Browsing by Author "Mendonça, Eneida A."
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Item Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium(American Medical Association, 2022) Zanobetti, Antonella; Ryan, Patrick H.; Coull, Brent; Brokamp, Cole; Datta, Soma; Blossom, Jeffrey; Lothrop, Nathan; Miller, Rachel L.; Beamer, Paloma I.; Visness, Cynthia M.; Andrews, Howard; Bacharier, Leonard B.; Hartert, Tina; Johnson, Christine C.; Ownby, Dennis; Khurana Hershey, Gurjit K.; Joseph, Christine; Yiqiang, Song; Mendonça, Eneida A.; Jackson, Daniel J.; Luttmann-Gibson, Heike; Zoratti, Edward M.; Wright, Anne L.; Martinez, Fernando D.; Seroogy, Christine M.; Gern, James E.; Gold, Diane R.; Children’s Respiratory and Environmental Workgroup (CREW) Consortium; Epidemiology, School of Public HealthImportance: In the United States, Black and Hispanic children have higher rates of asthma and asthma-related morbidity compared with White children and disproportionately reside in communities with economic deprivation. Objective: To determine the extent to which neighborhood-level socioeconomic indicators explain racial and ethnic disparities in childhood wheezing and asthma. Design, setting, and participants: The study population comprised children in birth cohorts located throughout the United States that are part of the Children's Respiratory and Environmental Workgroup consortium. Cox proportional hazard models were used to estimate hazard ratios (HRs) of asthma incidence, and logistic regression was used to estimate odds ratios of early and persistent wheeze prevalence accounting for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, and region and decade of birth. Exposures: Neighborhood-level socioeconomic indicators defined by US census tracts calculated as z scores for multiple tract-level variables relative to the US average linked to participants' birth record address and decade of birth. The parent or caregiver reported the child's race and ethnicity. Main outcomes and measures: Prevalence of early and persistent childhood wheeze and asthma incidence. Results: Of 5809 children, 46% reported wheezing before age 2 years, and 26% reported persistent wheeze through age 11 years. Asthma prevalence by age 11 years varied by cohort, with an overall median prevalence of 25%. Black children (HR, 1.47; 95% CI, 1.26-1.73) and Hispanic children (HR, 1.29; 95% CI, 1.09-1.53) were at significantly increased risk for asthma incidence compared with White children, with onset occurring earlier in childhood. Children born in tracts with a greater proportion of low-income households, population density, and poverty had increased asthma incidence. Results for early and persistent wheeze were similar. In effect modification analysis, census variables did not significantly modify the association between race and ethnicity and risk for asthma incidence; Black and Hispanic children remained at higher risk for asthma compared with White children across census tracts socioeconomic levels. Conclusions and relevance: Adjusting for individual-level characteristics, we observed neighborhood socioeconomic disparities in childhood wheeze and asthma. Black and Hispanic children had more asthma in neighborhoods of all income levels. Neighborhood- and individual-level characteristics and their root causes should be considered as sources of respiratory health inequities.Item Comparing Strategies for Identifying Falls in Older Adult Emergency Department Visits Using EHR Data(Wiley, 2020) Patterson, Brian W.; Jacobsohn, Gwen Costa; Maru, Apoorva P.; Venkatesh, Arjun K.; Smith, Maureen A.; Shah, Manish N.; Mendonça, Eneida A.; Pediatrics, School of MedicineItem DEI-05. Assessing Household Material Hardship in Children with Central Nervous System (CNS) Tumors(Oxford University Press, 2024-06-18) Coven, Scott L.; Tran, Yvette H.; Park, Seho; Mendonça, Eneida A.; Pediatrics, School of MedicineBACKGROUND: Household material hardship (HMH) is defined as unmet basic needs including food, heat, housing, or transportation. Researchers have documented higher rates of poor nutrition, injury, infectious disease, and hospitalization in healthy children living in families with household material hardship. Furthermore, targeted interventions exist to modify these health outcomes. However, little is known regarding the relationship between social determinants of health and their impact on overall and quality of survival for children with brain or spinal cord tumors. The current available information is based upon retrospective and secondary data sources, often limited to basic socioeconomic factors such as race and ethnicity. The objective was to describe the change in household material hardship through patient reported outcome measures from baseline to six-months and explore the association between social determinants of health, including prospective household material hardship data, and clinical outcomes among children with brain and spinal cord tumors. METHODS: We aimed to enroll 150 patients with a brain or spinal cord tumors who were followed by the Pediatric Neuro-Oncology Program at Riley Hospital for Children at IU Health. These participants were approached during their routinely scheduled clinic visits by a member of the study team. Written or verbal consent/assent was obtained, and their data was transcribed into a REDCap™ database. RESULTS: To date, we have enrolled 118 children onto this study, with 35/76 participants completing their six-month follow-up survey. In line with Kira Bona’s previous work, we have found that around 30% acknowledged one positive domain of household material hardship. Additionally, we have found that almost 40% of our cohort fall below the 200% Federal Poverty Level, which is often considered a cutpoint for lower socioeconomic status. CONCLUSIONS: We have shown that collecting prospective patient reported sociodemographic information is feasible in a busy clinical setting.Item Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department(Biomed Central, 2019-07-22) Patterson, Brian W.; Jacobsohn, Gwen C.; Shah, Manish N.; Song, Yiqiang; Maru, Apoorva; Venkatesh, Arjun K.; Zhong, Monica; Taylor, Katherine; Hamedani, Azita G.; Mendonça, Eneida A.; Pediatrics, IU School of MedicineBACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance.