Biomedical Informatics Commons^™

Advancing Precision Medicine: Unveiling Disease Trajectories, Decoding Biomarkers, And Tailoring Individual Treatments, Yanfei Wang

Dissertations & Theses (Open Access)

Chronic diseases are not only prevalent but also exert a considerable strain on the healthcare system, individuals, and communities. Nearly half of all Americans suffer from at least one chronic disease, which is still growing. The development of machine learning has brought new directions to chronic disease analysis. Many data scientists have devoted themselves to understanding how a disease progresses over time, which can lead to better patient management, identification of disease stages, and targeted interventions. However, due to the slow progression of chronic disease, symptoms are barely noticed until the disease is advanced, challenging early detection. Meanwhile, chronic diseases …

Operationalizing The Datagauge Framework In A Health Information Exchange Utilizing Hepatitis C Data, Edward Yao

Translational Projects (Open Access)

This project aims to implement the DataGauge framework in a health information exchange (HIE) setting as a proof of concept. The modified DataGauge framework, described by Diaz-Garelli et al. (2019), is utilized to test its functionality and applicability with any dataset. The specific objective of the project is to determine the number of hepatitis C-positive tests within the HIE. The implementation involved multiple iterations following the DataGauge framework's steps for data extraction and analysis. Five iterations were conducted, resulting in both successful and failed queries based on the validity of the data standards. The findings revealed that the HIE, in …

Multiparametric Magnetic Resonance Imaging Artificial Intelligence Pipeline For Oropharyngeal Cancer Radiotherapy Treatment Guidance, Kareem Wahid

Dissertations & Theses (Open Access)

Oropharyngeal cancer (OPC) is a widespread disease and one of the few domestic cancers that is rising in incidence. Radiographic images are crucial for assessment of OPC and aid in radiotherapy (RT) treatment. However, RT planning with conventional imaging approaches requires operator-dependent tumor segmentation, which is the primary source of treatment error. Further, OPC expresses differential tumor/node mid-RT response (rapid response) rates, resulting in significant differences between planned and delivered RT dose. Finally, clinical outcomes for OPC patients can also be variable, which warrants the investigation of prognostic models. Multiparametric MRI (mpMRI) techniques that incorporate simultaneous anatomical and functional information …

Implementing Clinical Decision Support Aimed At Reducing Co-Prescribing Of Opioids And Benzodiazepines At Adventist Healthcare Maryland, Monica Coley

Translational Projects (Open Access)

Clinical Decision Support (CDS) leverages computerized toolsets to provide condition specific guidance that aids providers in clinical decision making processes (AHRQ, 2019; AMIA, n.d.; ONC, 2018). Research has shown that applying CDS, interruptive within the electronic health record (EHR) prescribing workflow, can assist providers with avoiding unsafe medication prescribing, such as 1) multiple opioids and 2) opioid-benzodiazepine combinations (Malte et al., 2018; Smith et al., 2019, Price-Haywood et al., 2020; Nelson et al., 2022). In an effort to decrease the co-prescribing rate for 1) multiple opioids and 2) opioid-benzodiazepine combinations, Adventist HealthCare Maryland (AHC) launched a performance improvement project in …

Exploring The Use Of Bidirectional Text Messaging Reminders To Increase Colorectal Cancer Screening Rates In Patients Prescribed Cologuard®, James Harris

Translational Projects (Open Access)

Meaningfully engaging with patients through technology is becoming increasingly important in healthcare. Mailed letters, phone calls, and even one-way text messaging or some combination of these have all been utilized to communicate with patients regarding preventative healthcare screening measures, with varying degrees of success. While many studies have examined the use of bidirectional text messaging (BTM) to engage patients regarding mammograms, cervical cancer screening, and other issues, very little literature exists on BTM concerning colorectal cancer (CRC).

Therefore, this project sought to examine the impact of BTM between two primary care clinics and their respective patients who were prescribed and …

Virtual Patient/Family Communication In The Acute Care Setting, Kathleen Defigueiredo

Translational Projects (Open Access)

Patient and family-centered care strategies see patients and families as valuable healthcare team members. Such strategies thus treat these groups as essential clinical partners in providing safe, high-quality care. Participation, collaboration, and shared decision-making are central to this framework. Historically, hospitals have relied on physical presence at the bedside as a prerequisite to engaging families in the shared decision-making process. Visitor restrictions of the COVID-19 pandemic removed the primary strategy for family participation: physical presence. Healthcare organizations rapidly deployed mobile devices to help minimize the exposure of healthcare providers and provide video visits for family members. This deployment was often …

Implementation Of Telemedicine To Reduce No-Show Rates, Peter Kizza

Translational Projects (Open Access)

Missed appointments, or no-shows, are defined as “patients who neither kept nor canceled scheduled appointments” (Dayal, 2019, p.27). Missed appointments cost the United States healthcare system more than $150 billion annually. They disrupt the continuity of healthcare services, add to patients' dissatisfaction due to delays in getting new appointments, and hinder the detection and treatment of disease. The rates of missed appointments vary between countries and healthcare systems. Studies conducted previously in primary care settings found that the rate of missed appointments ranged from 5%–55% in different series in the United States. One study suggested that missed appointments are likely …

Leveraging Digital Technologies For Management Of Peripartum Depression To Mitigate Health Disparities, Alexandra Zingg

Dissertations & Theses (Open Access)

Health disparities are adverse, preventable differences in health outcomes that affect disadvantaged populations. Examples of health disparities can be seen in the condition of peripartum depression (PPD), a mood disorder affecting approximately 10-15% of peripartum women. For example, Hispanic and African-American women are less likely to start or continue PPD treatment. Digital health technologies have emerged as practical solutions for PPD care and self-management. However, existing digital solutions lack an incorporation of behavior theory and distinctive information needs based on women’s personal, social, and clinical profiles. Bridging this gap, I adapt Digilego, an integrative digital health development framework consisting of: …

Visualization Literacy And Decision-Making In Healthcare, Stacy Weil

Translational Projects (Open Access)

The ability of workers in the healthcare industry to analyze, interpret and communicate with health data is critical to decision-making and impacts both health and business outcomes. Optimal decision-making requires having real-time access to information that provides useful insights and that lends itself to collaborative decision-making. Data visualizations have the potential to facilitate decision-making in healthcare when presented as a dashboard. However, dashboards have shown varying results in both effectiveness and adoption. Data or graphical literacy challenges experienced by health team members could complicate strategic decision-making through an inability to correctly interpret or summarize the information presented in a dashboard. …

Usability And Technology Acceptance Of An Electronic Child Abuse Screening Tool In A Pediatric Emergency Department, Angela Hayes

Translational Projects (Open Access)

Up to half of all child physical abuse victims with major abuse injuries seen in hospitals had sentinel injuries assessed by medical providers. Universal screening for child abuse and neglect in the emergency department can potentially increase detection at lower levels of injury. However, we must consider usability for the electronic health record embedded child abuse and neglect-screening tool to be most effective. The user most likely to interact with the screening tool is the bedside nurse. The interface of the initial screening tool and the process of inputting information must be perceived as useful, usable, and satisfying to the …

Social Network Analysis Of Online Support Communities For Adolescent And Young Adult Cancer Survivors, Carlos Perez Aldana

Dissertations & Theses (Open Access)

There are an estimated 633,000 adolescent and young adult (AYA) cancer survivors in the U.S. and nearly 89,500 AYAs are diagnosed with cancer every year. Cancer creates developmental and life stage disruptions, which result in multiple survivorship challenges, particularly among AYAs. Despite the advances made in cancer oncology and survivorship care, AYA cancer survivors continue to face diverse and unique psychosocial needs. Research suggests that online support communities have the potential to positively impact psychosocial care by providing AYA cancer survivors with access to social support which can help them successfully transition from treatment back to normal life as well …

Identifying Risk Factors For Anchoring Bias During Emergency Department Transitions Of Care, Roni Matin

Dissertations & Theses (Open Access)

Transitions of care have been associated with breakdowns in communication and medical errors. In emergency departments (ED) these handoffs are typically known as sign outs. Sign outs provide continuity of care for ED patients whose diagnosis and care fall across shift changes. They are short interactions where pertinent information and responsibility for the patient is transferred to the physician assuming care for them. However, these exchanges may also be an opportunity for cognitive biases to be transferred or introduced, leading to erroneous decision making. Anchoring bias is known to have a significant impact on clinical decision making. Yet, little is …

Evaluation, Validation & Implementation Of A Computerized Diagnostic Decision Support System In Primary Practice, Joe Bridges

Translational Projects (Open Access)

Background: Medical diagnosis may be the most complex task attempted by humans. Studies estimate that 95% of diagnoses in outpatient care are accurate, implying that the annual rate of inaccurate diagnoses is 12 million in the US alone, with the potential for patient harm in about half. A well-researched differential might reduce inaccurate diagnoses by offering alternatives matching the patient’s symptoms. This study searched the literature for articles evaluating the diagnostic performance of commercially available computerized diagnostic decision support systems. This search led to selecting Isabel Pro, developed by Isabel Healthcare, Ltd. of Haslemere, UK.

Evaluation and Validation: …

Computer-Aided Diagnosis For Melanoma Using Ontology And Deep Learning Approaches, Xinyuan Zhang

Dissertations & Theses (Open Access)

The emergence of deep-learning algorithms provides great potential to enhance the prediction performance of computer-aided supporting diagnosis systems. Recent research efforts indicated that well-trained algorithms could achieve the accuracy level of experienced senior clinicians in the Dermatology field. However, the lack of interpretability and transparency hinders the algorithms’ utility in real-life. Physicians and patients require a certain level of interpretability for them to accept and trust the results. Another limitation of AI algorithms is the lack of consideration of other information related to the disease diagnosis, for example some typical dermoscopic features and diagnostic guidelines. Clinical guidelines for skin disease …

Enhance Representation Learning Of Clinical Narrative With Neural Networks For Clinical Predictive Modeling, Yuqi Si

Dissertations & Theses (Open Access)

Medicine is undergoing a technological revolution. Understanding human health from clinical data has major challenges from technical and practical perspectives, thus prompting methods that understand large, complex, and noisy data. These methods are particularly necessary for natural language data from clinical narratives/notes, which contain some of the richest information on a patient. Meanwhile, deep neural networks have achieved superior performance in a wide variety of natural language processing (NLP) tasks because of their capacity to encode meaningful but abstract representations and learn the entire task end-to-end. In this thesis, I investigate representation learning of clinical narratives with deep neural networks …

Secondary Use Of Structured Electronic Health Records Data: From Observational Studies To Deep Learning-Based Predictive Modeling, Laila Bekhet

Dissertations & Theses (Open Access)

With the wide adoption of electronic health records (EHRs), researchers, as well as large healthcare organizations, governmental institutions, insurance, and pharmaceutical companies have been interested in leveraging this rich clinical data source to extract clinical evidence and develop predictive algorithms. Large vendors have been able to compile structured EHR data from sites all over the United States, de-identify these data, and make them available to data science researchers in a more usable format. For this dissertation, we leveraged one of the earliest and largest secondary EHR data sources and conducted three studies of increasing scope. In the first study, which …

Standardizing New Diagnostic Tests To Facilitate Rapid Responses To The Covid-19 Pandemic, Xiao Dong

Dissertations & Theses (Open Access)

In order to enhance the data interoperability, an expeditious and accurate standardization solution is highly desirable for naming rapidly emerging novel lab tests, and thus diminishes confusion in early responses to pandemic outbreaks. This is a preliminary study to explore the roles and implementation of medical informatics technology, especially natural language processing and ontology methods, in standardizing information about emerging lab tests during a pandemic, thereby facilitating rapid responses to the pandemic. The ultimate goal of this study is to develop an informatics framework for rapid standardization of lab testing names during a pandemic to better prepare for future public …

Determining The Utility Of Hl7® Fast Healthcare Interoperability Resources (Fhir®) Standards In Supporting Ehr And Edc-Agnostic Esource Implementations For Clinical Research, Maryam Garza

Dissertations & Theses (Open Access)

Advances in efficiency while maintaining or improving quality are immediately needed in clinical research, specifically for multicenter clinical studies. Though recent evidence points toward electronic health record (EHR) to electronic data capture (EDC) system (EHR to EDC) data collection as a viable contribution, there are many unanswered process and outcome-level questions regarding quality, site burden, and cost within the context of multicenter clinical trials. Direct extraction and use of EHR data in multicenter clinical studies is a long-term and multifaceted endeavor that includes design, development, implementation and evaluation of methods and tools for semi-automating tasks in the research data collection …

Turf For Teams: Considering Both The Team And I In The Work-Centered Design Of Systems, Vickie Nguyen

Dissertations & Theses (Open Access)

Teams are an inherent part of many work domains, especially in the healthcare environment. Yet, most systems are often built with only the individual user in mind. How can we better incorporate the team, as a user, into the design of a system? By better understanding the team, through their user, task, representational, and functional needs, we can create more useful and helpful systems that match their work domain. For this research project, we utilize the TURF framework and expanded it further by also considering teams as a user, thus, creating the TURF for Teams framework. In addition, we chose …