<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Brain Injury | ISSUES | The Ohio State University</title><link>https://issues-osu.github.io/ISSUESlab/tag/brain-injury/</link><atom:link href="https://issues-osu.github.io/ISSUESlab/tag/brain-injury/index.xml" rel="self" type="application/rss+xml"/><description>Brain Injury</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 22 Oct 2025 00:00:00 +0000</lastBuildDate><image><url>https://issues-osu.github.io/ISSUESlab/media/logo_hu2fedd529b9d9d7008e9f6968cd645fa1_199187_300x300_fit_lanczos_3.png</url><title>Brain Injury</title><link>https://issues-osu.github.io/ISSUESlab/tag/brain-injury/</link></image><item><title>GIS Day 2025</title><link>https://issues-osu.github.io/ISSUESlab/presentations/gisday/</link><pubDate>Wed, 22 Oct 2025 00:00:00 +0000</pubDate><guid>https://issues-osu.github.io/ISSUESlab/presentations/gisday/</guid><description>&lt;p>Congratulations to our undergraduates &lt;a href="https://issues-osu.github.io/ISSUESlab/author/olivia-mclucas/" target="_blank" rel="noopener">&lt;strong>Oliva McLucas&lt;/strong>&lt;/a> and &lt;a href="http://localhost:1313/issues/author/malcolm-mccarthy/" target="_blank" rel="noopener">&lt;strong>Malcolm McCarthy&lt;/strong>&lt;/a> for their abstracts accepted to the 2025 GIS Day at &lt;strong>The Ohio State University&lt;/strong> on &lt;strong>November 19, 2025&lt;/strong>.&lt;/p>
&lt;p>&lt;strong>Olivia McLucas&lt;/strong>: &lt;em>Introducing a Spatial Adverse Childhood Environments Index using Geographical Information Systems&lt;/em> We extend the cumulative Adverse Childhood Experiences (ACEs) framework to the neighborhood scale with spACEs (Spatial Adverse Childhood Environments), an index of structural disadvantage in childhood. The spACES index is constructed from county-level measures in the 1990 Census, including poverty, educational attainment, employment structure, housing burden, single-parent prevalence, and racial residential segregation, which reflect the environments in which the Opportunity Atlas birth cohorts (children born 1978 to 1985) were raised. The Opportunity Atlas links childhood places of residence to adult outcomes, capturing household income rank, educational attainment, incarceration, and family formation (2010-2015), as well as credit outcomes (2020). Using GIS, we visualize geographic variation in spACEs and assess its association with long-term adult outcomes. We propose spACEs as a revised measure of childhood structural adversity that captures the enduring impact of neighborhood disadvantage across the life course.&lt;/p>
&lt;p>&lt;strong>McCarthy, M.&lt;/strong>: &lt;em>Mapping Traumatic Brain Injury using Geographic Information Systems&lt;/em> Traumatic brain injury (TBI) is a critical public health problem linked to numerous mechanisms, including unintentional injuries such as falls and motor vehicle crashes and intentional injuries such as assaults. Despite the magnitude of this burden, no research has systematically examined the geographic distribution of TBI hospitalizations and their county-level correlates. We utilize county-level hospitalization data from the Washington State Department of Health, filtered to include all TBI-related admissions by year. These records are linked to the Area Deprivation Index (ADI) for the period 2016–2023, encompassing domains of economic hardship and inequality, educational attainment, and financial strength. The merged dataset enables the analysis of spatial and temporal patterns of TBI hospitalization risk and tests whether county-level social and economic disadvantage is associated with higher rates of TBI hospitalization. Using GIS visualization and regression models, we demonstrate how community structural conditions shape the distribution of TBI and inform strategies for prevention.&lt;/p>
&lt;p>The presentations will be made available after the conference.&lt;/p></description></item><item><title>Enhancing Brain Injury Surveillance Using Large Language Models and Topic Modeling</title><link>https://issues-osu.github.io/ISSUESlab/presentations/aiforbi/</link><pubDate>Sun, 19 Oct 2025 00:00:00 +0000</pubDate><guid>https://issues-osu.github.io/ISSUESlab/presentations/aiforbi/</guid><description>&lt;p>Our presentation, &lt;em>Enhancing Brain Injury Surveillance Using Large Language Models and Topic Modeling&lt;/em>, was delivered by &lt;a href="https://issues-osu.github.io/ISSUESlab/author/karla-mccarthy-shockley/" target="_blank" rel="noopener">Dr. Shockley McCarthy&lt;/a> at the &lt;strong>AI for BI Conference&lt;/strong> at &lt;strong>The Ohio State University&lt;/strong> on &lt;strong>October 17, 2025&lt;/strong>.&lt;/p>
&lt;blockquote>
&lt;p>This work introduces an AI-driven framework for improving the detection and contextual understanding of brain injury cases using unstructured medical and administrative text. By applying large language models (LLMs) and structured topic modeling, we extract interpretable patterns from injury narratives and ICD-coded data to identify mechanisms of injury, intent, and underreported cases of intimate partner violence (IPV)–related brain injury.&lt;/p>
&lt;p>Integrating methods from public health, law, and computational linguistics, our approach aims to enhance the precision of injury surveillance systems and inform equitable prevention and policy strategies addressing violence-related traumatic brain injury (TBI).&lt;/p>
&lt;/blockquote>
&lt;p>
&lt;i class="fas fa-download pr-1 fa-fw">&lt;/i> Download the
&lt;a href="https://issues-osu.github.io/ISSUESlab/ISSUESlab/uploads/AIforBI_BrainInjuryPresentation.pdf" target="_blank">presentation here&lt;/a>
.&lt;/p></description></item><item><title>Intimate Partner Violence &amp; Brain Injury in U.S. Adults: Findings from the Medical Expenditure Panel Survey, 2021</title><link>https://issues-osu.github.io/ISSUESlab/policy-briefs/ipv-bi-costs/</link><pubDate>Wed, 27 Aug 2025 00:00:00 +0000</pubDate><guid>https://issues-osu.github.io/ISSUESlab/policy-briefs/ipv-bi-costs/</guid><description>&lt;h2 id="overview">Overview&lt;/h2>
&lt;p>National survey data show that adults who screen positive for intimate partner violence (IPV) experience more injuries and face greater medical costs than those who do not.
Nine million screened IPV-positive using the HITS screening tool, and survivors were significantly more likely to utilize emergency rooms and hospitals for treating their injuries.
Head and brain injuries were much more frequent among IPV survivors, and the average cost of treating these injuries was nearly twice as high compared to adults who did not screen positive for IPV.&lt;/p>
&lt;h2 id="key-messages">Key Messages&lt;/h2>
&lt;ul>
&lt;li>Approximately 9 million adults screened positive for IPV in 2021.&lt;/li>
&lt;li>IPV-positive adults had 3–4× higher ER and inpatient injury rates than IPV-negative adults.&lt;/li>
&lt;li>Adults who screened positive for IPV experienced more than twice the rate of brain-injury healthcare events compared to those who screened negative.&lt;/li>
&lt;li>Average per-capita spending on brain-injury care was about twice as high among IPV-positive adults.&lt;/li>
&lt;li>Inpatient TBI events are less common than ER events but far more costly; counts and spending are higher among IPV-positive adults.&lt;/li>
&lt;li>Poverty, social stressors, depression, and chronic conditions are significantly associated with IPV screen positivity.&lt;/li>
&lt;/ul>
&lt;h2 id="policy-relevance--recommendations">Policy Relevance &amp;amp; Recommendations&lt;/h2>
&lt;ul>
&lt;li>
&lt;p>&lt;em>Standardized protocols&lt;/em>: Implement routine protocols so that IPV-positive patients with head injury are screened for brain injury, and patients with head injury are also screened for IPV.&lt;/p>
&lt;/li>
&lt;li>
&lt;p>&lt;em>Integrated referral pathways&lt;/em>: Establish clear referral systems across emergency, primary, and specialty care so that when screening protocols are triggered, patients are automatically connected to appropriate follow-up services.&lt;/p>
&lt;/li>
&lt;li>
&lt;p>&lt;em>Follow-up for delayed symptoms&lt;/em>: Incorporate temporal follow-up in care plans, recognizing that brain injury symptoms may appear or worsen over time.&lt;/p>
&lt;/li>
&lt;li>
&lt;p>&lt;em>Accessibility and appropriateness&lt;/em>: Ensure screening and follow-up services are accessible, widely available, and tailored to the needs of IPV survivors.&lt;/p>
&lt;/li>
&lt;li>
&lt;p>&lt;em>Holistic screening&lt;/em>: Extend screening beyond identifying head injury to include social and health needs that may magnify injury effects and increase vulnerability to future IPV.&lt;/p>
&lt;/li>
&lt;li>
&lt;p>&lt;em>Care coordination&lt;/em>: Utilize medical social workers and interdisciplinary teams to integrate medical, psychosocial, and safety needs into a comprehensive care response.&lt;/p>
&lt;/li>
&lt;/ul>
&lt;h2 id="methodology">Methodology&lt;/h2>
&lt;p>This brief analyzes nationally representative data from the &lt;em>Medical Expenditure Panel Survey—Household Component (MEPS-HC) 2021&lt;/em>. Adults (age ≥18) were classified as IPV screen-positive if they scored &lt;strong>≥10&lt;/strong> on the Hurt, Insult, Threaten, Scream (HITS) scale, a validated four-item screening tool for intimate partner violence.&lt;/p>
&lt;p>Injury outcomes were identified using ICD-10-CM codes and Clinical Classifications Software Refined (CCSR) groupings from the MEPS Conditions file, with condition–event linkages used to assign emergency department (ER), inpatient, outpatient, office-based, home health, and prescription care to specific injuries. Brain injuries were defined as &lt;strong>traumatic brain injury (ICD-10 S06)&lt;/strong> and other head injuries (&lt;strong>S00–S09&lt;/strong>).&lt;/p>
&lt;p>We estimated:&lt;/p>
&lt;ul>
&lt;li>Injury and brain-injury events per 100 adults,&lt;/li>
&lt;li>Per-capita spending (in 2021 USD), and&lt;/li>
&lt;li>Weighted counts of injury-linked encounters.&lt;/li>
&lt;/ul>
&lt;p>Analyses applied MEPS survey weights (PERWT21F) and accounted for the complex design (VARSTR, VARPSU). We used survey-weighted generalized linear models (svyglm) to generate adjusted comparisons standardized over age, sex, and race/ethnicity. Risk ratios were estimated for sociodemographic factors, health-related social needs, and chronic health conditions associated with IPV screen positivity.&lt;/p>
&lt;h2 id="suggested-citation">Suggested Citation&lt;/h2>
&lt;p>Barboza-Salerno, G. E., Shockley McCarthy, K., Watson-Grace, A., Harrington, T., McCarthy, M. A., Peremen, N., &amp;amp; McLucas, O. (2025). &lt;em>Intimate Partner Violence &amp;amp; Brain Injury in U.S. Adults: Findings from the Medical Expenditure Panel Survey, 2021.&lt;/em> Policy brief. The Ohio State University, ISSUE Lab (Investigating Spatial Structures in Urban Environments).&lt;/p>
&lt;h2 id="download">Download&lt;/h2>
&lt;ul>
&lt;li>&lt;a href="Policy-brief-003-BI-IPV-costs.pdf">Download the full brief for more information&lt;/a>&lt;/li>
&lt;/ul></description></item></channel></rss>