Hands-on workshops as an effective means of learning advanced technologies including genomics, proteomics and bioinformatics

Integrating Social Determinants of Health in Machine Learning-Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study

BACKGROUND

The use of both clinical factors and social determinants of health (SDoH) in referral decision-making for case management may improve optimal use of resources and reduce outcome disparities among patients with diabetes.

OBJECTIVE

This study proposes the development of a data-driven decision-support system incorporating interactions between clinical factors and SDoH into an algorithm for prioritizing who receives case management services. The paper presents a design for prediction validation and preimplementation assessment that uses a mixed methods approach to guide the implementation of the system.

METHODS

Our study setting is a large, tertiary care academic medical center in the Deep South of the United States, where SDoH contribute to disparities in diabetes-specific hospitalizations and emergency department (ED) visits. This project will develop an interpretable artificial intelligence model for a population with diabetes using SDoH and clinical data to identify which posthospitalization cases have a higher likelihood of subsequent ED use. The electronic health record data collected for the study include demographics, SDoH, comorbidities, hospitalization-related factors, laboratory test results, and medication use to predict posthospitalization ED visits. Subsequently, a mixed methods approach will be used to validate prediction outcomes and develop an implementation strategy from insights into patient outcomes from case managers, clinicians, and quality and patient safety experts.

RESULTS

As of December 2023, we had abstracted data on 174,871 inpatient encounters between January 2018 and September 2023, involving 89,355 unique inpatients meeting inclusion criteria. Both clinical and SDoH data items were included for these patient encounters. In total, 85% of the inpatient visits (N=148,640) will be used for training (learning from the data) and the remaining 26,231 inpatient visits will be used for mixed-methods validation (testing).

CONCLUSIONS

By integrating a critical suite of SDoH with clinical data related to diabetes, the proposed data-driven risk stratification model can enable individualized risk estimation and inform health professionals (eg, case managers) about the risk of patients' upcoming ED use. The prediction outcome could potentially automate case management referrals, helping to better prioritize services. By taking a mixed methods approach, we aim to align the model with the hospital's specific quality and patient safety considerations for the quality of patient care and the optimization of case management resource allocation.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56049.

Teaching mass spectrometry: A compilation of approaches to teaching theory and practice of mass spectrometry

The areas of mass spectrometry applications seem to be much larger than those of any other analytical techniques. They extend from the determination of molecular mass in organic chemistry, through the analytical applications in forensic, environmental and omics sciences, the application in extra-terrestrial exploration and many others. Mass spectrometry, usually coupled with chromatographic techniques, has also found wide application in the pharmaceutical industry, forensic laboratories, laboratories of sanitary inspection or environmental inspection, etc. The growing areas of applications give rise to the demand for the comprehensive mass spectrometry education of undergraduates. This overview covers the body of literature describing various interesting ideas that can be successfully used for teaching mass spectrometry. Since mass spectrometry is a multidisciplinary field, old but dynamically developing, teaching mass spectrometry may be more problematic in comparison to teaching other analytical techniques, for example, there is the problem of position of mass spectrometry in the chemistry curriculum. On the other hand, it is obvious that the mass spectrometry community, besides difficult scientific work, does great and admirable teaching work, in order to perfectly educate undergraduates in the field of mass spectrometry and to make learning mass spectrometry as attractive as possible.

A new pan-European Train-the-Trainer programme for bioinformatics: pilot results on feasibility, utility and sustainability of learning

Demand for training life scientists in bioinformatics methods, tools and resources and computational approaches is urgent and growing. To meet this demand, new trainers must be prepared with effective teaching practices for delivering short hands-on training sessions—a specific type of education that is not typically part of professional preparation of life scientists in many countries. A new Train-the-Trainer (TtT) programme was created by adapting existing models, using input from experienced trainers and experts in bioinformatics, and from educational and cognitive sciences. This programme was piloted across Europe from May 2016 to January 2017. Preparation included drafting the training materials, organizing sessions to pilot them and studying this paradigm for its potential to support the development and delivery of future bioinformatics training by participants. Seven pilot TtT sessions were carried out, and this manuscript describes the results of the pilot year. Lessons learned include (i) support is required for logistics, so that new instructors can focus on their teaching; (ii) institutions must provide incentives to include training opportunities for those who want/need to become new or better instructors; (iii) formal evaluation of the TtT materials is now a priority; (iv) a strategy is needed to recruit, train and certify new instructor trainers (faculty); and (v) future evaluations must assess utility. Additionally, defining a flexible but rigorous and reliable process of TtT ‘certification’ may incentivize participants and will be considered in future.

Blending Gagne's Instructional Model with Peyton's Approach to Design an Introductory Bioinformatics Lesson Plan for Medical Students: Proof-of-Concept Study

BACKGROUND

With the rapid integration of genetics into medicine, it has become evident that practicing physicians as well as medical students and clinical researchers need to be updated on the fundamentals of bioinformatics. To achieve this, the following gaps need to be addressed: a lack of defined learning objectives for "Bioinformatics for Medical Practitioner" courses, an absence of a structured lesson plan to disseminate the learning objectives, and no defined step-by-step strategy to teach the essentials of bioinformatics in the medical curriculum.

OBJECTIVE

The objective of this study was to address these gaps to design a streamlined pedagogical strategy for teaching basics of bioinformatics in the undergraduate medical curriculum.

METHODS

The established instructional design strategies employed in medical education-Gagne's 9 events of instruction-were followed with further contributions from Peyton's four-step approach to design a structured lesson plan in bioinformatics.

RESULTS

First, we defined the specifics of bioinformatics that a medical student or health care professional should be introduced to use this knowledge in a clinical context. Second, we designed a structured lesson plan using a blended approach from both Gagne's and Peyton's instructional models. Lastly, we delineated a step-by-step strategy employing free Web-based bioinformatics module, combining it with a clinical scenario of familial hypercholesterolemia to disseminate the defined specifics of bioinformatics. Implementation of Schon's reflective practice model indicated that the activity was stimulating for the students with favorable outcomes regarding their basic training in bioinformatics.

CONCLUSIONS

To the best of our knowledge, the present lesson plan is the first that outlines an effective dissemination strategy for integrating introductory bioinformatics into a medical curriculum. Further, the lesson plan blueprint can be used to develop similar skills in workshops, continuing professional development, or continuing medical education events to introduce bioinformatics to practicing physicians.

Meet-U: Educating through research immersion

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4–5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master’s students in bioinformatics and modeling, with protein–protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.

Bioinformatic training needs at a health sciences campus

Background

Health sciences research is increasingly focusing on big data applications, such as genomic technologies and precision medicine, to address key issues in human health. These approaches rely on biological data repositories and bioinformatic analyses, both of which are growing rapidly in size and scope. Libraries play a key role in supporting researchers in navigating these and other information resources.

Methods

With the goal of supporting bioinformatics research in the health sciences, the University of Arizona Health Sciences Library established a Bioinformation program. To shape the support provided by the library, I developed and administered a needs assessment survey to the University of Arizona Health Sciences campus in Tucson, Arizona. The survey was designed to identify the training topics of interest to health sciences researchers and the preferred modes of training.

Results

Survey respondents expressed an interest in a broad array of potential training topics, including "traditional" information seeking as well as interest in analytical training. Of particular interest were training in transcriptomic tools and the use of databases linking genotypes and phenotypes. Staff were most interested in bioinformatics training topics, while faculty were the least interested. Hands-on workshops were significantly preferred over any other mode of training. The University of Arizona Health Sciences Library is meeting those needs through internal programming and external partnerships.

Conclusion

The results of the survey demonstrate a keen interest in a variety of bioinformatic resources; the challenge to the library is how to address those training needs. The mode of support depends largely on library staff expertise in the numerous subject-specific databases and tools. Librarian-led bioinformatic training sessions provide opportunities for engagement with researchers at multiple points of the research life cycle. When training needs exceed library capacity, partnering with intramural and extramural units will be crucial in library support of health sciences bioinformatic research.

Frontiers in Reproduction (FIR): An Assessment of Success

The Frontiers in Reproduction (FIR) course has been held annually since 1998 at the Marine Biological Laboratories in Woods Hole, MA. The primary purpose of the course is to train young reproductive biologists in cutting-edge techniques that would strengthen their career opportunities. An initial evaluation of the FIR course was conducted by surveying the participants who took the course between 1998 and 2002. The findings of this survey were published in Biology of Reproduction in 2006, which highlighted the overall positive impact the course had on the training and upward career trajectory of the participants during the first 5 yr. The current study was designed to access the continued impact of FIR at the 10-yr mark by evaluating the participants who took the course between 1998 and 2008 using two different survey mechanisms. Based on these evaluations and feedback from the participants, it was evident that 1) FIR continues to have a significant positive impact on the careers of the participants, 2) the majority of the participants continue to be involved in research or administration related to the reproductive sciences, 3) nearly 90% of the attendees have been successful in obtaining funding for their research, and 4) most alumni have published at least five manuscripts in higher impact journals since they took the course. Therefore, it is evident that FIR participants are highly successful and continue to significantly impact the advances in the reproductive sciences worldwide.

Using mobile sequencers in an academic classroom

The advent of mobile DNA sequencers has made it possible to generate DNA sequencing data outside of laboratories and genome centers. Here, we report our experience of using the MinION, a mobile sequencer, in a 13-week academic course for undergraduate and graduate students. The course consisted of theoretical sessions that presented fundamental topics in genomics and several applied hackathon sessions. In these hackathons, the students used MinION sequencers to generate and analyze their own data and gain hands-on experience in the topics discussed in the theoretical classes. The manuscript describes the structure of our class, the educational material, and the lessons we learned in the process. We hope that the knowledge and material presented here will provide the community with useful tools to help educate future generations of genome scientists.

DOI:http://dx.doi.org/10.7554/eLife.14258.001

A survey of scholarly literature describing the field of bioinformatics education and bioinformatics educational research

Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students' attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education.