State (NYS). For the quantitative aim, we will use the Client Data System and Medicaid claims data to examine the variation in clinical practices (ie, changes in telehealth, pharmacotherapy, group vs individual counselling and urine drug screening) and retention in treatment for OUD patients across 580 outpatient clinics in NYS during the pandemic. Clinics will be categorised into quartiles based on composite rankings by calculating cross-clinic Z scores for the clinical practice change and treatment retention variables. We will apply the random-effects modelling to estimate change by clinic by introducing a fixed-effect variable for each clinic, adjusting for key individual and geographic characteristics and estimate the changes in the clinical practice changes and treatment retention. We will then employ qualitative methods and interview 200 key informants (ie, programme director, clinical supervisor, counsellor and medical director) to develop an understanding of the quantitative findings by examining organisational characteristics of programmes (n=25) representative of those that rank in the top quartile of clinical practice measures as well as programmes that performed worst on these measures (n=25). Ethics and dissemination The study has been approved by the Institutional Review Board of NYU Langone Health (#i21-00573). Study findings will be disseminated through national and international conferences, reports and peer-reviewed publications.