2022 (Jan-Apr) | 2021 | 2020 | 2019 | 2018
Duke
Broadcast Link: Seminar
Abstract:
Dr. Haque will present preliminary results from an evaluation of eight frontier critical access hospitals (CAHs) in the midst of a CMS-funded demonstration program to provide cost-based reimbursement for providing access to telehealth services. Researchers reviewed applications and progress reports for the demonstration program and conducted in-person site visits. Barriers to implementation included the availability of distant providers, workflow challenges and provider acceptance. The main facilitator to implementation was external support, including additional funding and resources. Lessons learned from this study can be used to inform other telehealth implementations in rural settings.
Biosketch:
Saira N. Haque, PhD, MHSA, FAMIA is a senior health informaticist in RTI International’s eHealth, Quality and Analytics Division where she oversees the telehealth research portfolio. Dr. Haque has held many leadership roles in mixed-methods evaluations, policy analysis, case study development, and workflow analysis for clients such as the CDC, CMS, AHRQ, ONC, vendors and states. Her areas of interest are the use of technology to address behavioral health including substance use disorders, health information exchange, public and population health, and the intersection of technology and organizations. Her background includes a variety of consulting, research and operations positions for provider organizations and health plans. Dr. Haque holds a Master of Health Services Administration from the University of Michigan-Ann Arbor School of Public Health and a PhD in Information Science and Technology from Syracuse University.
UNC-CH
Broadcast Link: Seminar (Scroll to bottom and click play)
Abstract:
The burgeoning market of wearable devices (e.g., Fitbit, Garmin, Apple), used to measure physical activity, sleep, sedentary behaviors, and other health indicators, provides new opportunities for low-cost and scalable measurement of human behavior in a variety of settings. These sensor data support a range of uses, from guiding self-improvement, delivering patient-centric clinical care, tailoring public health interventions, reporting on population-level prevalence and trends, and offering a new avenue for public health surveillance.
To help illustrate the versatility of personal sensor data, three ongoing projects, sponsored by the National Institutes of Health (NIH), Department of Justice (DOJ), and Defense Advanced Research Projects Agency (DARPA), have been selected for review and discussion.
Biosketch:
Robert Furberg, PhD, MBA studies how emerging technologies, including smartphone apps and wearable devices, can be used to support clinical and public health interventions.
For over 15 years, Dr. Furberg has led interdisciplinary research and development teams at RTI implement and evaluate digital interventions for health promotion, primary and secondary disease prevention, and treatment adherence across a variety of patient populations. His current work explores how digital biomarkers can be used for both individualized assessment and public health surveillance.
In addition to his scientific responsibilities, Dr. Furberg serves on RTI’s Committee for the Protection of Human Subjects as an Institutional Review Board member. He is also a member of IEEE Standards Association Working Groups on Personal Data Privacy (P7002), Mobile Health Data (P1752), and the Consumer Technology Association’s Working Groups on Physical Activity and Stress Monitoring Data Standards.
UNC-C
Broadcast Link: Seminar
Abstract:
Randomized controlled trials (RCTs) are a ‘gold standard’ for estimating minimally unbiased treatment effects on health outcomes. However, RCTs are not always feasible and population-based observational studies may be more appropriate, particularly involving health analytics using big data. Assigning individuals at random between groups is not always feasible for ethical/practical concerns. Individuals ‘assign’ themselves to groups – e.g., studies about the impact of smoking cessation programs (SCPs) on blood pressure. Those who decide (not) to undertake such SCP intervention are self-selected, and biases/confounding factors (e.g., income, medical history, ethnicity, gender, age, education) may influence decisions (not) to attend SCPs, leading to potentially biased biostatistical inferences on this type of observational data. However, propensity score matching (PSM) reduces such study design biases.
PSM categorizes quantitatively individuals based on confounding factors associated with their decisions, so that samples of individuals ‘assigned’/matched to intervention(s) and control are similar/balanced across these factors. This transforms observational studies into pseudo-RCTs. For each person self-selected to the intervention, we ‘match’ M individuals with similar confounding characteristics who chose not to undertake the intervention. PSM relies on classification methods to ‘match’ individuals.
The Clinical Practice Research Datalink (CPRD) contains clinical and prescribing data for over 13 million patients in the United Kingdom; participating primary care practices are subject to regular audit to ensure data accuracy and completeness, allowing epidemiological studies of this data to be feasible. Since RCTs evaluating the impact of thiopurine treatment on Crohn’s disease patients is not practical, we used CPRD data to identify 5,640 patients with incident Crohn’s cases diagnosed over a 17-year period with at least an additional 5-year follow-up. Propensity score matching (PSM) is used to reduce bias, obtained in estimates of treatment effects as a result of confounding, between baseline factors and exposure group status. This presentation describes the PSM process, and applies optimal PSM, with a sensitivity analysis implementing additional matching techniques, using data collected from this nationally representative UK population-based study, where impact of duration and timing of thiopurine treatment on the likelihood of surgery is assessed using a Cox proportional hazards model and PSM.
Biosketch:
Dr. Laura H. Gunn received her PhD in Statistics and Decision Sciences from Duke University, during which time she also held a research training fellowship in Biostatistics with the National Institute of Environmental Health Sciences. Laura is currently Associate Professor of Public Health Sciences and Director of Health Analytics at University of North Carolina at Charlotte (UNCC), as well as Honorary Research Fellow at Imperial College London’s (ICL) School of Public Health (SPH) within the Faculty of Medicine. Prior to UNCC, Laura was Associate Professor of Public Health in Biostatistics, Department Chair of Health Sciences, and founding Program Director of Public Health at Stetson University, where she led the development of the undergraduate minor and major in Public Health, as well as co-developed undergraduate and graduate Data/Applied Analytics programs and received the University’s Community Partnership of the Year Award for establishing partnerships with Florida Hospital and Florida Department of Health. Additional prior positions include Associate Director of the Global eHealth Unit within ICL’s SPH. During this time, she also served as Lead Biostatistician for Research Design Service London at ICL. Laura was Biostatistics Director and Interim Associate Dean of Georgia Southern University’s Jiann-Ping Hsu College of Public Health (JPHCOPH), where she was among the founding faculty to develop masters and doctoral programs primarily in Biostatistics and Epidemiology within JPHCOPH and served on the core leadership team for Council on Education for Public Health (CEPH) accreditation. She received the JPHCOPH Faculty Awards of Excellence for Teaching & Mentoring, as well as for Service. Laura served a term on the U.S. Department of Health and Human Services’ Medicare Evidence Development and Coverage Advisory Committee; and, a sample of additional service roles includes: Treasurer for the American Statistical Association Georgia Chapter; Chair and Program Committee Chair of the Biopharmaceutical Applied Statistics Symposium; and reviewer for various statistics and health journals, as well as US and UK nationally-funded grants. Her research accounts for 45 peer-reviewed journal articles, book chapters and technical reports, as well as serving as a PI or co-I on funded external grants and contracts totaling over $6.5 million, including National Institutes of Health (US) and National Institute for Health Research (UK) grants. A sample of her publications includes such journals as PLoS ONE, American Journal of Gastroenterology, Annals of Family Medicine, British Journal of Dermatology, Pediatrics, Biostatistics, Biometrics, International Journal of Integrated Care, and Cochrane Database of Systematic Reviews; and, she has over 150 invited and contributed regional, national, and international presentations.
NCCU
Broadcast Link: Seminar
Abstract:
This seminar will focus on how model organisms, such as Drosophila melanogaster (fruit fly), are used to illuminate understanding of human health and human behavior in an emerging field known as ‘translational research’. The ultimate idea is that one can take what is discovered at the lab bench and bring it to the patient’s bedside. Though not a medical clinician, while in her lab at the wet-bench, Dr. Silver Key analyzes the alcohol-induced behavior of a living library of fruit flies known as the Drosophila Genetics Reference Panel (DGRP) with the aim of discovering novel genes involved in alcoholism. One unique gene that has an alcohol-resistance phenotype, discovered in the lab (independent of the DGRP project) is also important for ovarian cancer. Additionally, Dr. Silver Key’s lab, as part of the Genomics Education Partnership (GEP), annotates gene boundaries and regulatory elements using comparative genomics at the in silico bench. Both ‘translational research’ in general and present data on Dr. Silver Key’s current research will be introduced.
Biosketch:
Catherine Silver Key, PhD, completed her doctorate in Microbiology and Immunology at UNC-Chapel Hill. Subsequently, she taught at Elon University for 2.5 years as an adjunct visiting professor in the Biology Department and then spent 4 years as a Seeding Post-doctoral Innovators in Research and Education (SPIRE) at UNC-Chapel Hill. She is currently a tenured, associate professor of Biological & Biomedical Sciences at North Carolina Central University (NCCU). Her lab focuses on studying genes that effect development and behavior of the organism, Drosophila melanogaster (the fruit fly) and genomes of related Drosophila species using bioinformatics. She is currently supported by an NIH/NIGMS sub-award from Chapel Hill.
ECU
Broadcast Link: Seminar (Scroll to bottom and click play.)
Abstract:
In this webinar, Dr. Anne Dickerson will share her experiences and insights as she developed her research agenda over the last 20 years. She will share how her educational experiences assisted her in determining which questions to pursue for research. Through examples of her students and research agenda, strategies to select potential funders and maximize data gathered will be highlighted. Finally, collaboration with other researchers both within and outside her field will be discussed.
Biosketch:
Anne Dickerson, PhD, OTR/L, SCDCM, FAOTA is Professor in East Carolina University’s Department of Occupational Therapy and Director of the Research for the Older Adult Driver Initiative (ROADI). Dr. Dickerson is an international leader in occupational therapy research in areas of older adults, driver simulation, and drivers with autism spectrum disorder, and driver rehabilitation. She was awarded ECU’s 2018 Lifetime Achievement Award for Excellence in Research and Creative Activity. Dr. Dickerson is the PI for a funded grant from NHTSA to the state of North Carolina: A demonstration project promoting highway safety program guideline No. 13 and is a co-PI on a NHTSA project with the American Occupational Therapy Association.
Wake Forest
Broadcast Link: Seminar
Abstract:
The creation of statistical models for risk prediction has rapidly increased over the past 20 years as electronic health records (EHRs) and other electronic data have become ubiquitous in health care. Unfortunately, these tools have had minimal impact on clinical practice and patient outcomes. There are many reasons for the ineffectiveness of clinical decision support tools including: “alert-fatigue”, unsuccessful implementation of the tools into existing clinical workflows, clinician workloads, and lack of physician confidence in the tools. Many of these tools might have more impact if they were targeted at other members of the care team, including patients. Dr. Wells has proposed the use of “direct-to-patient alerts” and will give an example of an ongoing research project that will target high risk patients with text messages to suggest hemoglobin A1c (HbA1c) screening. He will describe the creation of a previously published HbA1c prediction tool being used to identify high risk patients as well as the research strategy for the upcoming project.
Biosketch:
Dr. Wells is an Associate Professor in the Department of Biostatistics and Data Science at the Wake Forest School of Medicine where he also serves as the Associate Program lead for the Biomedical Informatics Program in the Clinical and Translational Science Institute. He is board certified in both Family Medicine and Clinical informatics and has extensive experience in the extraction and analyses of EHR data both locally and for multicenter projects like the CDC funded SEARCH for Diabetes in Youth. Much of his research has focused on the creation of risk prediction models built from EHR data and the evaluation of outcomes in patients with diabetes. Dr. Wells is passionate about improving the creation and implementation of clinical decision support tools for better medical decision-making.
UNC-CH
Broadcast Link: Seminar
Abstract:
Over 45% of the 85.7 million US adults with hypertension have uncontrolled blood pressure resulting in increased risks of cardiovascular disease including stroke, heart failure, and myocardial infarction. Guidelines on hypertension management include lifestyle modification (e.g., diet, exercise) and medication initiation as first line treatment. To understand current hypertension treatment efforts and improve hypertension control, it is important to determine the frequency and inter-relatedness of lifestyle modification and hypertension medication initiation. However, lifestyle modification data is documented in narrative form within the electronic health record, making it “invisible” in evaluation of discrete data or metric measurement of hypertension treatment. Electronic health record data from 14,860 adult hypertension patients at an academic medical center were analyzed using natural language processing and statistical methods to determine documentation of lifestyle modification (i.e., advice and/or assessment) and hypertension medication initiation. Methods and results from this analysis will be discussed.
Biosketch:
Kimberly Shoenbill, MD, PhD is a physician and informatician at the University of North Carolina – Chapel Hill. She is an Assistant Professor working in the Department of Family Medicine and the Program on Health and Clinical Informatics. She received her MD and her PhD in Clinical Investigation with an emphasis in Informatics from the University of Wisconsin – Madison. She is dually board certified in Family Medicine and Clinical Informatics. Her research focuses on secondary use of electronic health record data using natural language processing and machine learning coupled with statistical analysis. She is committed to using informatics to evaluate, inform, and improve patient care delivery and outcomes.
Duke
Broadcast Link: Seminar
Abstract:
Linking data sources can help to enrich clinical researchers to more accurately define study populations, enable adjustment for confounding, and improve the capture of health outcomes. While there is much guidance about the technical process of linking data, there is less so about the pre study assessment of feasibility and the post study evaluation of the linkage results. When creating novel linked datasets, researchers must assess the feasibility of both scientific aspects (data quality and linkage methods) and operational aspects (access, data use and transfer, governance, and cost). Another key aspect of data linkage evaluation is to articulate how a linkage process was performed and its accuracy so that the potential for bias can be assessed. This presentation will review the results of a group effort to create guidance for the assessment of the feasibility of health data linkage for researchers, as well as recommendations for the evaluation and reporting of health data linkage. Examples of health data linkage from Dr. Raman’s work will be shared.
Biosketch:
Sudha Raman, PhD, is an Assistant Professor in the Department of Population Health Sciences. She is an epidemiologist who focuses on the use and effects of medications in populations (pharmaco-epidemiology), with careful consideration of a medicine’s benefits as well as harms. She received her PhD in epidemiology from the University of North Carolina at Chapel Hill and completed a fellowship at the Center for Pragmatic Health Systems Research at Duke Clinical Research Institute. Her current research explores the quality and methodological challenges of conducting research using real-world data, such as electronic medical records and administrative claims data, as applied to the evaluation of health care for both children and adults.
UNC-C
Broadcast Link: Seminar (Scroll to bottom and click play)
Abstract:
With the rapid increase in health-related data, we are seeing a revolution in both data sources and data analytics that can supplement and change traditional health care. My research focuses on utilizing our daily interaction on social media platforms to better understand health-related needs and concerns and then encourage positive behavior change at both the individual and population levels in the contexts of health. For this purpose, I process text communication from a highly popular social media platform, such as Reddit as well as a smaller but popular public online health communities like WebMD. In this talk, I share my research on (1) a process towards deriving health implications and identifying health-related changes from social media data and (2) a development towards behavioral change through data analytics.
Biosketch:
Albert Park, PhD is an Assistant Professor in the Department of Software and Information Systems within the College of Computing and Informatics at the University of North Carolina-Charlotte. His research focuses on understanding and addressing a variety of public and personal health problems by applying computational methods (e.g., Natural Language Processing, Machine Learning) to large datasets. He was a National Institutes of Health-National Library of Medicine Post-Doctoral Fellow at the University of Utah. He holds a bachelor’s and master’s degrees in Computer Science from Virginia Tech, and a Ph.D. in Biomedical and Health Informatics from the University of Washington.
NCCU
Broadcast Link: Seminar
Abstract:
Correction and republication provide a mechanism for identifying and updating non-maleficent but message distorting errors in biomedical literature. Inappropriate use of anomalous literature is spread by the citation of invalidated scholarly works. It is known that republished versions are cited more often than corrected versions of articles. The strength of invalidation correction and republication can be quantified. This presentation summarizes an analysis of 15,000+ citations to 548 articles indexed in PubMed. The bibliometric analysis described shows that corrected articles are cited about 51% less than controls. Thus, the practice of correction and republication leads to a reduction in the citation of flawed works that is fast-acting and long-lasting. Though it is not possible to quantify patient risk, the corrective effect is also visible when human subjects involved in secondary research are considered. Not only does correction reduce inappropriate citation, it also leads to reduced patient risk in later research.
Biosketch:
Dr. Gabriel Peterson, PhD, is an Associate Professor at the School of Library and Information Sciences at North Carolina Central University in Durham, NC. He holds bachelor’s degrees in Biochemistry (BS), Chemistry (BA), and Spanish (BA) from New Mexico State University, and an MS in Biotechnology from the University of Texas at San Antonio. He earned his Doctorate in Information Science from the University of Missouri in 2006. He joined North Carolina Central University School of Library and Information Sciences in 2007.
Dr. Peterson’s research interests pertain to the intersection of health sciences and biomedical literature and the Information Society. Health literacy and access to scientific and health information can improve lives by reducing health information disparities so it is important to understand how to make high-quality information accessible to those who can benefit most from it. One aspect of his research focuses on scholarly communication and the use of health information: He studies the self-correcting attributes of science. He is the author of the 2013 article, “Characteristics of retracted open access biomedical literature: a bibliographic analysis” and the 2019 brief communication, “The effectiveness of correction and republication as quality control in scholarly communications – a bibliometric analysis” in the Journal of the American Society of Information Science and Technology. His current research examines the impact of anomalous literature on human subjects and healthcare searching/seeking behaviors.
ECU
Broadcast Link: Seminar
Abstract:
The patient handoff was recognized by the Joint Commission (TJC) in 2006 as a national patient safety goal after it was identified as a leading cause of sentinel events. Communication breakdown resulting in patient care errors continue to be among the top leading cause of medical errors. Establishing a minimal data set between Emergency Department Nurses and Inpatient Nurses has proven to be a challenge due to communication differences, language barriers and finding a common tool. A Quality Improvement project to increase the nursing perception of the patient handoff is being established at a community hospital.
A new role that can help bridge the gap of implementation of research into the field of healthcare is the Doctorate of Nurse Practice (DNP). The DNP can be instrumental in implementing evidence-based practice into the clinical setting through mechanisms like quality improvement projects.
Biosketch:
Mary Jo Nimmo, MSN RN-BC has been in the field of Informatics for the past 20 years in multiple roles. After receiving her masters, she became the Director of Nursing Support at a community hospital. In that position she was responsible for computers in nursing and many other aspects of nursing support. She trained at the Juran Institute and worked in Process Redesign and then became the Director of Management Information Systems. In that role, she was responsible for all aspects of information systems at the community hospital. After 11 years , she did one year of consulting then joined UNC Health Care to implement their new software system. After seven implementations across the state, she is now the IT Director at a community hospital in Eastern North Carolina pursing her Doctorate in Nurse Practice in Leadership at East Carolina University.
Duke
Broadcast Link: Seminar (Audio only)
Abstract: (A story in 5 Acts)
As Electronic Health Record (EHR) systems mature, the opportunity exists to implement real-time clinical decision support tools. One area of focus has been the prediction of who will deteriorate while in the hospital. In 2015, the National Early Warning Score (NEWS), with an associated best practice alert, was implemented into the Duke University Health Systems EHR system. After the score had been used for over year, we were asked to evaluate its effectiveness (Act 1). With effectiveness found lacking, we were asked to develop a better score (Act 2). After developing a better score, we implemented our model and evaluated its performance prospectively (Act 3). This raised additional questions about how much better we could do if our prediction model was not constrained by the limitations of the implementation environment of the EHR system. In response, we have developed a time-to-event deep learning recurrent neural network (RNN) model (Act 4). As we built out and tried to refine our models, new questions were raised regarding how changing clinical measurements relate to risk of deterioration (Act 5). Ultimately, what started as a question of quality improvement, turned into a research investigation. This story illustrates how partnerships with the health system can lead (hopefully) to better patient care and spur academic research. This work is joint with a variety of faculty, students and staff who are statisticians, clinicians and informaticists.
Biosketch:
Ben Goldstein, MPH, PhD, is an Associate Professor of Biostatistics & Bioinformatics at Duke University, while also holding joint appointments with the Duke Clinical Research Institute and the Children’s Health & Discovery Initiative. His research interests are in the meaningful use of Electronic Health Records data. His work sits at the intersection of Biostatistics, Biomedical Informatics, Epidemiology and Machine Learning. Dr. Goldstein collaborates actively with both clinicians and fellow methodologists locally at Duke and nationally. He received his MPH and PhD in Biostatistics from the University of California at Berkeley.
Duke
Broadcast Link: Seminar
Abstract:
The promise of precision medicine in oncology is predicated on the availability of accurate, high quality data from the clinic and the laboratory. Likewise, a Learning Health System is one in which we use data to monitor that we are following guidelines and care pathways to deliver the best care and not revert to prior practices (regression testing for care!) and also provide real world evidence to determine effectiveness and identify populations that would benefit from novel therapies. Into this mix of clinical drivers are the rapidly changing capabilities in instrumentation, computing, data science, and the pervasive use of sensors and smart devices – many of which have health applications. A few of the opportunities will be highlighted in leveraging the increasingly digital landscape in healthcare and biomedical research as we move toward a learning health system for cancer.
Biosketch:
Warren A. Kibbe, PhD, FACMI is the chief for Translational Biomedical Informatics in the Department of Biostatistics and Bioinformatics, Chief Data Officer for the Duke Cancer Institute and Director of the Bioinformatics Core for the Clinical & Translational Sciences Institute (CTSI). He joined the Duke University School of Medicine in August of 2017 after serving as the acting Deputy Director of the National Cancer Institute (NCI) and Director of the NCI’s Center for Biomedical Informatics and Information Technology where he oversaw 60 federal employees and more than 600 contractors, and served as an acting Deputy Director for NCI. As an acting Deputy Director, Dr. Kibbe was involved in the myriad of activities that NCI oversees as a research organization, as a convening body for cancer research, and as a major funder of cancer research, funding nearly $4B US annually in cancer research throughout the United States.
UNC-CH
Broadcast Link: Seminar (Click play button on the bottom left)
Abstract:
Wearable Device Data Access – Attitudes, Barriers and Possible Solutions
The Global smart wearable device market is growing at a tremendous pace. For Healthcare providers, this means significant improvements in data accuracy, remote patient monitoring and convenience in provision of services. Access to the data collected through these devices can revolutionize dynamics in Medical Research. These devices are not only powerful resources for continually updating medical data from billions of individuals, but also allow the correlation of measured health parameters with other user demographic data.
Despite the promise of endless possibilities, there are some major barriers in accessing wearable device data. Many consumers are not willing to share their personal device data for a variety of reasons. A qualitative coding of consumers survey responses was done to explore and quantify major barriers in wearables data sharing. This discussion will include analysis of consumers attitudes that lead to their decline in sharing wearables data as well as recommendations and possible ways to address these concerns.
Biosketch:
Ayesha Aslam, MD is a Professional science Masters student in Biomedical and Health Informatics at UNC-Chapel Hill. Her work, as a digital Health intern at RTI included qualitative review of the survey data collected from wearable devices by consumers and devising recommendations to improve personal health data sharing by the consumers.
Dr. Aslam is ECFMG certified and has over 8 years of clinical experience working in both the public and private sectors in Pakistan. She aspires to contribute her expertise as a physician informaticist to improve healthcare and develop clinical decision tools for the providers to make the best informed decisions.
NCCU
Broadcast Link: Seminar (Click play button on the bottom left)
Abstract:
The North Carolina Native American Ethnobotany Project is 2-year research investigation of cultural and medicinal plants of significance to Indigenous communities in North Carolina. This lecture highlights several plants with a long history of medicinal use within these communities to fight infections and examines the scientific evidence to support their use by local communities.
Biosketch:
Tracie Locklear, PhD is a Research Assistant Professor at North Carolina Central University in the Department of Pharmaceutical Sciences. She is a translational scientist and experienced clinical researcher with a PhD in Pharmacognosy and a strong background in women’s health research. Her research evaluates the role of plant nutrients in human health and wellness. She works closely with communities interested in the reestablishment of healthy food traditions that support healthy living, and food security in rural communities without access to fresh produce.
UNC-Charlotte
Broadcast Link: Seminar
Abstract:
Twitter provides health researchers with the opportunity to collect health related information from an unstructured data source. Previous studies have demonstrated Twitter’s ability to collect information and monitor physical activity, dietary habits, and life satisfaction. Few studies have utilized a small-scale Twitter study to retrieve user-generated content regarding diabetes, diet, exercise, and obesity (DDEO) to characterize the topics associated with them. Using sentiment analysis and unsupervised topic modeling, the works presented will describe how these two computational approaches facilitate the analytical characterization of DDEO. Highlighted will be the knowledge health practitioners can gain from the computational approaches utilized and how we move from knowledge discovery to knowledge use.
Biosketch:
George Shaw, Jr., PhD is an Assistant Professor in the Department of Public Health Sciences at UNC Charlotte. He joined the department in August of 2018 after receiving his doctorate degree in Library and Information Science at the University of South Carolina. His current research focuses on the intersection of computational science and public health; he conducts computational text analysis on social media data to understand the connecting health topics of diet, diabetes, exercise, and obesity. Broadly, his research interests include text mining, machine learning, health literacy, information systems, and health information-seeking behaviors.
ECU
Broadcast Link: Seminar (Click play button on bottom left)
Abstract:
Organs, tissues and cells of the human body experience multi-directional and complex mechanical loads in their natural environment. Consequently, mechanical forces play an important role in pathogenesis of many connective tissue diseases and in the outcome of various surgeries. This talk will cover how
computational modeling and experimental techniques can be utilized to better understand the interaction of both native tissue and implants with their mechanical environment. Furthermore, examples will be presented from past and present research dealing with predictive modeling of connective tissue pathologies and surgical outcomes with the overarching goal of making various surgical techniques safer and more effective.
Biosketch:
Dr. Vahdati is an Assistant Professor in the Department of Engineering atEast Carolina University. His research is focused in the areas of multi-physics computational modeling and multi-scale biomechanical testing of natural and synthetic biomaterials for applications in precision medicine. He utilizes computer
modeling (virtual experiments) and experimental techniques to study the interaction of implants with native tissue, to predict the outcome of subject-specific surgical techniques and to prevent and diagnose mechanically-induced pathologies of soft and calcified tissues. Dr. Vahdati joined ECU after working for a Fortune 500 medical device company and the Cleveland Clinic, Ohio.
UNC-CH
Broadcast Link: Seminar (Click play button on bottom left)
Abstract:
Major healthcare challenges include information overload and accessibility to adequate care. In the EHR era, we face large, complex data that demand time-sensitive decisions by providers. The challenge of finding information in the EHR results in poor patient outcomes, provider dissatisfaction, and increased healthcare-related costs. By improving EHR interface designs, providers can navigate the EHR more efficiently and effectively. On the other hand, the growing demands for healthcare combined with shortage in providers create a difficulty in providing care, especially for patients in rural areas. Telemedicine, the interaction between providers and patients remotely through information technologies, provides a promising solution to improve access. This talk discusses the impact of innovative informatics methods to improve Provider-EHR relationship, and to improve health equity and bridge health disparities.
Biosketch:
With over a decade of experiences, Dr. Saif Khairat, PhD, FAMIA has lead national and international projects to enhance healthcare services and research, specifically within the informatics world. His research agenda comprises two main areas: (1) health IT usability and visualization, (2) telemedicine in health services research. He is site PI of the NIH funded project titled “Overcoming the Barriers to Clinical Trial Recruitment through Teleconsent”. Dr. Khairat was Co-Principal Investigator of the Great Plains Telehealth Resource and Assistance Center, funded by Health Resources and Services Administration (HRSA), a three-year federally funded center that is responsible for increasing Telehealth awareness and providing consultation to healthcare providers and vendors in six states.
Wake Forest
Broadcast Link: Seminar
Abstract:
The Decision Support Analytics Workgroup (DSAW) at Cinncinati Children’s Hospital Medical Center (CCHMC) was founded by Dr. Eric Kirkendall. The collaborative continues to investigate the links between the effectiveness of clinical decision support (CDS), patient safety, and user efficiency. Many of the research projects have also incorporated artificial intelligence techniques (e.g., natural language processing) and other innovative methods to detect adverse events/harm across multiple hospital environments. The results have shown vast improvements in detecting and mitigating errors compared to traditional methods. This seminar will focus on how Decision Support Analytics and Healthcare Innovation are utilized to solve problems such as data challenges and real-time safety event detection when being used as part of clinical decision support.
Biosketch:
Dr. Eric Kirkendall is a pediatrician that uses health information technology to maximize patient safety and quality in clinical care delivery, data management, and novel application/software development. He is the former Associate Chief Medical Information Officer in Cincinnati Children’s, overseeing the design, implementation, and optimization of the electronic health record and other associated technologies. Dr. Kirkendall was recruited to Wake Forest Baptist Health, to help lead NNGN™ (“engine”) – the Wake Forest Center for Healthcare Innovation. In that role Eric utilizes informatics tools and technologies to accomplish NNGN’s mission of rapidly translating innovation and discoveries into our clinical enterprise, promoting increased care quality, safety, and cost-effectiveness.
Duke
Broadcast Link: Seminar
Abstract:
Molecular Pathology and Digital Pathology represent two related disciplines of diagnostic medicine that are rapidly evolving due to advancement of technology. Data, infrastructure, and communication standards along with emerging interoperability initiatives serve to help accelerate creation of robust, scalable solutions for advancing patient care within healthcare organizations. This seminar will examine recently proposed models for information management covering both molecular data and tissue based imaging.
Biosketch:
Dr. Dash is a board-certified pathologist with fellowship training in Cytopathology and Informatics. He currently serves as the Beaker physician champion and Director for Laboratory Informatics Strategy, reporting to the office of the Chief Health Information Officer for Duke Health. He has an undergraduate degree in computer science and specializes in medical informatics, fine needle aspiration cytology and surgical pathology of breast cancer. Dr. Dash is involved in the research and development of medical terminologies and associated software tools for medical data mining and analysis. He is the principal author of Duke’s primary biorepository informatics platform managing samples and associated clinical data, called MAW3®, which has been in development since 1998, has served in a production environment since 2000. Dr. Dash is active on a number of national and international committees, including serving as a Co-Chair of the Integrating the Healthcare Enterprise (IHE) Pathology and Laboratory Medicine (PaLM) Domain, and serving the College of American Pathologists on their Informatics Committee, Information Technology Leadership Committee, CAP Foundation Board, and the Board of Governors.
UNC-C
Broadcast Link: Seminar
Abstract:
Electronic Health Record data is a fundamental to the development of learning healthcare systems, yet they present severe limitations for their reliable secondary analysis. Though clinical data often presents a high enough quality level for patient care and billing, their quality is often questioned for research applications. For example, clinical data are often found to contain inaccurate values, incomplete records, inaccessible information within clinical notes or just be recorded at an unusable level of granularity for specific analyses (e.g., yearly glucose level readings for research questions involving investigating daily changes). This seminar will describe some of these data quality limitations, introduce DataGauge: a practical process for systematically designing and implementing quality assessments of re-purposed clinical data, present data showing the impact of clinical workflows on the quality of clinical data sets and discuss the heterogeneity of such workflows that complicates the secondary use of clinical data.
Biosketch:
Franck Diaz, PhD is an Assistant Professor of Health Analytics and Informatics at the Department of Public Health Science in the College of Health and Human Sciences at University of North Carolina at Charlotte (UNCC). He joined UNCC in August of 2019 after completing a K-12 PRIME fellowship program for the National Institute for General Medical Science at Wake Forest School of Medicine and being part of WakeHealth’s Clinical and Translational Science Institute. His research focuses on developing methods for the reliable reuse of clinical data and carrying out secondary analyses to uncover modes of failure in clinical data sets. Dr. Diaz holds a PhD in Health Informatics from the University of Texas Health Science Center at Houston’s School of Biomedical informatics. He also holds a specialized Biomedical Engineering degree from Polytech’Marseille in France.
ECU
Broadcast Link: Seminar
Abstract:
Health communication professionals face numerous challenges in reaching marginalized and transient populations. Mobile technology, geofencing in particular, offers the potential to reach populations that are not easily accessible through traditional communication channels or social media. This seminar presents data from three separate studies that utilized geofencing and mobile display technology to reach these audiences. The first study applies the technology to beach safety along the North Carolina coast, the second to dental resource awareness in a population of Native Americans, and the third to mental health resources for migrant farm workers in Eastern North Carolina. Research design, results and technology pros and cons will be discussed.
Biosketch:
Dr. Mary Tucker-McLaughlin is an Associate Professor and the Undergraduate Coordinator for the ECU School of Communication. She holds a PhD in Mass Communication from the University of South Carolina. Her current research focuses on the use of technology in the dissemination of public health messages. She has served as an investigator on both internal and external grants including a Robert Wood Johnson grant for $250,000. Her research has been published in public health, health promotion, and mass communication journals. She is a former television news journalist and public relations professional who has also served as a consultant for both manufacturing and health organizations in Eastern North Carolina.
NCCU
Broadcast Link: Seminar
Abstract:
Sickle Cell Disease (SCD) is the most common genetic disorder of blood characterized by frequent & debilitating acute pain crises and chronic persistent pain. There is increased research interest on the interaction between biological, cognitive, and affective factors influencing onset, maintenance & resolution of chronic pains associated with SCD (Edwards et al., 2005). This talk will explore a promising treatment — Hydroxyurea (HU), fear of movement (kinesiophobia), and premenstrual syndrome (PMS) as they relate to our clinical and scientific understandings of this multifaceted disorder. How this all fits into the Bio-Psych-Social Model, and our wider understanding of disease and treatment will be discussed.
Biosketch:
John J. Sollers III, Ph.D, is an internationally known expert on heart rate variability (HRV) and health and has authored or co-authored over 80 peer-reviewed journal articles. He received his M.A. (1995) and Ph.D.(1997) in Experimental; Psychology from the University of Missouri-Columbia. Dr. Sollers was a Staff Scientist with the National Institute of Aging, NIH, an Asst. Research Professor at The Ohio State University, and Senior Lecturer (US equivalent of Tenured Associate Professor) at the University of Auckland Medical School (Auckland, New Zealand) before joining the faculty at NCCU.
Duke
Broadcast Link: Seminar
Abstract:
Pragmatic clinical trials frequently rely upon information collected for other purposes (e.g., patient reported outcomes, health records and medical claims). This presentation will review and evaluate the different data sources that are available for ascertaining death and hospitalization endpoints in clinical research studies. Typically, a single data source is insufficient for obtaining complete death and hospitalization information. This leads to the creation of hybrid data collection strategies. TRANSFORM-HF’s death and hospitalization endpoint identification and validation procedures will be reviewed as an example of how multiple data collection methods can be used to obtain more complete data coverage in a pragmatic clinical trial.
Biosketch:
Dr. Eisenstein’s primary research interest is the use of information technologies to simplify clinical trial operations and reduce research costs. This has included the evaluation of four population-based studies that used asynchronous decision support to improve care coordination for Medicaid patients. He is also involved with several efforts to evaluate the feasibility of eSource (direct data capture from site electronic health records to clinical trial databases). Currently, he is Data Coordinating Center Co-PI for the National Heart, Lung, and Blood Institute sponsored TRANSFORM-HF clinical trial. This 6000 patient heart failure pragmatic trial is using novel information technology strategies to simplify clinical trial design, improve operations and reduce costs.