Health Information Technology Commons^™

Healthcare Supply Chain Optimization Techniques: Case Studies Of Pittsburgh-Area Healthcare Centers, Alan D. Smith

Atlantic Marketing Association Proceedings

No abstract provided.

Developing A Computational Pipeline For Biomarker Discovery In Ischemic Reperfusion Injury, Surabhi Panda, Kaitlyn Insana, Dimitri Pestov

Rowan-Virtua Research Day

Background: Ischemia-reperfusion injury (IRI) contributes significantly to tissue damage in cardiovascular disease. During IRI, stressed and dying cells release ribosomal RNA, which exhibits distinct fragmentation patterns that may serve as potential diagnostic biomarkers. Although these patterns have been observed using low-resolution biochemical techniques, there is currently no standardized computational approach to quantify and visualize RNA fragmentation for clinical interpretation.

Hypothesis: A computational pipeline can be developed to visualize and analyze ribosomal RNA fragmentation patterns, enabling identification of distinct fragmentation hotspots associated with ischemic conditions and potential biomarker discovery.

Methods: RNA fragmentation datasets generated from ribosomal RNA experiments in a Saccharomyces …

Bio-Cybersecurity: Securing The Healthcare Industry, Amanda D. Coleman

Cybersecurity Undergraduate Research Showcase

Bio-cybersecurity refers to the aspect of cybersecurity that applies to the biological sciences and the protection of digital biomedical information. Today’s healthcare industry has evolved with the enhancement of internet and biomedical technology. While hospitals and private medical providers remain compliant with the Health Information Portability and Accountability Act (HIPAA) through traditional means of securing documented patient information, the emergence of beneficial internet-based healthcare services like virtual appointments and digital patient records requires new policies and healthcare cybersecurity frameworks to protect sensitive information from unauthorized access. This paper examines the role of cybersecurity in healthcare, the vulnerabilities that exist and …

Redesigning A Fitness App Interface For Physiological Constrained Users*, Joseph E. Manzanillo

Campus Research Month

As fitness tracking converges with medical monitoring, inclusive design becomes a matter of health equity. This research utilizes a Polar Beat redesign to address exclusionary "sporty" aesthetics that can exclude 300 million colorblind users. Based in Human-Computer Interaction (HCI), the study implements WCAG AA standards and color-blind-verified filters to mitigate data loss during Situational Induced Impairment (SIID), when high-intensity exercise compromises cognitive and visual processing. By optimizing user journeys for Paralympic and geriatric archetypes, this work demonstrates that accessibility is the essential bridge transitioning mobile fitness apps into viable, inclusive instruments for clinical medical use.

Exploring The Relationship Between Behavioral Health Early Prediction Model And Patient Outcomes In The Emergency Department, Karen M. Richendollar, Kathie M. Zimbro

Knowledge and Creativity Expo

Problem: Emergency departments (EDs) are increasingly utilized for mental health (MH) care, often resulting in overcrowding and delayed access to specialized services. A significant proportion of MH patients are discharged without a psychiatric consult, raising concerns about safety and readmission rates. This trend places additional strain on already limited behavioral health resources and contributes to care delays for patients in acute crisis. Moreover, the lack of standardized discharge criteria for MH patients increases variability in care and may compromise patient outcomes. Purpose: This study evaluates the effectiveness of the Behavioral Health Early Discharge Prediction Model (BHEDPM) in identifying MH patients …

Visual Aids And Numeracy In Healthcare: Leveraging The Drawing Effect, Zephyr J. Markley

Capstone Showcase

Healthcare decisions often require patients to interpret numerical risk information under stress, yet many struggle with low numeracy, which can distort comprehension and undermine informed consent. Well-designed visual aids can improve diagnostic inference, calibrate confidence, and support better choices, especially for patients with limited numeracy, but their impact depends on whether users can actually interpret the format accurately. Drawing may further enhance these tools by adding a tactile, generative layer that engages visual, semantic, and motoric processing while helping patients organize information into concrete models.

Passive visual aids appear useful but limited because they often position patients as observers rather …

Validating Pharmacogenomics Generative Artificial Intelligence Query Prompts Using Retrieval-Augmented Generation (Rag), Ashley Rector, Beth Breeden, Jay Dorris

Student Scholar Symposium

This study evaluated the performance of Sherpa Rx, an artificial intelligence platform leveraging large language models and retrieval-augmented generation (RAG) for pharmacogenomics, by validating its performance across key response metrics. Sherpa Rx integrated Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines with Pharmacogenomics Knowledgebase (PharmGKB) data to generate contextually relevant responses. A dataset (N=260 queries) spanning 26 CPIC guidelines was used to evaluate drug-gene interactions, dosing recommendations, and therapeutic implications. In Phase 1, only CPIC data was embedded; Phase 2 additionally incorporated PharmGKB. Responses were scored on accuracy, relevance, clarity, completeness (5-point Likert scale), and recall. Wilcoxon signed-rank tests compared accuracy between …

Developing Nlp-Based Open-Source Tools To Improve Medication Order Interpretation In Ehr Systems, Preslie Breton

Student Scholar Symposium

Interpreting free-text medication orders in Electronic Health Record (EHR) systems is challenging due to variability, increasing the risk of errors and non-compliance with Joint Commission (TJC) standards. This research develops Natural Language Processing (NLP) tools to enhance medication order accuracy, particularly for Duplicate PRN orders. Our open-source, vendor-neutral approach ensures broad applicability across healthcare institutions while maintaining data security.

Using Python and the Natural Language Toolkit (NLTK), we implemented a four-phase methodology. First, the NLP framework was developed on Google Colab for collaborative accessibility. Next, models were trained on 10,000 anonymized synthetic free-text medication orders to detect non-compliant entries. Model …

Enhancing Diabetes Management With Visual Tools: A Multimodal Approach For High-Risk Urban Populations, Mikyla R. Futz, Jesse Edwards, Md, Fhm

Health Equity and Quality Improvement (HEQI) Summit

Background & Objective

Patients from historically marginalized communities face disproportionate barriers to diabetes mellitus (DM) management due to limited health literacy, language discordance, and a lack of culturally responsive educational resources. These structural challenges contribute to poorer glycemic control, higher complication rates, and reduced adherence to recommended care. While visual communication tools have demonstrated efficacy in improving comprehension, self-efficacy, and disease outcomes in chronic illness, their integration into diabetes care remains limited and inconsistently implemented.

Visual interventions may be particularly impactful in populations with low health literacy or limited digital access, yet few have been embedded into routine outpatient workflows. …

Enhancing Primary Care Navigation For D/Deaf And Hard-Of-Hearing Patients: A Wayfinding Intervention Proposal, Mikyla R. Futz, Mary L. Micou, Robert S. Pugliese, Pharmd, Bcps, Jesse Edwards, Md, Fhm

Health Equity and Quality Improvement (HEQI) Summit

Background

Auditory-dependent healthcare environments present persistent barriers to patients who are d/Deaf or hard of hearing (d/DHH), particularly where verbal instructions and auditory notifications dominate communication workflows. This contributes to delayed access to care, decreased satisfaction and strained patient provider-relationships, and significantly higher hospitalization rates —16-21% for individuals with mild to moderate hearing loss, respectively. Additionally, these patients experience higher rates of chronic conditions, lower health literacy, and reduced healthcare satisfaction. Existing interventions are often fragmented and narrowly focused, failing to capture the heterogeneity of d/DHH patients’ needs. This project introduces a scalable, continuous solution grounded in inclusive design principles …

Assessing The Efficacy Of Using The Ptsd Coach Mobile Application For Managing Ptsd Symptoms: Results Using The Hopkins Symptom Checklist-21, Muntaha Rana, Kaylea Shoulders, Deep Patel, Anne Jones

Rowan-Virtua Research Day

Background: Primary care settings often become the first place where patients with mental health concerns go, especially with shortages of mental health providers. During Covid-19 mental health concerns increased, increasing the demand of primary care providers to help assist patients navigate their concerns. Hypothesis: Participants that use the PTSD Coach App for 30 days will have reduced HSCL-21 follow-up scores compared to their intake. Methods: Patients were recruited from the Rowan-Virtua family medicine office in Sewell. The PCL-5 with the HSCL-21 was administered, with patients then using the PTSD Coach app for 30 days. Researchers followed up with patients after …

Artificial Intelligence In Detecting Heart Failure - A Systematic Review, Dale Shober, Kyle Kowalski, Aria Sen

Rowan-Virtua Research Day

Many studies have presented an artificial intelligence (AI) model to read electrocardiograms (ECGs) for the purpose of detecting or classifying the severity of heart failure. While most literature suggests that these AI-ECG models are effective at detecting or classifying heart failure, their efficacy in comparison to the current standards of care is not well researched. Furthermore, the barriers to implementation and the risks of these systems have not been studied and compiled. This literature review aims to outline the efficacy of AI-ECG models, determine how effective AI-ECG is in comparison to the standards of care, and outline the barriers to …

Enhancing Diagnostic Accuracy In Dyspnea: The Role Of Ai-Enhanced Ecg Interpretation, Sami Asif, Ayesha Mushtaq

Rowan-Virtua Research Day

Dyspnea is a frequent and diagnostically challenging presentation in emergency departments, requiring rapid distinction between cardiac and non-cardiac causes. Traditional approaches, including NT-proBNP testing and clinical assessment, often lack optimal sensitivity and specificity. Recent advancements in artificial intelligence (AI) have introduced AI-enhanced electrocardiogram (ECG) analysis as a promising diagnostic tool capable of identifying cardiac dysfunction with high accuracy.

A structured literature review was performed using PubMed to identify randomized controlled trials, prospective validations, and systematic reviews published between 2018 and 2024. Studies evaluating AI-ECG performance, NT-proBNP testing, and clinical assessment in adult patients presenting with dyspnea were included. Data extracted …

Home-Based Stroke Rehabilitation: Virtual Reality For The Elderly?, Joseph C. Moschella, Liam H. Kerrick

Rowan-Virtua Research Day

Stroke remains the leading cause of long-term disability, especially within the elderly population. Nearly 50 percent of stroke survivors never achieve full independence post-stroke. This literature review examines the capability of virtual reality (VR), as home-based continuation of stroke rehabilitation for elderly patients. VR has the potential to improve motor recovery, increase independence, and reduce healthcare costs for stroke survivors. A comprehensive literature review has been conducted following the PRISMA guidelines to evaluate VR therapy compared to conventional post-stroke therapy. VR rehabilitation demonstrated improvements in motor ability, however it did not demonstrate significantly superior improvements when compared to conventional therapy. …

Leveraging Ai In Teledermatology: A Literature Review On Advancing Health Equity For Underserved Populations, Jared Hensley, Smaran Marupudi, Blake Martin, Neharika Penmetcha, Maria Villegas

Research Symposium

Background: Health disparities in dermatological care tend to disproportionately affect underserved populations, particularly those in rural and resource-limited settings. Teledermatology, augmented by artificial intelligence (AI), presents an opportunity to address these inequities by providing underserved populations with improved diagnostic capabilities. Despite its promise, AI models in teledermatology can often exhibit biases, such as reduced diagnostic efficacy for Fitzpatrick skin types IV-VI, due to their training on non-representative datasets. This literature review explores AI's role in teledermatology and potential strategies to enhance its utility for underserved populations.

Methods: A comprehensive review of peer-reviewed literature was conducted to evaluate the integration of …

Could Telemedicine Approaches Improve Inclusivity In Spinal Cord Injury Care And Research?: Insights From Epidemiological Texas Data, Anesu Karen Murambadoro, Daniel Salinas, Victoria Elizondo, Kevin Garcia Valdez, Blake Martin, Paul Bonilla, Kelsey Baker

Research Symposium

Background: Spinal cord injury (SCI) affects hundreds of Texans, with annual healthcare costs exceeding $43,800 per individual, with the bulk of these costs coming from frequent rehabilitation visits. In a geographically vast state with only two major SCI rehabilitation centers, Texans with SCI may face substantial barriers to accessing specialized care, particularly in rural and underserved areas. Telemedicine, which encompasses remote delivery of healthcare services and rehabilitation, has offered promising solutions in easing travel burden and improving physician reach. For example, nationally, in 2021, 37.0% of individuals utilized telemedicine. Furthermore, telemedicine usage was greatest among individuals living in West and …

Investigating The Relationship Between The Circadian Clock, Age, And Lifestyle, Samuel Park, Amaka Eziakonwa, Amega Nguyen, Madison Payne, Erich Stahmer, Alexis Salinas, Payson Broome, Angel Oliver, Christian Mccormick, Jasmyn Brown, Julie A. Zacharias-Simpson, Jutta Ward, Deborah Bell-Pedersen

Annual Research Symposium

This poster presentation aims to understand how circadian clock strength and phase are affected by age and lifestyle. By analyzing changes in physiological rhythms, the study seeks to develop strategies for promoting healthy aging by optimizing circadian function.

Tracking The Effects Of Time Zone Shift On An Individual’S Circadian Rhythm, Amaka Eziakonwa, Erich Stahmer, Amega Nguyen, Samuel Park, Madison Payne, Alexis Salinas, Deborah Bell-Pedersen, Julie A. Zacharias-Simpson

Annual Research Symposium

This poster presentation aims to understand how a rapid time-zone change can affect an individual’s circadian rhythms. By quantifying changes in physiological rhythms, the study seeks to develop targeted therapeutic interventions to mitigate the negative effects of jetlag.

Can We Eliminate The Negative Consequences Of Circadian Desynchronization Caused By Night Shift Work By Using A Light Therapy Lamp To Simulate A Sunset?, Amega Nguyen, Madison Payne, Amaka Eziakonwa, Erich Stahmer, Alexis Salinas, Samuel Park, Julie A. Zacharias-Simpson, Deborah Bell-Pedersen

Annual Research Symposium

This poster aims to understand the relationship between desynchronosis of circadian rhythms and night-shift work and how light therapy can mitigate some of the issues of desynchronosis. This study seeks to develop therapies for disrupted circadian rhythms from night-ship works.

Circadian Rhythm And Its Impact On Balance And Physical Performance, Angel Oliver, Christian Mccormick, Eseosa Aigbe, Tanner Erwin, Ariela Khandadash, Benjamin Khavkin, Samuel Park, Jutta Ward, Deborah Bell-Pedersen

Annual Research Symposium

This study explores the relationship between circadian rhythms and human performance across three key domains: cardiovascular endurance, vestibular function, and strength. Through the review of data obtained through performance testing at two different time points along with 24-hour physiological tracking, this study attempts to find correlations between circadian function and physical performance.

Investigating The Impact Of Shift Work On Circadian Rhythms And Health In Healthcare Workers, Dominique Gillette, Grace Godfrey, Jacob Godfrey, Angela Nguyen, Hannah Gewaid, Carissa Salamatin, Sharon Sengphanith, Samuel Park, Colin Burton, Neha Doppalapudi, Daniel Oraee, Deborah Bell-Pedersen

Annual Research Symposium

This poster presentation aims to discuss how working the night shift contributes to health risks through the disruption of circadian rhythm in healthcare workers. We hope to gain insight on the relationship between these disturbances and the circadian clock in order to establish strategies that optimize healthy lifestyles for healthcare workers.

Artificial Intelligence In Conservative Dentistry And Endodontics, Keerthana Kesavalu Krishnamurthy

Annual Research Symposium

No abstract provided.

Anesthesia And Pain Management In Conflict-Affected Regions: Addressing Global Health Barriers To Access And Quality Of Care​, Naeel Uddin, Sierra Brown, Maria Easler, Ayanda Mkhize, Marwa Hamdam, Chandu Goli, Lauren Draper

Annual Research Symposium

This poster examines how to deliver safe, effective anesthesia and pain control in areas with limited resources and ongoing security threats. Focusing on portable technology, ketamine-based protocols, and telemedicine, we highlight ethical considerations, training needs, and global collaborations. Our findings outline a pathway to reduce suffering and improve surgical outcomes in vulnerable populations by addressing challenges unique to conflict settings.

The Opportunities And Barriers Surrounding The Use Of Digital Health And Telemedicine In Sub-Saharan Africa, Aveline Langmead, Afua Osei-Wusu, Erica Tutuwan, Sara Mcmahon, Porter Biggs

Annual Research Symposium

No abstract provided.

Machine Learning And Shap Interpretability For Chronic Disease Understanding, Nnaemeka Charles Igwe, Khandaker Mamun Ahmed

SDSU Data Science Symposium

Non-communicable diseases (NCDs), such as diabetes, are major global health concerns influenced by various health parameters and lifestyle choices. Traditional methods struggle to efficiently predict and manage these conditions due to the complexity and diversity of medical data. There is a need to leverage machine learning algorithms and modern computational tools to accurately predict diabetes, improve diagnosis, and provide actionable insights for better healthcare outcomes. In this project we study the application of machine learning methods for predicting NCDs such as diabetes. Moreover, we leverage hyperparameter tuning techniques for model development and SHapley Additive exPlanation (SHAP) for results interpretations and …

An Open Approach To Clinical Study Recruitment Automation, Andrew Bouras, Andrew Bouras, Dhruv Patel, Rahul Kataria

HCA-NSU MD Research Day

Objective: To present an innovative Patient Recruitment Automation System that leverages open standards and promotes open data in clinical research. Background: Patient recruitment for clinical studies faces challenges in efficiency, data security, and regulatory compliance. These issues can delay research timelines and impact healthcare advancements. Methods: We developed a system that integrates with Electronic Health Record (EHR) systems to identify potential participants using predefined criteria. The platform employs Azure-based infrastructure with advanced data protection techniques, ensuring HIPAA compliance. It features an automated screening process using adaptive questionnaires and a communication module for participant engagement. Results: The system demonstrates improved efficiency …

The Impact Of Electronic Messaging On Hiv In A Medically Underserved Population, Blake Martin, Smaran Marupudi, Justin Heckman, Russell Wiggins

Research Colloquium

Introduction: HIV in the United States has affected all types of demographics and has been growing by 50,000 new infections each year. Healthy people 2030 states that their objectives of both reducing new HIV cases and increasing knowledge of the disease has had little to no change. We intend to decrease both short-term incidence of HIV contracture and long-term incidence of disease progression to AIDS via utilization of an electronic health messaging and outreach system.

Methods: Individuals will be registered for text alerts at their next AHEC medical appointment. The practitioner, utilizing an HIV Risk Assessment Tool would ask high-risk …

Vysion Software, Isaias Hernandez-Dominguez Jr, Chander Luderman Miller

2024 Symposium

Vision loss presents significant challenges in daily life. Existing solutions for blind and visually impaired individuals are often limited in functionality, expensive, or complex to use. Vysion Software addresses this gap by developing a user-friendly, all-in-one AI companion app that provides features including text summarization, real-time audio descriptions, and AI-enhanced navigation. This project details the development plan, initial functionalities, and future vision for Vysion Software.

Investigation Of The Utility Of A Ptsd Coaching Mobile App To Address Mental Health Services Demand In A Primary Care Clinic: Analysis Of Caps-5 Measures, Sindhura Nemani, Danielle Rae Schweitzer, Anne C. Jones

Rowan-Virtua Research Day

The COVID-19 pandemic affected countless people globally, resulting in a greater need for mental health professionals and resources¹. The demand for mental health care is soaring yet the limitation of resources has strained the healthcare system, making it challenging to help patients in a timely manner². This poster represents a snapshot of a larger project that is striving to investigate an intervention to help bridge the gap between patient need and prompt referral through a warm handoff approach and use of the PTSD Coach mobile application as well as exploring patients’ satisfaction^3,4,5,6,8,9. In this …

Unveiling The Potential: The Role Of Ai-Enhanced Ecg In Cardiovascular Disease Detection, Alisha Vincent

Rowan-Virtua Research Day

Background: The Electrocardiogram (ECG) is a widely utilized, non-invasive, cost-effective cardiac test. Its integration with Artificial Intelligence (AI) has empowered it to become a potent screening tool and a predictor for various cardiovascular diseases, especially in asymptomatic individuals. Objective: This review investigates the utility of AI-powered ECG in early detection of cardiac conditions, focusing on conditions such as low ejection fraction (LEF), atrial fibrillation (AF), aortic valve stenosis (AVS), and cardiac amyloidosis (CA). Methods: A literature review spanning 2018 to 2024 was conducted, analyzing 10 articles - 3 on AF, 3 on AVS, 3 on LEF, and …