Reducing Acute Healthcare Services With Self-Management Of Blood Pressure Monitoring Through Remote Patient Monitoring For Hypertensive Patients A Quality Improvement Project, Becky J. Wagner

Doctor of Nursing Practice (DNP) Manuscripts

Hypertension (HTN) affects nearly half of U.S. adults and remains a leading cause of preventable emergency department (ED) visits, hospitalizations, and healthcare costs due to poor blood pressure (BP) control (Fryar et al., 2024; Mullins et al., 2019). Traditional care models often lack the continuous monitoring and timely intervention needed for effective chronic disease management. Remote Patient Monitoring (RPM) provides an innovative approach by delivering real-time BP data, enabling early clinical intervention, and encouraging patient engagement in self-management (Omboni et al., 2020).

This Doctor of Nursing Practice (DNP) project evaluated the effectiveness of an RPM intervention in reducing acute healthcare …

Improvements Upon Reprocessing Of Orthopedic Single-Use Instruments, Alyssa P. Nguyen

Master's Projects and Capstones

Internal Medline data for Hospital A, a level I academic trauma center, identified a quality gap due to improper segregation and underutilization of orthopedic single-use device reprocessing bins. The baseline reprocessing rate of 4% for orthopedic products results in missed sustainability opportunities, financial strain, and increased regulated waste. A proposed quality improvement intervention implemented updated communication strategies, visual management tools, and education modules to reinforce current reprocessing workflows and close knowledge gaps. Outcome measures include the percentage of SUDs collected for reprocessing, survey results on reprocessing awareness, and potential financial savings in Appendix I. Early data showed a 10% year-to-year …

Ai-Driven Biomarker Discovery & Progression Modeling For Precision Diagnosis Of Glaucoma, Cheng Huang

Computer Science and Engineering Theses and Dissertations

This dissertation presents a comprehensive study on the integration of artificial intelligence (AI) for glaucoma diagnosis and retinal image analysis. Leveraging multimodal imaging data including fundus photography, Optical Coherence Tomography Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), the research develops a suite of deep learning frameworks designed to detect early glaucomatous changes with high precision, robustness, and interpretability. A series of novel architectures are introduced, spanning vessel segmentation networks, biomarker discovery pipelines, and multimodal fusion models, all designed to enhance diagnostic accuracy and generalizability across diverse populations. To facilitate reproducible and scalable ophthalmic AI research, this work …

Faktor-Faktor Yang Berhubungan Dengan Kejadian Prediabetes Pada Perawat Di Rumah Sakit X Tahun 2025, Putri Nurhaliza, Chandrayani Simanjorang, Agung Raharjo

Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan

Prediabetes dapat berkembang menjadi diabetes melitus dan meningkatkan risiko penyakit kardiovaskular. Selain itu, beban ekonomi juga meningkat akibat tingginya biaya pelayanan kesehatan dan penurunan produktivitas kerja. Salah satu kelompok berisiko prediabetes adalah perawat karena karakteristik pekerjaannya, seperti penerapan sistem kerja sif serta tingginya beban dan tekanan kerja yang dapat memicu stres. Penelitian ini dilakukan untuk mengidentifikasi faktor-faktor yang berhubungan dengan kejadian prediabetes pada perawat di Rumah Sakit X pada tahun 2025. Desain studi yang digunakan adalah cross-sectional dengan sumber data primer yang dikumpulkan melalui pengisian kuesioner dan data sekunder yang diperoleh dari laporan hasil medical check-up tahun 2025. Populasi dalam …

September 2026, Swosu Bulldog Wellness Committee

SWOSU BULLDOG WELLNESS

• Self-Care Awareness Month

• Stress Management Tips for Bulldogs

• Bulldog Resources

• Myth or Fact Quiz

From Dissertation To Deployment: A Unified Software Platform Operationalizing Clinical-Prediction And Sequential-Security Ai For Healthcare, Olsi Shehu, Damiana Teliti, Jasmin Kevrić, Bekir Karlik

Communications of the IIMA

Advances in machine learning for healthcare are abundant, yet most validated models remain confined to research notebooks and never reach secure, usable clinical software. This paper addresses that deployment gap by presenting a unified, security-hardened software platform that operationalizes two complementary streams of doctoral research inside a single, role-based hospital information system. The first stream contributes a clinical-prediction capability: an ultra-hybrid ensemble that couples a quantum-inspired feature transformation, particle-swarm feature selection, and calibrated soft voting for cancer-outcome prediction (96.41% accuracy, AUC-ROC 0.983 on TCGA-BRCA), survival stratification, multi-cancer generalization, and pharmacogenomic drug-response classification (89.31% mean accuracy across 25 compounds). The second …

Precision Approaches Improve Community Health, Roger A. Rennekamp, David Buys

Journal of Extension

Recent advances in data science provide Extension practitioners with access to data sorted by zip code, census tract, or neighborhood. Such hyper-local data now allows Extension personnel to assess community needs and assets at a more granular level and focus their work on the people and communities of greatest need. In this article, we introduce an approach we refer to as precision public health. Using such a precision approach to community assessment and, ultimately, programming can save money, increase the likelihood of producing measurable results, and create more manageable workloads for county-based Extension personnel.

September 2026, Swosu Rural Health Center

RURAL ROCKS

Introducing Hilltop Health: Connecting Campus, Community & Care

This fall marks an exciting new chapter for SWOSU Hilltop Health as services and partnerships continue to grow within the Jerry & Margaret Hodge College of Pharmacy and Rural Health Center. Designed to create a more connected approach to health and wellness, Hilltop Health brings together healthcare access, prevention, education, and community resources while creating new opportunities for collaboration across SWOSU and western Oklahoma.

Unique Pharmaceutical Laboratories (A Div. of J. B. Chemicals & Pharmaceuticals Ltd.) Issues Voluntary Nationwide Recall of Cetirizine Hydrochloride Tablets USP 5 mg Due to Potential Cross Contamination …

A Systematic Review Of Recommendations For Asynchronous Teledentistry, Helen Chen D.D.S., Seeun Mo D.D.S., Rami Habib D.D.S., Hannah Kim D.D.S., Madusha Perera D.D.S., Courtney H. Chinn D.D.S., M.P.H.

The New York State Dental Journal

Background: COVID-19 renewed interest in teledentistry to improve access to oral healthcare. This review assessed recommendations for asynchronous teledentistry regarding image capturer, device, target population, capture protocol and diagnostic ability.

Methods: Five reviewers conducted a PRISMA guided search for eligible studies published from 2000–2023. Articles were independently evaluated using a four-point rubric.

Results: Sixteen articles were included, with a mean score of 5.38/15. The lowest score was for image capturer, and the highest for diagnosis of oral disease.

Conclusion: Limited evidence supports standardized protocols, underscoring the need for further research on best teledentistry practices.

Post-Pandemic Telebehavioral Health: Sustaining And Regulating Remote Mental Health Care As A Core Modality, Weiqiao Dong

Dartmouth College Master’s Theses

The United States continues to face a persistent mental health crisis after the COVID-19 pandemic, raising a policy question about the long-term role and regulation of telebehavioral health as a core modality of care. This thesis examines that question through a case study of New York State, an early center of the pandemic and a leader in telehealth policy reform.

Guided by the Health Policy Triangle framework, this thesis integrates longitudinal data from all 62 New York counties for 2010-2025 with a 2025 cross-sectional dataset covering 61 counties. Seventeen standardized indicators are organized into four dimensions: geographic, economic, demographic, and …

Cultural Tailoring Of Digital Nutrition Interventions: A Scoping Review Of Adaptation Strategies, Evaluation Methods, And Evidence Gaps, Wendy Liang

Master's Projects and Capstones

Background: Nutrition-related chronic diseases disproportionately affect culturally diverse populations, highlighting the need for effective and equitable interventions. Digital nutrition interventions have expanded rapidly due to their accessibility; however, the extent to which they incorporate and evaluate cultural tailoring remains unclear.

Research aim: This scoping review maps the existing evidence on culturally tailored digital nutrition interventions, describes cultural adaptation strategies used, examines methods used to evaluate cultural appropriateness, and identifies gaps for future research and public health practice.

Methods: A scoping review was conducted following the PRISMA-ScR guidelines.

Findings: Culturally tailored digital nutrition interventions generally improved participant engagement, acceptability, and dietary …

Improving Adherence To Remote Patient Monitoring (Rpm) For Patients With Hypertension, Chioma Udegbune

Student Scholarly Projects

Practice Problem: Hypertension is a leading contributor to cardiovascular disease, and suboptimal adherence to remote patient monitoring (RPM) limits opportunities for timely intervention and effective blood pressure management in outpatient primary care.

PICOT: The PICOT question that guided this project was: Among outpatient clinic nursing staff responsible for remote patient monitoring (RPM) in adults with hypertension (P), how does implementation of a structured nurse-led education and reminder protocol (I), compared to standard RPM practices consisting of routine onboarding and passive reminder processes (C), influence patient adherence to RPM protocols (O) over a 10-week period (T)?

Evidence: Evidence supports nurse-led education, …

Improving Documentation Of Skin Assessment In The Med-Surg Overflow Microsystem, Min Kim, Mikeal A. Swift

Master's Projects and Capstones

Abstract

Problem

Hospital-acquired pressure injuries (HAPIs) remain a costly patient safety concern with increased morbidity and prolonged hospitalization. Inconsistent admission skin assessment documentation in a 24-bed overflow medical–surgical microsystem led to delayed wound identification and misclassification.

Context

A baseline needs assessment (n = 15) identified key barriers, including low nurse confidence utilizing Rover (mobile software application) and linking photos to the LDA (lines-drains-airway) in the electronic health record.

Intervention

A bundle of 6 components was tested over 12 weeks: standardization of the two-RN skin assessments within 8 hours of admission or transfer; optimization of Rover photo capture and LDA linkage; …

Ai-Driven Multi-Modal Mr For Precision Oncology, Maneet K. Marwaha

Radiologic Sciences

Purpose To examine the role of artificial intelligence (AI) in multiparametric magnetic resonance (MR) imaging for precision oncology, with a focus on automated tumor segmentation, treatment response prediction, and workflow efficiency.

Method A literature review was conducted to examine current evidence on AI applications in multiparametric MR imaging for oncology. Studies evaluating deep learning models for tumor segmentation, longitudinal imaging analysis, and treatment response prediction were synthesized using a thematic analysis approach.

Results Three primary themes emerged: (a) AI-driven tumor segmentation improved accuracy, reproducibility, and efficiency across multiparametric MR sequences; (b) deep learning models enhanced prediction of treatment response through …

Reducing Potentially Preventable Emergency Department Visits (Ppvs) Through A Telehealth Intervention In Children With Asthma Within A Managed Care Organization (Mco), Renee A. Roker

Doctor of Nursing Practice Final Project Abstract

Abstract

Purpose:  The purpose of this quality improvement project was to reduce unnecessary ED utilizations among children with asthma enrolled in a Medicaid managed care health plan. The project aimed to improve access to care and enhance asthma self-management.

Background:  Asthma is one of the leading causes of Emergency Department (ED) utilization, among vulnerable populations. Members experience barriers to timely primary and specialist care, contributing to Potentially Preventable ED Visits (PPV) rates. This places managed care organizations (MCOs) at risk for financial penalties if not meeting the Texas PPV benchmark.

Methodology:  Guided by the Chronic Care Model, Lean Six Sigma …

Ai-Enhanced Ct Reconstruction: Effects On Image Quality Across Dose Levels And Implications For Radiation Dose Optimization: A Systematic Review, Matthew R. Alberto

Radiologic Sciences

Purpose To evaluate how deep learning image reconstruction (DLIR) affects diagnostic image quality and noise characteristics at different radiation dose levels and how it influences dose optimization compared with conventional reconstruction methods.

Method A systematic review was conducted using major databases for studies published between 2020 and 2026. Eligible studies assessed DLIR across multiple dose levels, reported radiation dose, included quantitative image quality metrics, and compared DLIR with filtered back projection or iterative reconstruction.

Results Thirty‑seven studies met criteria, and 15 were synthesized. Three themes emerged: (a) DLIR reduced noise by 15–82% and often improved signal-to-noise and contrast-to-noise ratios while …

Reducing Mr Acquisition Times Using Artificial Intelligence: A Systematic Review, Fatin M. Arief

Radiologic Sciences

Purpose To synthesize existing evidence on artificial intelligence (AI) applications for reducing magnetic resonance (MR) imaging acquisition time, evaluate their impact on image quality, and identify challenges in clinical implementation.

Method A systematic literature review was conducted using PubMed, CINAHL, and Scopus including peer reviewed, English-language articles published between 2020 and 2026. Both qualitative and quantitative primary research were eligible and had to be on AI use in MR processes. Findings were analyzed through thematic synthesis, and the quality of each study was appraised using relevant critical appraisal tools.

Results Three major themes emerged: AI methods in MR procedures, perceived …

Impact Of Artificial Intelligence On The Roles And Career Trajectories Of Radiologic Technologists, Carolina Esquivel

Radiologic Sciences

Purpose To examine how artificial intelligence (AI) is influencing the roles, responsibilities, and career trajectories of radiologic technologists by identifying emerging challenges and opportunities associated with AI integration in medical imaging.

Method A systematic literature review was conducted using PubMed and CINAHL to identify peer-reviewed studies published between 2016 and 2026. Eligible studies examined AI applications in medical imaging and their effects on workforce roles, education, collaboration, and professional practice. Findings were synthesized using thematic analysis.

Results Three primary themes emerged: (a) workflow efficiency and protocol optimization through AI-assisted imaging processes; (b) professional skill development and evolving responsibilities related to …

High-Definition Healing: Investigating Ai-Driven Mr Reconstruction Methods, Jerell R. Jones

Radiologic Sciences

Purpose To analyze recent artificial intelligence (AI)-driven magnetic resonance (MR) reconstruction methods aimed at addressing long acquisition times, image artifacts, and workflow inefficiencies.

Method A systematic literature review was conducted using PubMed, Scopus, and Scopus AI, targeting peer‑reviewed studies published between 2015 and 2026. Search terms included “MRI,” “magnetic resonance imaging,” “artificial intelligence,” “deep learning,” and “machine learning.” Eligible studies included methodology, validation, and review papers. Extracted data included algorithm type, study design, key findings, and limitations. Themes were identified through content analysis and generative AI use.

Results Prominent themes identified were the emergence of generative adversarial networks, advanced neural …

Comparing Ai-Generated And Human-Written Radiology Reports: Evidence From The Literature, Lakenya Webb

Radiologic Sciences

Purpose To evaluate the current evidence comparing artificial intelligence (AI)-generated radiology reports with radiologist-written reports, emphasizing diagnostic accuracy, clinical reasoning, workflow efficiency, and patient safety.

Method A literature review was performed using peer-reviewed articles identified through The University of Texas MD Anderson Cancer Center Research Medical Library. Studies evaluating AI-generated radiology reports were analyzed using AI-assisted thematic synthesis to identify recurring patterns related to report quality, diagnostic performance, and clinical implementation.

Results The literature consistently identified three overarching themes: (a) AI-generated reports demonstrated improvements in structured reporting and factual consistency but exhibited variable diagnostic accuracy; (b) current AI systems had …