Faculty Bibliography

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:In 2016, a short message service text messaging intervention to titrate insulin in patients with uncontrolled type 2 diabetes was implemented at two health care facilities in New York City. OBJECTIVE:This study aimed to conduct a qualitative evaluation assessing barriers to and the facilitators of the implementation of the Mobile Insulin Titration Intervention (MITI) program into usual care. METHODS:We conducted in-depth interviews with 36 patients enrolled in the MITI program and the staff involved in MITI (n=19) in the two health care systems. Interviews were transcribed and iteratively coded by two study investigators, both inductively and deductively using a codebook guided by the Consolidated Framework for Implementation Research. RESULTS:Multiple facilitator themes emerged: (1) MITI had strong relative advantages to in-person titration, including its convenience and time-saving design, (2) the free cost of MITI was important to the patients, (3) MITI was easy to use and the patients were confident in their ability to use it, (4) MITI was compatible with the patients' home routines and clinic workflow, (5) the patients and staff perceived MITI to have value beyond insulin titration by reminding and motivating the patients to engage in healthy behaviors and providing a source of patient support, and (6) implementation in clinics was made easy by having a strong implementation climate, communication networks to spread information about MITI, and a strong program champion. The barriers identified included the following: (1) language limitations, (2) initial nurse concerns about the scope of practice changes required to deliver MITI, (3) initial provider knowledge gaps about the program, and (4) provider perceptions that MITI might not be appropriate for some patients (eg, older or not tech-savvy). There was also a theme that emerged during the patient and staff interviews of an unmet need for long-term additional diabetes management support among this population, specifically diet, nutrition, and exercise support. CONCLUSIONS:The patients and staff were overwhelmingly supportive of MITI and believed that it had many benefits and that it was compatible with the clinic workflow and patients' lives. Initial implementation efforts should address staff training and nurse concerns. Future research should explore options for integrating additional diabetes support for patients.

BACKGROUND:Patients with active cancer account for a growing percentage of all emergency department (ED) visits and have a unique set of risks related to their disease and its treatments. Effective triage for this population is fundamental to facilitating their emergency care. OBJECTIVES/OBJECTIVE:We evaluated the validity of the Emergency Severity Index (ESI; version 4) triage tool to predict ED-relevant outcomes among adult patients with active cancer. METHODS:tests for independence to relate ESI scores with 1) disposition, 2) ED resource use, 3) hospital length of stay, and 4) 30-day mortality. RESULTS:Among the 1008 subjects included in this analysis, the ESI distribution skewed heavily toward high acuity (>95% of subjects had an ESI level of 1, 2, or 3). ESI was significantly associated with patient disposition and ED resource use (p values < 0.05). No significant associations were observed between ESI and the non-ED based outcomes of hospital length of stay or 30-day mortality. CONCLUSION/CONCLUSIONS:ESI scores among ED patients with active cancer indicate higher acuity than the general ED population and are predictive of disposition and ED resource use. These findings show that the ESI is a valid triage tool for use in this population for outcomes directly relevant to ED care.

INTRODUCTION/BACKGROUND:Emergency departments (ED) care for society's most vulnerable older adults who present with exacerbations of chronic disease at the end of life, yet the clinical paradigm focuses on treatment of acute pathologies. Palliative care interventions in the ED capture high-risk patients at a time of crisis and can dramatically improve patient-centred outcomes. This study aims to implement and evaluate Primary Palliative Care for Emergency Medicine (PRIM-ER) on ED disposition, healthcare utilisation and survival in older adults with serious illness. METHODS AND ANALYSIS/UNASSIGNED:This is the protocol for a pragmatic, cluster-randomised stepped wedge trial to test the effectiveness of PRIM-ER in 35 EDs across the USA. The intervention includes four core components: (1) evidence-based, multidisciplinary primary palliative care education; (2) simulation-based workshops; (3) clinical decision support; and (4) audit and feedback. The study is divided into two phases: a pilot phase, to ensure feasibility in two sites, and an implementation and evaluation phase, where we implement the intervention and test the effectiveness in 33 EDs over 2 years. Using Centers for Medicare and Medicaid Services (CMS) data, we will assess the primary outcomes in approximately 300 000 patients: ED disposition to an acute care setting, healthcare utilisation in the 6 months following the ED visit and survival following the index ED visit. Analysis will also determine the site, provider and patient-level characteristics that are associated with variation in impact of PRIM-ER. ETHICS AND DISSEMINATION/UNASSIGNED:Institutional Review Board approval was obtained at New York University School of Medicine to evaluate the CMS data. Oversight will also be provided by the National Institutes of Health, an Independent Monitoring Committee and a Clinical Informatics Advisory Board. Trial results will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER/BACKGROUND:NCT03424109; Pre-results.

Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practical approach to measure and model air pollution concentration levels. In this study, we developed LUR models for street-level fine particulate matter (PM_2.5) concentration levels in Seoul, South Korea. 169 h of data were collected from an approximately three week long campaign across five routes by ten volunteers sharing seven AirBeams, a low-cost ($250 per unit), smartphone-based particle counter, while geospatial data were extracted from OpenStreetMap, an open-source and crowd-generated geographical dataset. We applied and compared three statistical approaches in constructing the LUR models - linear regression (LR), random forest (RF), and stacked ensemble (SE) combining multiple machine learning algorithms - which resulted in cross-validation R² values of 0.63, 0.73, and 0.80, respectively, and identification of several pollution 'hotspots.' The high R² values suggest that study designs employing mobile sampling in conjunction with multiple low-cost air quality monitors could be applied to characterize urban street-level air quality with high spatial resolution, and that machine learning models could further improve model performance. Given this study design's cost-effectiveness and ease of implementation, similar approaches may be especially suitable for citizen science and community-based endeavors, or in regions bereft of air quality data and preexisting air monitoring networks, such as developing countries.

Rationale: Air quality improvements are increasingly difficult to come by as modern pollution control technologies and measures have been widely implemented in the United States. Although there have been dramatic improvements in air quality over the last several decades, it is important to evaluate changes in the health impacts of air pollution for a more recent time period to better understand the current trajectory of air quality improvements. Objectives: To provide county-level estimates of annual air pollution-related health outcomes across the United States and to evaluate these trends from 2008 to 2017, presented as part of the annual American Thoracic Society (ATS)/Marron Institute "Health of the Air" report. Methods: Daily air pollution values were obtained from the U.S. Environmental Protection Agency's Air Quality System for monitors in the United States from 2008 to 2017. Concentration-response functions used in the ATS/Marron Institute "Health of the Air" report were applied to the pollution increments corresponding to differences between the rolling 3-year design values (reported as the third year) and ATS-recommended levels for annual particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM_2.5; 11 μg/m³), short-term PM_2.5 (25 μg/m³), and ozone (O₃; 60 ppb). Health impacts were estimated at the county level in locations with valid monitor data. Results: Annual excess mortality in the United States due to air pollution levels greater than recommended by the ATS decreased from approximately 12,600 (95% confidence interval [CI], 5,470-21,040) in 2010 to 7,140 (95% CI, 2,290-14,040) in 2017. This improvement can be attributed almost entirely to reductions in PM_2.5-related mortality, which decreased by approximately 60% (reduced from 8,330 to 3,260 annual deaths), whereas O₃-related mortality remained largely unchanged, other than year-to-year variability, over the same time period (reduced from 4,270 to 3,880 annual deaths). Conclusions: Improvements in health impacts attributable to ambient PM_2.5 concentrations have been observed across most regions of the United States over the last decade, although the rate of these improvements has leveled off in recent years. Despite two revisions of the National Ambient Air Quality Standards strengthening the standard for O₃ in 2008 and 2015, there has not yet been a substantial improvement in the health impacts attributable to O₃ during this time period. In many U.S. cities, an increase in the exposed population over the last decade has outpaced the improvements in ambient O₃ concentrations, resulting in a net increase in O₃-related health impacts over time.

The authors examined children's access to books in 153 four-year-olds from low-income, U.S. ethnic-minority families. Mothers reported on the number of books available to their children and the variety of books their children had, such as concept books about letters, numbers, and shapes and narrative books about cultural beliefs and relationships. Mothers also reported on the frequency of mother"child book-sharing interactions. The authors coded characteristics of book-sharing interactions from videos of mother"child sharing of a wordless book. Most children had a variety of concept books but few narrative books. Children who were later born and who had English-speaking (vs. Spanish-speaking) parents had a greater variety of narrative books than did their counterparts, and children living with their father and mother had a greater variety of narrative and concept books than those who did not reside with their father. The variety of narrative books predicted children's narrative contributions during book sharing through the mediator of mothers" questions about the story. In contrast, the variety of concept books predicted children's referential contributions (e.g., "That's a tree") through the mediator of mothers" referential questions (e.g., "What's that?"). Household composition, home language use, and the content of books shape the early literacy experiences of children from low-income, ethnic-minority families.

Background and Aims: Contemplating the use of N-acetylcysteine as a neuroprotectant, with dextran as an antithrombotic for patients with NIHSS less than or equal to 5, we quantified treatment-relevant clinical characteristics of a sample of this patient population at a single stroke center over one year.
Method(s): Patients with NIHSSResult(s): One-hundred twenty-eight of 310 (41%) patients with ischemic stroke had NIHSSConclusion(s): Minor stroke symptoms may not be captured by the current NIHSS. This population rarely had renal or hepatic failure, making them good candidates for combination N-acetylcysteine and dextran

BACKGROUND:Low-income Hispanic women are at-risk of poor prenatal diet quality. Correlates associated with prenatal diet quality in this group of women are understudied. OBJECTIVE:The objective of this study was to examine the associations between financial, cultural, psychosocial, and lifestyle correlates and prenatal diet quality in low-income Hispanic women. DESIGN/METHODS:This cross-sectional analysis used data from pregnant women enrolled in the Starting Early Trial, a randomized-controlled trial of a primary-care based child obesity prevention program beginning in pregnancy. The trial enrolled women from clinics affiliated with a large urban medical center in New York City from 2012 to 2014. Financial, cultural, psychosocial, and lifestyle variables were collected using a comprehensive baseline questionnaire. Usual dietary intakes over the past year were assessed using the Block Food Frequency Questionnaire 2005 bilingual version. PARTICIPANTS/METHODS:The study enrolled low-income Hispanic women between 28 and 32 gestational weeks (N=519). MAIN OUTCOME MEASURES/METHODS:Prenatal diet quality was measured by the Healthy Eating Index 2015. STATISTICAL ANALYSES PERFORMED/METHODS:Unadjusted and adjusted multivariable linear regression analyses were performed to determine independent associations between financial, cultural, psychosocial, and lifestyle correlates and Healthy Eating Index 2015 total score. RESULTS:Overall prenatal diet quality was poor (mean Healthy Eating Index 2015 total score=69.0±9.4). Most women did not meet the maximum score for total vegetables (65.3%), whole grains (97.1%), dairy (74.8%), fatty acids (84.4%), refined grains (79.8%), sodium (97.5%), saturated fats (92.9%), and added sugars (66.5%). Women who reported screen time ≤2 hours/day, physical activity before and/or during pregnancy, and being born outside the United States had higher mean Healthy Eating Index 2015 total score than women with screen time >2 hours/day, no physical activity, and those born in the United States. CONCLUSIONS:Prenatal diet quality of low-income pregnant Hispanic women was suboptimal. This cross-sectional study revealed associations between cultural and lifestyle factors and prenatal diet quality in low-income Hispanic women. Longitudinal studies are needed to determine long-term influences and specific behaviors to target for effective intervention studies.