Faculty Bibliography

The COVID-19 pandemic accelerated the adoption of remote patient monitoring technology, which offers exciting opportunities for expanded connected care at a distance. However, while the mode of clinicians' interactions with patients and their health data has transformed, the larger framework of how we deliver care is still driven by a model of episodic care that does not facilitate this new frontier. Fully realizing a transformation to a system of continuous connected care augmented by remote monitoring technology will require a shift in clinicians' and health systems' approach to care delivery technology and its associated data volume and complexity. In this article, we present a solution that organizes and optimizes the interaction of automated technologies with human oversight, allowing for the maximal use of data-rich tools while preserving the pieces of medical care considered uniquely human. We review implications of this "augmented continuous connected care" model of remote patient monitoring for clinical practice and offer human-centered design-informed next steps to encourage innovation around these important issues.

BACKGROUND:Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous chemicals with mechanisms of toxicity that include endocrine disruption. We examined associations of prenatal urinary PAH with spontaneous preterm birth (PTB) and gestational age (GA) at birth. We also assessed whether infant sex modifies the association of PAH exposure with spontaneous PTB and GA at birth. METHODS:-transformed OH-PAH concentrations as the exposure, adjusted for specific gravity and suspected confounders. Effect modification by infant sex was assessed using interaction terms and marginal estimates. RESULTS:Percent detection was highest for 2-OH-NAP (99.8%) and lowest for 1-OH-PYR (65.2%). Prevalence of spontaneous PTB was 5.5% (N = 92). Ten-fold higher 2-OH-NAP exposure was associated with 1.60-day (95% CI: -2.92, -0.28) earlier GA at birth. Remaining associations in the pooled population were null. Among females, we observed significant inverse associations between 1-OH-PYR and PTB (OR: 2.65 [95% CI: 1.39, 5.05]); and 2-OH-NAP with GA: -2.46 days [95% CI: -4.15, -0.77]). Among males, we observed an inverse association between 2/3/9-OH-FLUO and PTB (OR = 0.40 [95% CI: 0.17,0.98]). ORs for PTB were higher among females than males for 2-OH-PHEN (p = 0.02) and 1-OH-PYR (p = 0.02). DISCUSSION/CONCLUSIONS:We observed inverse associations of 2-OH-NAP exposure with GA and null associations of remaining OH-PAHs with GA and PTB. Females may be more susceptible to spontaneous PTB or shorter GA following prenatal exposure to some OH-PAHs. This study is the first to assess sex-specific OH-PAH toxicity in relation to spontaneous PTB and GA.

Given the growth of the older adult population in the United States, there is a greater need for tools to enable students, trainees, and clinicians to master the comprehensive geriatric assessment. Our goal was to develop a mobile phone application (app) to assist in performing this assessment. We performed a market survey of 45 apps that related to geriatrics and health screening. We evaluated for usability, target audience, and instruments used. Deficiencies included: (1) focusing on a single domain; (2) being time-intensive; and (3) having components behind a paywall. We then designed an app that incorporates instruments that are well-validated, available at no cost, and brief in length. GeriKit includes eight domains: cognition, depression, function, strength, medications, falls, and advance care planning. Each instrument requires fewer than 5 minutes, and once it is completed and scored, the user can access relevant educational materials. GeriKit was launched for Apple users in December 2020, and for Android in August 2021. There have been over 3,400 downloads to date. The GeriKit app makes the comprehensive geriatric assessment accessible to a wide audience, improving the ability to for learners to perform geriatric assessments.

INTRODUCTION/BACKGROUND:State cancer prevention and control programs rely on public health surveillance data to set objectives to improve cancer prevention and control, plan interventions, and evaluate state-level progress towards achieving those objectives. The goal of this project was to evaluate the validity of using electronic health records (EHRs) based on common data model variables to generate indicators for surveillance of cancer prevention and control for these public health programs. METHODS:Following the methodological guidance from the PRISMA Extension for Scoping Reviews, we conducted a literature scoping review to assess how EHRs are used to inform cancer surveillance. We then developed 26 indicators along the continuum of the cascade of care, including cancer risk factors, immunizations to prevent cancer, cancer screenings, quality of initial care after abnormal screening results, and cancer burden. Indicators were calculated within a sample of patients from the New York City (NYC) INSIGHT Clinical Research Network using common data model EHR data and were weighted to the NYC population using post-stratification. We used prevalence ratios to compare these estimates to estimates from the raw EHR of NYU Langone Health to assess quality of information within INSIGHT, and we compared estimates to results from existing surveillance sources to assess validity. RESULTS:Of the 401 identified articles, 15% had a study purpose related to surveillance. Our indicator comparisons found that INSIGHT EHR-based measures for risk factor indicators were similar to estimates from external sources. In contrast, cancer screening and vaccination indicators were substantially underestimated as compared to estimates from external sources. Cancer screenings and vaccinations were often recorded in sections of the EHR that were not captured by the common data model. INSIGHT estimates for many quality-of-care indicators were higher than those calculated using a raw EHR. CONCLUSION/CONCLUSIONS:Common data model EHR data can provide rich information for certain indicators related to the cascade of care but may have substantial biases for others that limit their use in informing surveillance efforts for cancer prevention and control programs.

A reliable, individualized, and dynamic surrogate of cardiovascular risk, synoptic for key biologic mechanisms, could shorten the path for drug development, enhance drug cost-effectiveness and improve patient outcomes. We used highly multiplexed proteomics to address these objectives, measuring about 5000 proteins in each of 32,130 archived plasma samples from 22,849 participants in nine clinical studies. We used machine learning to derive a 27-protein model predicting 4-year likelihood of myocardial infarction, stroke, heart failure, or death. The 27 proteins encompassed 10 biologic systems, and 12 were associated with relevant causal genetic traits. We independently validated results in 11,609 participants. Compared to a clinical model, the ratio of observed events in quintile 5 to quintile 1 was 6.7 for proteins versus 2.9 for the clinical model, AUCs (95% CI) were 0.73 (0.72 to 0.74) versus 0.64 (0.62 to 0.65), c-statistics were 0.71 (0.69 to 0.72) versus 0.62 (0.60 to 0.63), and the net reclassification index was +0.43. Adding the clinical model to the proteins only improved discrimination metrics by 0.01 to 0.02. Event rates in four predefined protein risk categories were 5.6, 11.2, 20.0, and 43.4% within 4 years; median time to event was 1.71 years. Protein predictions were directionally concordant with changed outcomes. Adverse risks were predicted for aging, approaching an event, anthracycline chemotherapy, diabetes, smoking, rheumatoid arthritis, cancer history, cardiovascular disease, high systolic blood pressure, and lipids. Reduced risks were predicted for weight loss and exenatide. The 27-protein model has potential as a "universal" surrogate end point for cardiovascular risk.

Unhealthy levels of air pollution are breathed by billions of people worldwide, and air pollution is the leading environmental cause of death and disability globally. Efforts to reduce air pollution at its many sources have had limited success, and in many areas of the world, poor air quality continues to worsen. Personal interventions to reduce exposure to air pollution include avoiding sources, staying indoors, filtering indoor air, using face masks, and limiting physical activity when and where air pollution levels are elevated. The effectiveness of these interventions varies widely with circumstances and conditions of use. Compared with upstream reduction or control of emissions, personal interventions place burdens and risk of adverse unintended consequences on individuals. We review evidence regarding the balance of benefits and potential harms of personal interventions for reducing exposure to outdoor air pollution, which merit careful consideration before making public health recommendations with regard to who should use personal interventions and where, when, and how they should be used. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

BACKGROUND:The characteristics of community members exposed to World Trade Center (WTC) dust and fumes with Chronic Obstructive Pulmonary Disease (COPD) can provide insight into mechanisms of airflow obstruction in response to an environmental insult, with potential implications for interventions. METHODS:We performed a baseline assessment of respiratory symptoms, spirometry, small airway lung function measures using respiratory impulse oscillometry (IOS), and blood biomarkers. COPD was defined by the 2019 GOLD criteria for COPD. Patients in the WTC Environmental Health Center with <5 or ≥5 pack year smoking history were classified as nonsmoker-COPD (ns-COPD) or smoker-COPD (sm-COPD), respectively. MAIN RESULTS/RESULTS:= 0.007). CONCLUSIONS:Spirometry findings and small airway measures, as well as inflammatory markers, differed between patients with ns-COPD and sm-COPD. These findings suggest potential for differing mechanisms of airway injury in patients with WTC environmental exposures and have potential therapeutic implications.

OBJECTIVE:We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS/METHODS:As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: (1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); (2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and (3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of (1) fast-food restaurants and (2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS:Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways. CONCLUSIONS:Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.

BACKGROUND:Electronic patient portals are increasingly used in health care systems as communication and information-sharing tools and show promise in addressing health care access, quality, and outcomes. However, limited research exists on portal use patterns and practices among diverse patient populations, resulting in the lack of culturally and contextually tailored portal systems for these patients. OBJECTIVE:This study aimed to summarize existing evidence on the access and use patterns, barriers, and facilitators of patient portals among Chinese Americans, who represent a growing patient population in the United States with unique health care and health technology needs. METHODS:The authors conducted a literature search using the PRISMA Protocol for Scoping Reviews (Preferred Reporting Items for Systematic Reviews and Meta-Analyses-ScR) for extracting articles published in major databases (MEDLINE, Embase, and PsycINFO) on patient portals and Chinese Americans. Authors independently reviewed the papers during initial screening and full-text review. The studies were analyzed and coded for the study method type, sample population, and main outcomes of interest. RESULTS:In total, 17 articles were selected for inclusion in the review. The included articles were heterogenous and varied in their study aims, methodologies, sample populations, and outcomes. Major findings identified from the articles include variable patterns of portal access and use among Chinese Americans compared to other racial or ethnic groups, with limited evidence on the specific barriers and facilitators for this group; a preference for cross-sectional quantitative tools such as patient surveys and electronic health record-based data over qualitative or other methodologies; and a pattern of aggregating Chinese American-related data into a larger Asian or Asian American designation. CONCLUSIONS:There is limited research evaluating the use patterns, experiences, and needs of Chinese Americans who access and use patient portal systems. Existing research is heterogeneous, largely cross-sectional, and does not disaggregate Chinese Americans from larger Asian demographics. Future research should be devoted to the specific portal use patterns, preferences, and needs of Chinese Americans to help ensure contextually appropriate and acceptable design and implementation of these digital health tools.