Health Information Technology Commons^™

Enhancing Hospital Length Of Stay Using Ai Agent Modular Capabilities, Dami Fred

Theses and Dissertations

Hospital Length of Stay (LOS) analysis is essential for managing hospital efficiency and financial performance, yet the analytical depth required remains inaccessible to many organizations due to technical and resource constraints. This thesis introduces the AI Agent Modular Capabilities (AIAM) framework, which decomposes LOS analysis into discrete, codifiable capabilities integrated into a single skill activatable with one prompt. Seven AI Agent Modular Capabilities were developed using a Work Breakdown Structure and tested against a simulated hospital scenario across three successive skill versions. Results demonstrate that the packaged AIAM skill produces comprehensive, consistent, multi-section LOS analyses from a single interaction, outperforming …

Digital Technology And Women’S Health In Nigeria: A Feminist Sts Walkthrough Analysis Of Mdoc Digital Health, Edith Michael Ogbodo

Dissertations, Master's Theses and Master's Reports

This thesis critically examines how a Nigerian digital health platform, mDoc, represents and constructs women’s health. Drawing on Feminist Science and Technology Studies (STS) and Light et al.’s (2018) walkthrough method, the study interrogates the values, assumptions, and power relations embedded in mDoc’s design, language, and governance structures. The analysis reveals that mDoc, despite positioning itself as an equitable solution to Nigeria’s health crisis, reproduces and depoliticizes the structural inequalities it claims to address. Through its neoliberal emphasis on self-care, the individualization of structurally produced suffering, and the datafication of women’s bodies, the platform encodes gendered, colonial, and class-based assumptions …

From Passive To Powerful: Creating Engaging Resident-As-Teacher Modules, Anna E Rueda, Stephanie V Sherman, Sherita J Love, Glenn C Bridges, Wesley A Mayer, Mark J Harbott, Teri L Turner, Bani M Ratan

Faculty and Staff Publications

Background: We aimed to design, implement, and evaluate three novel institutional resident-as-teacher (RAT) e-modules for postgraduate year (PGY) 1, 2, and 3 and compare them to previously utilized online trainings.

Methods: We utilized PICRAT, a model examining both students' relationship with technology (passive, interactive, creative) and instructors' use of technology (replaces, amplifies, or transforms) to create interactive experiences that amplified teaching methodologies. We compared evaluations of the previous and new trainings with an unpaired t test. New modules were assessed with one-way analysis of variance for specialty-based acceptability and content analysis of two open-ended questions.

Results: Response rates averaged 93.2% …

From Silos To Systems: A Conceptual Framework For Workforce Aligned Oral Health Education, Meghan Bastin

2026 Scholarly Teaching Conference: Poster Session Papers

In the current U.S. educational system, becoming a dentist follows a few prescriptive pathways.  Learners typically complete an undergraduate degree before entering time-intensive doctoral training.  This results in only 3-4 years of direct professional education embedded within an eight -year process, while learners accumulate significant financial investment in their education.  With the average cost of graduate-level dental education alone exceeding $300,000 and new federal borrowing limits likely to further constrain access, there is an opportunity to explore alternative ways of structuring oral health education.

This poster presents a conceptual, system-level framework that explores a perspective in which oral health education …

Striving To Thrive: Balancing Digital Health Innovation And Patient Protection Under Thailand’S Legal Framework, Thidarat Liamsomboon

Theses and Dissertations

The digitalization of health care has fundamentally transformed how health care services are accessed, delivered, and experienced worldwide. Telemedicine, artificial intelligence–assisted diagnostics, electronic health records, wearables, and mobile health applications are no longer novelties, but have become a substantial part of a modern clinical practice. Although these technologies offer great prospects for making health care more accessible, reducing administrative burden, and improving the quality of care, they also pose significant legal and regulatory challenges. The rate of technological development has far outpaced Thailand’s existing legal frameworks for regulating medical practice, professional accountability, and patient protection. This regulatory “lag” has generated …

Robust And Interpretable Medical Image Segmentation Via Retrieval And Mechanistic Analysis, Salma Ahmed

Theses and Dissertations (Comprehensive)

Medical image segmentation is a critical component of clinical decision-making, yet deep learning based segmentation models face persistent challenges. These models typically require large volumes of densely annotated data, exhibit strong sensitivity to domain shifts across scanners and patient populations, and lack explicit anatomical priors. Furthermore, despite continual architectural advances beyond fully convolutional networks, most segmentation models remain opaque, where they lack the granularity required for component-level analysis. As a result, when segmentation models fail, it is difficult to identify which internal representations are responsible, limiting developers’ ability to diagnose errors, improve robustness, or establish trust in clinical settings. Existing …

Instruction-Tuned Large Language Models With Explicit Domain Control For Sexual And Reproductive Health Education, Dinda Majesty, Kemas Rahmat Saleh Wiharja

Knowledge Engineering and Data Science

Sexual and reproductive health (SRH) education remains a sensitive and underserved domain in Indonesia, where sociocultural factors often constrain access to medically reliable information. While large language models (LLMs) enable conversational health assistance, general-purpose models lack explicit domain control, raising safety and reliability concerns in sensitive medical contexts. This study presents a domain-specific SRH conversational system developed through supervised instruction tuning of LLaMA-2-7B-Chat using 93,299 instruction-formatted samples derived from physician-authored question–answer interactions. The training objective follows causal language modeling over structured instruction sequences. At the same time, domain boundaries are enforced through explicit refusal modeling embedded directly in the instruction-tuning …

Integrating Association Rule Mining With Neural Collaborative Filtering For Clinical Drug Recommendation, Baso Ummul Ikshan, Irawati Irawati, Herdianti Darwis, Roesman Ridwan Raja

Knowledge Engineering and Data Science

Selecting appropriate drug therapy is an important part of clinical decision-making because it requires matching medications with patient complaints and diagnoses. However, drug recommendation in primary healthcare still relies heavily on manual interpretation, limiting scalability, reproducibility, and systematic knowledge extraction from routine medical records. From a Knowledge Engineering and data-driven recommendation perspective, this challenge highlights the need for approaches that can transform clinical co-occurrence patterns into structured, machine-interpretable interactions. This study investigates integrating Association Rule Mining (Apriori and FP-Growth) with Neural Collaborative Filtering (NCF) to develop a context-based drug therapy recommendation system. A total of 1,000 medical record transactions were …

Hubungan Persepsi Manfaat Terhadap Kesadaran Kesehatan Pengguna Wearable Device Di Kota Banda Aceh, Raihanil Fitri, Tahara Dilla Santi, Hafnidar A. Rani

Perilaku dan Promosi Kesehatan: Indonesian Journal of Health Promotion and Behavior

Background. Wearable devices are portable technologies designed to be worn directly on the body and capable of collecting and analyzing data related to various aspects of a user's health. Aim. This study aims to analyze the influence of perceived benefits on users' health awareness among wearable device users in Banda Aceh City.

Aim. This study aims to analyze association of perceived benefits on users' health awareness among wearable device users in Banda Aceh City.

Method. This research applied a descriptive quantitative design with a cross-sectional approach. Data were collected using a questionnaire from 106 active wearable device …

Using Machine Learning To Predict Women At Risk Having A Child With Congenital Heart Defects, Amany M. Abdo Prof., Asmaa M. Mosallam Ms., Laila M. Abdelhamid Assoc.Prof.

Information Systems

Congenital heart defects (CHD) are heart malformations present at birth, affecting heart function and circulation, and are a leading cause of infant mortality. CHD can result from genetic, environmental, and maternal health factors, making early detection essential. Early diagnosis allows for timely intervention, reducing risks like heart failure or stroke. In countries like Egypt, CHD often remains undiagnosed due to limited healthcare resources. Artificial intelligence (AI) can improve early detection by analyzing risk factors. This study presents a predictive model for CHD using maternal and paternal health factors. Data was collected from 571 families: 260 with a CHD-affected child and …

Mediapipe-Based Extraction Of Joint Rom And Position From Patient Videos For The Functional Movement Screen: An Exploratory Study, Joshua Paul Verdillo, Lily Ann Bautista

Philippine Journal of Physical Therapy

Introduction. The Functional Movement Screen (FMS) is widely used to identify movement deficiencies and potential injury risk. However, its reliance on visual inspection introduces subjectivity, requires specialized training, and necessitates face-to-face assessment. Advances in computer vision, offer opportunities to automate and better objectify functional movement assessment. This exploratory study aimed to evaluate the feasibility of using a MediaPipe-based system, Software-Optimized Movement Assessment (SOMA), to extract joint range of motion (ROM), joint position, and compensatory movement patterns from patient videos during FMS performance.

Methods. SOMA was developed using MediaPipe Pose and MediaPipe Hands libraries integrated with Python-based tools to analyze videos …

Personal Health Advice In The World Of Artificial Intelligence: An Assessment Of Responses From Chatgpt For Three Common Health Conditions In The Southern United States, Marion W. Evans Jr, Julie Harrison Swartz, Harrison Ndetan, Damian Francis, John Moore, Mary Kozub, Ernie Kaninjing, Jennifer Jones-Locklear, Debbie Greene, Josie Doss

Journal of Public Health in the Deep South

Background: Artificial intelligence (AI) applications within the health sciences including education and healthcare practice are now common. Patients are likely to apply AI to better understand their health status or to learn what they can do to improve their health.

Purpose: The purpose of this study was to evaluate outputs from ChatGPT for three common health conditions seen in the southern United States as to whether it would include medically biased care or lifestyle related advice, legitimate sources of information and to assess reading levels generated.

Methods: Health care professionals rated outputs in 4 areas and interrater …

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 …

Implementation And Outcomes Of A Digital Onboarding Taskforce In The Acute Care Setting, Julianna Lenoir, Alexzandra Gentsch, Akshay Krishnan, Jeffrey Ndubisi, Marissa Witmer, Kristin L. Rising, Brooke Worster, Angela M. Gerolamo

Jefferson Center for Connected Care Faculty Papers

INTRODUCTION: Use of digital health technology can improve patient health outcomes; however, not all patients have the knowledge and skills to download a health app and access a patient portal. Providing digital onboarding support to hospitalized patients has potential to overcome some barriers to accessing needed education in the community, including both having the time and a location to receive education. To address this, our team developed the Jefferson Digital Onboarding Taskforce (JeffDOT), a group of staff and students who approach hospitalized patients and provide one-on-one teaching on how to sign up for and use a patient portal.

METHODS AND …

Evaluating The Impact Of System, Information, And Service Quality On User Outcomes In Malaysian Public Hospitals: A Structural Equation Modeling Approach, Muhd Siv Azhar Merican Abdullah, Azimatun Noor Aizuddin, Mohd Rizal Abdul Manaf

Makara Journal of Health Research

Background: Increasing use of hospital information systems (HIS) underscores the need to evaluate their impact on User Satisfaction and Perceived Net Benefits. This study investigated the connections among outsourced System Quality, Information Quality, Service Quality, Perceived Usefulness, User Satisfaction, and Perceived Net Benefits in the context of Malaysian public hospitals.

Methods: Data were collected from 1,376 healthcare personnel across six public hospitals and analyzed using structural equation modeling through analysis of moment structures grounded in the DeLone and McLean Information Systems Success Model.

Results: System and Service Qualities significantly influenced User Satisfaction and Perceived Usefulness, while Information Quality impacted …

Objective Vs. Perceived Maternal Smartphone Use And Observed Mother-Infant Interaction Quality, Alison K. Ventura, Lara N. Wolfers, Sarah M. Coyne, Rachel Pfafman, Sabrina Uva, Karla I. Ceja Almontes, Aniruddha S. Shinde, Adam M. Galovan, Brandon Mcdaniel

Health Services and Informatics Research

Introduction:

Prior research links maternal smartphone use to reduced sensitivity and responsiveness to infant cues, but emerging evidence suggests that mothers' perceptions of their smartphone use - such as feelings of empowerment or distress - may also shape the quality of mother-infant interactions. This study examined how both objective and perceived smartphone use related to mother-infant interaction quality in naturalistic settings.

Method:

Participants were 147 mother-infant dyads from a longitudinal study of smartphone use and infant development. When infants were 2 months old, mothers completed 5 days of ecological momentary assessment (EMA), reporting time spent with their infant, perceived smartphone-related …

Dental Care Utilization And Expenditures Among Individuals With Asthma, Shillpa Naaval, Vaibhavi Mone

Health Services and Informatics Research

Objectives To examine dental care utilization and health and dental care expenditures among individuals with asthma.

Methods Data from the 2022 Medical Expenditure Panel Survey (MEPS) (n = 21,405) were used to examine dental care utilization (any dental, preventive dental, and treatment dental visit) among individuals ≥ 1 year with and without asthma, and mean expenditures were summarized.

Results Overall, the asthma diagnosis was 13.2%, 14.7% in working-age adults compared to 9.5% in children. The percentage of treatment dental visits was higher overall (17.0% vs. 14.5%, p <  0.05) among the asthma group compared to the non-asthma group. Among individuals with asthma, those who had preventive dental visits had lower dental expenditures compared to those who had treatment dental visits for all age groups.

Conclusion Individuals with asthma had a higher prevalence of using dental treatment services. …

Referral Strategies For Recruitment And Engagement Of Community Adults Into Online Extension Health Programs, Cheryl L. Eschbach, Dawn A. Contreras, Holly B. Tiret

Journal of Human Sciences and Extension

This article shares details behind building organizational capacity to establish program referrals for statewide recruitment of community adults into Cooperative Extension’s online health programs. This study explores the role of intentional recruitment strategies (active and passive) to increase participant program enrollment into health education and shares examples from one state that has created a trained workforce that offers ongoing research- and evidence-based programs. After many years of trying paper, phone, and electronic medical record methods to increase program reach, Michigan State University Extension tried an electronic referral process via a QR code and web link, accompanied by program marketing, to …

December 2025, Swosu Bulldog Wellness Committee

SWOSU BULLDOG WELLNESS

• SWOSU Wellness 5k
• Employee Massages 12/4 & 12/5
• Flu Season
• Winter Crossword

Augmenting Large Language Models To Predict Social Determinants Of Mental Health In Opioid Use Disorder Using Patient Clinical Notes, Madhavi Pagare, Deva Sai Kumar Bheesetti, Inyene E. Essien-Aleksi, Mohammad Arif Ul Alam

Health Sciences Faculty Publications

Objective

Identifying social determinants of mental health (SDOMH) in patients with opioid use disorder (OUD) is crucial for estimating risk and enabling early intervention. Extracting such data from unstructured clinical notes is challenging due to annotation complexity and requires advanced natural language processing (NLP) techniques. We propose the Human-in-the-Loop Large Language Model Interaction for Annotation (HLLIA) framework, combined with a Multilevel Hierarchical Clinical-Longformer Embedding (MHCLE) algorithm, to annotate and predict SDOMH variables. Materials and Methods

We utilized 2636 annotated discharge summaries from the Medical Information Mart for Intensive Care (MIMIC-IV) dataset. High-quality annotations were ensured via a human-in-the-loop approach, refined …

December 2025, Swosu Rural Health Center

RURAL ROCKS

• FDA MedWatch - 20 mEq Potassium Chloride Injection by Otsuka ICU Medical
• Plan to expand Medicare Coverage of GLP-1s
• Pharmacist Interventions in The US Oncology Network Cut Cancer Care Costs by Nearly $9 Million

Real-Time Estimated Sequential Organ Failure Assessment (Sofa) Score With Intervals: Improved Risk Monitoring With Estimated Uncertainty In Health Condition For Patients In Intensive Care Units, Yan He, Qian Luo, Hai Wang, Zhichao Zheng, Haidong Luo, Oon Cheong Ooi

Research Collection Lee Kong Chian School Of Business

Purpose: Real-time risk monitoring is critical but challenging in intensive care units (ICUs) due to the lack of real-time updates for most clinical variables. Although real-time predictions have been integrated into various risk-scoring systems to aid monitoring, existing systems do not address uncertainties in risk assessments. We developed an enhanced risk monitoring framework based on commonly used systems like the Sequential Organ Failure Assessment (SOFA) score by incorporating uncertainties to improve the effectiveness of real-time risk monitoring in ICUs.Methods: This study included 5,351 patients admitted to the Cardiothoracic ICU in the National University Hospital in Singapore. We developed machine learning …

A Study On The Influence Of Entity Internet Hospital Platforms And Health Literacy Facilitation On Postoperative Patients’ Platform Usage, Hong Ye

Dissertations and Theses Collection (Open Access)

Entity Internet Hospital (EIH) is emerging online medical service platforms in China. Currently, while EIHs in China are developing rapidly, their usage rates remain low. However, postoperative patients have substantial follow-up consultation needs. Consequently, incentivizing postoperative patients to use EIH from the demand side is a highly challenging proposition in the current era. Grounded in Technology Acceptance Model and Health Belief Model, this study examined the impacts of platform and health literacy facilitation on platform usage (including intention and frequency) among 631 postoperative patients with cardiovascular disease from four medical institutions in Wuhan, and explored the moderating role of literacy …

Ataxia-Telangiectasia Mutated Activation Mediates Transforming Growth Factor Beta Signaling In Acetaminophen-Induced Liver Injury In Mice, Matthew Mcmillin, Christopher S Chu, Elaina Williams, Juliet Venter, Kiersten Bell, Anca D Petrescu, Patrick Mireles, Sharon Demorrow

Faculty and Staff Publications

Acetaminophen (APAP) overdose is associated with increased transforming growth factor beta 1 (TGFβ1) signaling and elevated oxidative stress, which exacerbate DNA damage. TGFβ1 has been shown to regulate ataxia-telangiectasia mutated (ATM) signaling and DNA repair in other cell types. This study investigates the DNA damage response (DDR) during APAP-induced liver injury, focusing on ATM-mediated regulation of TGFβ1 signaling. APAP administration in vitro and in vivo resulted in DNA damage, increased ATM signaling, accumulation of γH2AX, and activation of phosphorylated ataxia telangiectasia mutated (pATM) and phosphorylated checkpoint kinase 2 (pChk2). Pretreatment with an ATM inhibitor, KU55933, attenuated APAP-induced hepatocyte damage and …

Development Of A Telenursing-Based Self-Assessment Questionnaire For Diabetic Foot Ulcer Risk, Ratna Wirawati Rosyida, Sugiyarto Sugiyarto

Jurnal Keperawatan Indonesia

Development of a Telenursing-Based Self-Assessment Questionnaire for Diabetic Foot Ulcer Risk. Early identification of the risk of diabetic foot ulcers (DFU) is crucial in preventing ulcers. Caring for diabetic patients, including early detection of the risk of DFU with telenursing, will improve accessibility to health facilities and also help the work of nurses. Currently, there are many instruments or tools to detect the risk of DFU, but instruments that apply telenursing and can be used independently and easily by patients are still limited. This study aimed to develop a digital self-assessment questionnaire for DFU risk in type 2 Diabetes Mellitus …

Promoting Competence And Confidence: Simulation-Based Basic Life Support Training For Jordanian Nurses, Yousef Shukry Abu-Wardeh, Wan Muhamad Amir W Ahmad, Mohd Shaharudin Shah Che Hamzah, Intan Idiana Hassan

Jurnal Keperawatan Indonesia

Cardiopulmonary arrest is a major health issue that affects healthcare providers. The COVID-19 pandemic has added a new risk to rescuers who may be attempting to resuscitate victims. It is essential to strike a balance between resuscitation and the need to protect oneself from infection. The study aims to evaluate the effectiveness of simulation training in enhancing the Basic Life Support (BLS) knowledge, skills, and confidence levels of newly employed nurses. The study employed a single-masked, prospective, randomized controlled trial design, which consisted of three phases: a pre-test, an immediate post-test, and a post-test conducted three months later. The American …

Determining Factors For Long Term Use Of Gadget By Preschool Children, Wardatus Sholihah, Allenidekania Allenidekania, Nur Agustini, Rukmini Rukmini, Dwi Yuniar Ramadhani

Jurnal Keperawatan Indonesia

In the digital era, preschoolers spent more time playing on their gadgets than with their peers. The excessive use of gadgets (including laptops, cellphones, tablets, and similar electronic devices) can have negative impacts on preschool-age children. This study analyzes the determining factors that influence the duration of gadget use in preschool children. The study used a correlational design with a cross-sectional approach involving 318 parents who were selected using cluster sampling. The results showed that there was a significant relationship between the duration of gadget use and the gender of the parents (p = 0.001), parental education (p = 0.035), …

Psychological Distress And Quality Of Life Among Infertility Couples Undergoing Infertility Treatment In Malaysia, Farrahdilla Hamzah, Zamzaliza Abdul Mulud, Malini Mat Napes, Sarah Abdul Mubarak, Rosliza Shafie

Jurnal Keperawatan Indonesia

Infertility often leads to stress, anxiety, and depression, significantly affecting the quality of life of affected couples. This study explored the sociodemographic and psychological factors influencing the quality of life among infertile couples undergoing in vitro fertilization (IVF) treatment in Malaysia, using a cross-sectional design. A total of 126 infertile couples were purposively sampled from three public hospitals offering IVF treatment. The Depression, Anxiety, and Stress Scale (DASS-21) measured psychological distress levels, while the Fertility Quality of Life (Ferti-QoL) scale assessed fertility-related quality of life. Data collection adhered to strict ethical standards, with confidentiality ensured. Participants provided informed consent and …

Assessing Community Readiness And Benefits Of A Nursing Program: Implications For Healthcare And Education, Mary Anne Frances D. Reyes, Aaron A. Funa, Robert Jamisola, Ma. Joahna D. Perdigon, Jerica D. Latonero

Jurnal Keperawatan Indonesia

In response to recent policy shifts allowing the establishment of new nursing programs in the Philippines, this study assesses the perceived readiness of Sorsogon, a geographically underserved province, to implement a bachelor of science in nursing program. It also explores the anticipated benefits that such a program may offer to students and the local community. A cross-sectional survey of 375 stakeholders, selected through purposive sampling, was conducted using a validated instrument developed through expert consultation. Quantitative data were analyzed using descriptive statistics, while qualitative responses were examined through thematic analysis. The findings reveal widespread support for the proposed program, emphasizing …