Doctor of Philosophy

dissertationClinical research plays a vital role in producing knowledge valuable for understanding human disease and improving healthcare quality. Human subject protection is an obligation essential to the clinical research endeavor, much of which is governed by federal regulations and rules. Institutional Review Boards (IRBs) are responsible for overseeing human subject research to protect individuals from harm and to preserve their rights. Researchers are required to submit and maintain an IRB application, which is an important component in the clinical research process that can significantly affect the timeliness and ethical quality of the study. As clinical research has expanded in both volume and scope over recent years, IRBs are facing increasing challenges in providing efficient and effective oversight. The Clinical Research Informatics (CRI) domain has made significant efforts to support various aspects of clinical research through developing information systems and standards. However, information technology use by IRBs has not received much attention from the CRI community. This dissertation project analyzed over 100 IRB application systems currently used at major academic institutions in the United States. The varieties of system types and lack of standardized application forms across institutions are discussed in detail. The need for building an IRB domain analysis model is identified. . iv In this dissertation, I developed an IRB domain analysis model with a special focus on promoting interoperability among CRI systems to streamline the clinical research workflow. The model was evaluated by a comparison with five real-world IRB application systems. Finally, a prototype implementation of the model was demonstrated by the integration of an electronic IRB system with a health data query system. This dissertation project fills a gap in the research of information technology use for the IRB oversight domain. Adoption of the IRB domain analysis model has potential to enhance efficient and high-quality ethics oversight and to streamline the clinical research workflow

Mental Health Assessment of Dental Students and Dental Residents in a Midwestern Dental School: A Pilot Study

Title from PDF of title page, viewed November 10, 2023Thesis advisors: Melanie Simmer-Beck and Mary P. WalkerVitaIncludes bibliographical references (pages 36-39)Thesis (M.S.)--Department of Oral and Craniofacial Sciences. University of Missouri--Kansas City, 2023This study examined which demographic factors were associated with high levels of anxiety and depression in dental students and dental residents in a midwestern dental school. A twenty-four-item survey was distributed to 461 dental students and dental residents. The survey was divided into three domains including student and resident demographics, level of anxiety, and level of depression. Demographic factors were program of study, year of study, belonging to a high-risk group, marital status, parental status, physical activity, and social media usage. A high-risk group was defined as an individual who identified as African American, American Indian or Alaska Native, Asian, Hispanic or Latino, LGBTQ+, Native Hawaiian or Pacific Islander, or multiracial. The level of depression was measured utilizing the Patient Health Questionnaire 9 (PHQ-9), and level of anxiety was measured utilizing the General Anxiety Disorder 7 (GAD-7). To determine associations between demographic factors and levels of anxiety and depression Fisher’s Exact or Chi-squared tests were used. Only 12 respondents were dental residents and were excluded from further analyses due to insufficient statistical power. Survey data revealed no statistically significant association between level of anxiety or depression and year of study. Survey data revealed a statistically significant association of a low level of anxiety and greater than three days per week of physical activity. Additionally, survey data revealed a statistically significant association between a high level of depression and belonging to a high-risk group. Overall, results of this study suggest that some dental student demographics are associated with levels of anxiety and depression.Introduction -- Methods -- Results -- Discussion -- Conclusion

Stakeholder-driven development and implementation of CRICIT: an app to support high-quality data capture and protocol monitoring for outpatient clinical trials with vulnerable populations

Abstract Introduction:Choosing an appropriate electronic data capture system (EDC) is a critical decision for all randomized controlled trials (RCT). In this paper, we document our process for developing and implementing an EDC for a multisite RCT evaluating the efficacy and implementation of an enhanced primary care model for individuals with opioid use disorder who are returning to the community from incarceration. Methods:Informed by the Knowledge-to-Action conceptual framework and user-centered design principles, we used Claris Filemaker software to design and implement CRICIT, a novel EDC that could meet the varied needs of the many stakeholders involved in our study. Results:CRICIT was deployed in May 2021 and has been continuously iterated and adapted since. CRICIT’s features include extensive participant tracking capabilities, site-specific adaptability, integrated randomization protocols, and the ability to generate both site-specific and study-wide summary reports. Conclusions:CRICIT is highly customizable, adaptable, and secure. Its implementation has enhanced the quality of the study’s data, increased fidelity to a complicated research protocol, and reduced research staff’s administrative burden. CRICIT and similar systems have the potential to streamline research activities and contribute to the efficient collection and utilization of clinical research data

Investigating the User Experience of Electronic Data Capture Systems: Perspectives of Clinical Research Coordinators

The purpose of this study is to explore the user experiences (UX) of clinical research coordinators (CRCs) with electronic data capture (EDC) systems. Fifteen CRCs were recruited and participated in semi-structured interviews. Interview transcripts were coded and analyzed thematically. Themes were further contextualized within a theoretical framework comprised of the Technology Acceptance (TAM) Model, the Task-Technology-Fit (TTF) Model, and concepts from usability theory. Themes emerging from the data included EDC usability and task-technology-fit challenges, and identification of organizational and technological barriers towards EDC acceptance and performance. This study contributes to the literature by evaluating EDC systems from the perspective of a previously uninvestigated user group—CRCs—for the first time. Future work shall expand the results of this study by quantitatively evaluating EDC usability and informing the design of EDC systems.Master of Science in Information Scienc

Epidemiology in the time of COVID-19

My placement was with the Office of Health Protection and Response (OHPR) at the Australian Government Department of Health. During this time, I also had the opportunity to work at the Northern Territory Centre for Disease Control (CDC). The placements and experiences allowed me to apply the skills of the epidemiology of infectious diseases I acquired through the program. This thesis details projects undertaken at the field placements to fulfil the core requirements of the Master of Philosophy (Applied Epidemiology) program . The projects comprise a epidemiological study into in-flight transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on Australian repatriation flights from India into Darwin, a multi-jurisdictional outbreak investigation into COVID-19 among returned attendees of a wedding in Bali, Indonesia, the establishment of a surveillance network for COVID-19 outbreaks, and an analysis of the effect of the COVID-19 pandemic and public health interventions on salmonellosis in Australia during 2020. In this thesis, I also describe other public health experiences I gained during the MAE program, including my role in teaching, responsibilities as part of the epidemiology and surveillance team assisting the national COVID-19 response, and analysis of arboviral disease trends with a focus on Bamah Forest Virus infection

Timely and reliable evaluation of the effects of interventions: a framework for adaptive meta-analysis (FAME)

Most systematic reviews are retrospective and use aggregate data AD) from publications, meaning they can be unreliable, lag behind therapeutic developments and fail to influence ongoing or new trials. Commonly, the potential influence of unpublished or ongoing trials is overlooked when interpreting results, or determining the value of updating the meta-analysis or need to collect individual participant data (IPD). Therefore, we developed a Framework for Adaptive Metaanalysis (FAME) to determine prospectively the earliest opportunity for reliable AD meta-analysis. We illustrate FAME using two systematic reviews in men with metastatic (M1) and non-metastatic (M0)hormone-sensitive prostate cancer (HSPC)

Exploring the Impact of Service Learning on Interprofessional Collaborative Practices of Occupational Therapists

Previous research has demonstrated that students in healthcare related disciplines, who experience service learning, gain professional skills necessary for their career (Flinn, Kloos, Teaford, Clark, & Szucs, 2009; Holsapple, 2012; Seif et al., 2014). Research connecting service learning and career outcomes has primarily focused on short term perception of service learning benefit. Service learning may have a long lasting impact on career outcomes, especially for Occupational Therapists practicing in interdisciplinary healthcare teams. While previous research has suggested that service learning increases professional skills, little research has addressed the long lasting impact of service learning on interprofessional collaborative practice in healthcare teams. We aim to examine the impact of service learning on interprofessional collaborative practice (using the AITCS) (Orchard, King, Khalili, & Bezzina, 2012) in a sample of 379 licensed Occupational Therapists from the general population. Results indicate that service learning does have an impact on interprofessional collaborative practice, specifically related to core principles of team-based healthcare. Findings from this study suggest service learning could be an effective tool for interprofessional education, especially in the healthcare field

Enriching information extraction pipelines in clinical decision support systems

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01[Resumo] Os estudos sanitarios de múltiples centros son importantes para aumentar a repercusión dos resultados da investigación médica debido ao número de suxeitos que poden participar neles. Para simplificar a execución destes estudos, o proceso de intercambio de datos debería ser sinxelo, por exemplo, mediante o uso de bases de datos interoperables. Con todo, a consecución desta interoperabilidade segue sendo un tema de investigación en curso, sobre todo debido aos problemas de gobernanza e privacidade dos datos. Na primeira fase deste traballo, propoñemos varias metodoloxías para optimizar os procesos de estandarización das bases de datos sanitarias. Este traballo centrouse na estandarización de fontes de datos heteroxéneas nun esquema de datos estándar, concretamente o OMOP CDM, que foi desenvolvido e promovido pola comunidade OHDSI. Validamos a nosa proposta utilizando conxuntos de datos de pacientes con enfermidade de Alzheimer procedentes de distintas institucións. Na seguinte etapa, co obxectivo de enriquecer a información almacenada nas bases de datos de OMOP CDM, investigamos solucións para extraer conceptos clínicos de narrativas non estruturadas, utilizando técnicas de recuperación de información e de procesamento da linguaxe natural. A validación realizouse a través de conxuntos de datos proporcionados en desafíos científicos, concretamente no National NLP Clinical Challenges(n2c2). Na etapa final, propuxémonos simplificar a execución de protocolos de estudos provenientes de múltiples centros, propoñendo solucións novas para perfilar, publicar e facilitar o descubrimento de bases de datos. Algunhas das solucións desenvolvidas están a utilizarse actualmente en tres proxectos europeos destinados a crear redes federadas de bases de datos de saúde en toda Europa.[Resumen] Los estudios sanitarios de múltiples centros son importantes para aumentar la repercusión de los resultados de la investigación médica debido al número de sujetos que pueden participar en ellos. Para simplificar la ejecución de estos estudios, el proceso de intercambio de datos debería ser sencillo, por ejemplo, mediante el uso de bases de datos interoperables. Sin embargo, la consecución de esta interoperabilidad sigue siendo un tema de investigación en curso, sobre todo debido a los problemas de gobernanza y privacidad de los datos. En la primera fase de este trabajo, proponemos varias metodologías para optimizar los procesos de estandarización de las bases de datos sanitarias. Este trabajo se centró en la estandarización de fuentes de datos heterogéneas en un esquema de datos estándar, concretamente el OMOP CDM, que ha sido desarrollado y promovido por la comunidad OHDSI. Validamos nuestra propuesta utilizando conjuntos de datos de pacientes con enfermedad de Alzheimer procedentes de distintas instituciones. En la siguiente etapa, con el objetivo de enriquecer la información almacenada en las bases de datos de OMOP CDM, hemos investigado soluciones para extraer conceptos clínicos de narrativas no estructuradas, utilizando técnicas de recuperación de información y de procesamiento del lenguaje natural. La validación se realizó a través de conjuntos de datos proporcionados en desafíos científicos, concretamente en el National NLP Clinical Challenges (n2c2). En la etapa final, nos propusimos simplificar la ejecución de protocolos de estudios provenientes de múltiples centros, proponiendo soluciones novedosas para perfilar, publicar y facilitar el descubrimiento de bases de datos. Algunas de las soluciones desarrolladas se están utilizando actualmente en tres proyectos europeos destinados a crear redes federadas de bases de datos de salud en toda Europa.[Abstract] Multicentre health studies are important to increase the impact of medical research findings due to the number of subjects that they are able to engage. To simplify the execution of these studies, the data-sharing process should be effortless, for instance, through the use of interoperable databases. However, achieving this interoperability is still an ongoing research topic, namely due to data governance and privacy issues. In the first stage of this work, we propose several methodologies to optimise the harmonisation pipelines of health databases. This work was focused on harmonising heterogeneous data sources into a standard data schema, namely the OMOP CDM which has been developed and promoted by the OHDSI community. We validated our proposal using data sets of Alzheimer’s disease patients from distinct institutions. In the following stage, aiming to enrich the information stored in OMOP CDM databases, we have investigated solutions to extract clinical concepts from unstructured narratives, using information retrieval and natural language processing techniques. The validation was performed through datasets provided in scientific challenges, namely in the National NLP Clinical Challenges (n2c2). In the final stage, we aimed to simplify the protocol execution of multicentre studies, by proposing novel solutions for profiling, publishing and facilitating the discovery of databases. Some of the developed solutions are currently being used in three European projects aiming to create federated networks of health databases across Europe