Tag Archives: capstone

HOW DO CAPSTONE PROJECTS IN NURSING INFORMATICS CONTRIBUTE TO THE ADVANCEMENT OF HEALTHCARE DELIVERY

Leave a reply

Nursing informatics is a growing field that applies information and technology to support nursing practice, research and improve patient care. Capstone projects are a core requirement for many nursing informatics graduate programs, allowing students to demonstrate their mastery of concepts through the application of skills and knowledge to solve real-world healthcare problems. These projects make valuable contributions by developing tools and solutions that directly support the delivery of care.

One of the key ways capstone projects advance healthcare is by addressing gaps and inefficiencies identified in current clinical practice through the creation of new technologies and applications. For example, a recent project developed a mobile application to streamline admission, transfer and discharge processes between emergency departments and inpatient units. By automating paperwork and communication, it helped reduce delays and errors. Another project designed a clinical decision support tool integrated into the electronic health record to assist nurses in assessing risk factors and managing care for patients with heart failure. Projects like these save healthcare providers time so they can spend more of it on direct patient care activities.

Capstone work also enhances healthcare delivery by improving access to and coordination of care. One nursing informatics student created a telehealth platform allowing remote patient monitoring and video conferencing with providers. This benefited patients in rural areas with limited transportation options or specialty care locally available. Another project implemented an information system across diverse care settings – from hospitals to home health – facilitating the secure sharing of patient data between providers. Seamless data exchange supports continuity as patients transition between levels of care.

Many projects focus on leveraging technologies like artificial intelligence, machine learning and predictive analytics to augment clinical decision making. For example, one analyzed large datasets to develop models that can predict risk of hospital readmissions, pressure injuries or medication errors based on a variety of patient factors. Having these predictive tools available at the point of care empowers nurses to implement preventative interventions earlier. Other work applies similar techniques to radiology images, using automation to flag anomalies faster and improve diagnostic accuracy. As data volumes in healthcare continue climbing, these types of informatics solutions will grow increasingly valuable.

Privacy and security of protected health information are also top priorities addressed through capstone work. A variety of projects have centered around strengthening existing safeguards, implementing new access controls and authentication methods, or educating clinicians and patients on best practices. One developed an electronic system and mobile app for obtaining informed consent during research studies in full HIPAA compliance. Others conducted security risk assessments or created policies and guidelines around topics such as email encryption standards when exchanging files containing sensitive patient data. As threats to cybersecurity increase, these contributions play an important role in maintaining public trust in healthcare technologies.

Nursing informatics students additionally help advance care delivery through projects focused on user experience, usability and adoption of systems. Several analyzed clinician interactions with electronic health records, identifying inefficient workflows or areas for improvement. Recommendations from one such capstone helped optimize screen navigation and streamline documentation directly at the point of care. Another implemented a comprehensive training and support program to address barriers hindering full utilization of a new EHR system rollout. Proper end user training and ongoing support are essential for successful integration of technologies into clinical workflows.

Capstone projects can contribute through knowledge creation and dissemination. Some involve conducting systematic literature reviews on emerging topics, compiling best practices and developing evidence-based guidelines. These synthesis works help translate research findings into applicable recommendations that can guide the field. Other students pursue original nursing informatics research for their projects – such as evaluating new apps, prototypes or technologies through studies. Findings are then presented at conferences and published in scholarly journals, expanding the body of evidence and lessons learned to continually advance practice.

Nursing informatics capstone projects make invaluable contributions to healthcare delivery across diverse areas including clinical workflows, access to and coordination of care, predictive analytics and decision support, privacy/security, user experience, knowledge generation and more. Through creative applications of informatics principles and technologies, students directly address real problems impacting patients and providers. Their work helps optimize delivery systems, empower data-driven decisions at the point of care and integrate information management seamlessly into clinical practice – all advancing the overall outcomes, safety, efficiency and patient-centeredness of healthcare.

WHAT ARE SOME OTHER ROLES THAT ARE COMMONLY FOUND IN CAPSTONE PROJECTS

Leave a reply

Project Manager: The project manager is the lead person responsible for ensuring the successful completion of the capstone project. Their primary roles and responsibilities include:

Creating and maintaining a clear project plan and timeline that outlines all the key deliverables, milestones, resources required, budget if applicable, and project schedule. This involves breaking down the overall project into individual tasks with assigned start and end dates.

Effectively communicating the project plan and any updates to all stakeholders involved such as team members, faculty advisors, partners/clients etc. This involves holding regular status meetings to keep everyone informed and on track.

Managing the scope, budget, quality, human resources and overall change requests for the project. Part of this involves working with the team and stakeholders to finalize requirements and ensure expectations are managed throughout.

Assigning specific tasks and roles to team members based on their abilities and scheduling to ensure work is evenly distributed. This involves maintaining accountability and monitoring progress on all assignments.

Identifying and mitigating any potential risks that could jeopardize the successful completion of the project. Risk management requires continuous assessment and implementing of backup plans when needed.

Resolving conflicts or issues within the team or with outside stakeholders. As the team leader, the PM facilitates open communication and consensus building.

Preparing and presenting the final project results documentation and deliverables. This includes final reports, demonstrations, presentations that showcase if the project goals were achieved.

Collecting feedback and lessons learned to improve future project management capabilities. The PM leads a retrospective to evaluate what went well and identify process enhancements.

Faculty Advisor: The faculty advisor acts as a mentor and guide for the student capstone team. Their main duties include:

Helping the team properly define the overall project scope and goals based on learning outcomes and course requirements. This entails ensuring projects are sufficiently complex yet feasible.

Providing guidance on effective project management practices, problem solving approaches, research methods, documentation standards and overall quality expectations.

Assisting the team with sourcing appropriate resources, equipment or expertise needed that are beyond student capabilities. Connecting teams to industry mentors is also common.

Holding regular check-ins with the project manager to review status, address any challenges, and answer technical questions the team faces. Advisors offer an outside perspective.

Facilitating collaboration when conflicts arise and helping teams course correct when off track. Advisors draw on experience to get projects back on pace.

Reviewing and approving significant project deliverables and documentation like proposals, status reports, design specifications and final presentation materials.

Assessing the learning and skills gained throughout the process through evaluation of artifacts, presentations, and informal conversations. Advisors provide summative feedback.

Helping secure funding, facilities access, partners/participants when needed that require institutional permissions. Advisors leverage professional networks.

Celebrating accomplishments at completion and facilitating the transition of successful projects to be implemented in “the real world”.

Client Representative: When the capstone involves working with an external partner/client, one of their staff typically fulfills this role. Their duties include:

Providing important context on the target user/customer needs the project aims to satisfy through concrete requirements, constraints and goals.

Sharing organizational priorities and guidelines the project work should align with such as brand standards, policies, regulatory factors.

Offering subject matter expertise through knowledge sharing sessions and answering technical questions from the student team.

Regularly reviewing work-in-progress and deliverables to ensure the end solution will actually benefit the client and addressing any concerns early.

Facilitating access to necessary resources the client can provide like data, equipment use, facilities access that are fundamental to the project.

Promoting the student work within their own organization and championing for potential implementation if outcomes are deemed successful.

Judging the final results from an end-user viewpoint and providing perspective on real world feasibility, adoption challenges, and overall value to their operations.

Maintaining open client communication with both students and advisors throughout the process to manage expectations on scope, priorities and timelines.

This covers some of the extended details around common capstone project roles seen such as project manager, faculty advisor and client representative that often guide larger student teams towards successful completion of complex work. Let me know if any part of the answer requires further elaboration or clarification.

HOW ARE CAPSTONE PROJECTS EVALUATED AT UCF

Leave a reply

Capstone projects at UCF are meant to demonstrate a student’s mastery of the key concepts, skills, and knowledge learned throughout their undergraduate academic program. With that goal in mind, capstone projects undergo a rigorous evaluation process to ensure students are assessed in a comprehensive manner.

At the start of the capstone experience, students work closely with their capstone instructor and other faculty advisors to determine an appropriate project topic that aligns with their major and allows them to apply what they have studied. Topics can range widely depending on the discipline but all must be substantive enough to require integrating learning from multiple courses and demonstrating advanced skill levels. The topic selection is initially reviewed and approved by capstone instructors.

Once a topic is chosen, students develop a detailed project proposal outlining the goals, scope, methodology, timeline, and anticipated outcomes or deliverables of their planned work. Proposals are typically 5-10 pages and include elements such as an introduction and problem statement, literature review, proposed methods, intended results or product, and overview of how the project will be evaluated. These initial proposals are critically reviewed by capstone instructors and often other relevant experts. Feedback is provided to ensure the proposed work is properly focused, sufficiently ambitious in its goals yet realistic in its approach. Students may need to revise and resubmit proposals until receiving full approval to move forward.

With an approved proposal in hand, students then embark on executing the key aspects of their capstone project work over one or two semesters. Throughout this period, students meet regularly with their capstone instructor and other advisors for guidance, mentorship, and to track progress. Capstone faculty review draft deliverables, provide substantive feedback for improvement, and hold students accountable to their proposed timeline and standards of quality. Midway through, students often submit an interim report on accomplishments and any adjustments needed to their original proposal.

Toward the end of the capstone term, students submit a final comprehensive written report, portfolio, thesis, or other culminating product, adhering to prescribed formatting guidelines. The quality and rigor of these final deliverables are of paramount importance, as they serve as the primary basis for evaluation. Accompanying materials such as annotated bibliographies, datasets, code, prototype designs, marketing or outreach plans, etc. provide further evidence of the work and often factor into final grades.

Final capstone projects also typically include a public presentation or defense. This allows students to orally communicate about their work to a broader audience, including capstone instructors, other faculty members, student peers, and often community stakeholders or employers. Presentations are usually 15-25 minutes followed by a lengthy question and answer session where presenters must demonstrate expertise in both their project substance and ability to think on their feet.

The capstone evaluation process at UCF is intended to comprehensively judge student performance across multiple critera, including but not limited to:

Depth and quality of research, analysis, or other technical work conducted
Clear identification and importance of the research question/problem addressed
Appropriate selection and application of relevant conceptual frameworks/theories
Thoroughness and effectiveness of proposed and implemented methodsologies
Rigor of data collection, measurement, analysis techniques as applicable
Strength and validity of results, insights, conclusions reached
Clarity, organization, and quality of writing in the final report/deliverables
Effectiveness of oral presentation skills as demonstrated in defenses
Ability to handle questions that may challenge conclusions or point out limitations
Extent to which the work makes an important contribution to the relevant field
Demonstration of initiative, independence, and advanced skill mastery
Adherence to deadlines, formatting requirements, and other expectations

Capstone instructors and reviewing faculty utilize detailed rubrics to systematically evaluate student performance across these criteria when determining final grades. Rubrics include quantitative scoring of elements as well as opportunities for qualitative commentary. Scores on deliverables, presentations, and other factors such as peer/self evaluations are combined mathematically according to predetermined weightings. Students must meet minimum thresholds across criteria in order to pass. Those whose performance far exceeds expectations can earn A grades, while substandard work may result in no course credit.

The capstone evaluation process at UCF aims to provide a comprehensive, transparent and rigorous assessment of student achievement through significant applied works of independent scholarship. By design, the capstone experience cultivates advanced research, technical and soft skills while confirming whether undergraduates have gained the knowledge and abilities befitting degree conferral. The multi-stage process of proposal development, ongoing guidance, and summative evaluation through rubrics helps ensure this important learning outcome is realized for all students.

CAN YOU PROVIDE SOME EXAMPLES OF MACHINE LEARNING CAPSTONE PROJECTS THAT STUDENTS HAVE WORKED ON

Leave a reply

NLP sentiment analysis of restaurant reviews: In this project, a student analyzed a dataset of thousands of restaurant reviews to determine the sentiment (positive or negative) expressed in each review. They trained an NLP model like BERT to classify each review as expressing positive or negative sentiment based on the words used. This type of sentiment analysis has applications in determining customer satisfaction.

Predicting bike rentals using weather and calendar data: For this project, a student used historical bike rental data along with associated weather and calendar features (holidays, day of week, etc.) to build and evaluate several regression models for predicting the number of bike rentals on a given day. Features like temperature, precipitation and whether it was a weekday significantly improved the models’ ability to forecast demand. The models could help bike rental companies plan fleet sizes.

Predicting credit card fraud: Using a dataset of credit card transactions labeled as fraudulent or legitimate, a student developed and optimized machine learning classifiers like random forests and neural networks to identify transactions that have a high likelihood of being credit card fraud. Features included transaction amounts, locations, and other attributes. Financial institutions could deploy similar models to automatically flag potentially fraudulent transactions in real-time.

Predicting student performance: A student collected datasets containing student demographics, test scores, course grades and other academic performance indicators. Several classification and regression techniques were trained and evaluated on their ability to predict a student’s final grade in a course based on these factors. Factors like standardized test scores, number of absences and previous GPA significantly improved predictions. Such models could help identify students who may need additional support.

Diagnosing pneumonia from chest X-rays: In this project, a student analyzed a large dataset of chest X-ray images that were manually labeled by radiologists as either having signs of pneumonia or being healthy. Using techniques like convolutional neural networks, they developed models that could automatically analyze new chest X-rays and classify them as showing pneumonia or being normal with a high degree of accuracy. This type of diagnostic application using deep learning has real potential to help clinicians.

Predicting housing prices: A student collected data on properties sold in a city including features like number of bedrooms, bathrooms, lot size, age and neighborhood. They developed and compared regression models trained on this data to predict future housing sale prices based on property attributes. Factors like number of bathrooms and lot size significantly impacted prices. Real estate agents could use similar models to estimate prices when listing new homes.

Recommending movies on Netflix: Using Netflix’s anonymized movie rating dataset, a student built collaborative filtering models to predict rating scores for movies that a user has not yet seen based on their ratings history and the ratings from similar users. Evaluation metrics showed the models could reasonably recommend new movies a user might enjoy based on their past preferences and preferences of users with similar tastes. This type of recommendation system is at the core of how Netflix and other platforms suggest new content.

Predicting flight delays: For their project, a student assembled datasets containing flight records along with associated details like weather at origin/destination airports, aircraft type and airline. Several classification algorithms were developed and evaluated on their ability to predict whether a flight will be delayed based on these features. Factors like temperature inversions, crosswinds and aircraft type significantly impacted delays. Airlines could potentially use such models operationally to plan for and mitigate delays.

Predicting diabetes: Using medical datasets containing biometric/exam results of patients together with diagnoses of whether they had diabetes or not, a student developed and optimized machine learning classification models to identify undiagnosed diabetes cases based on these risk factor features. Features with the highest predictive value included BMI, glucose levels, blood pressure and family history of diabetes. Physicians could potentially deploy or consider similar models to help screen patients and supplement their clinical decision making.

As demonstrated through these examples, machine learning capstone projects provide students opportunities to work on real-world applications of their skills and knowledge. Some key benefits of these types of projects include: gaining hands-on experience applying machine learning techniques to solve problems, developing skill in data preparation, feature engineering, model development/evaluation and interpretation. They also help students demonstrate their abilities to potential employers or for further academic studies. Capstone projects are an ideal way for students to showcase what they’ve learned while working on meaningful problems.

WHAT ARE SOME EXAMPLES OF CROSS DISCIPLINARY CAPSTONE PROJECTS AT TEXAS A M UNIVERSITY

Leave a reply

Texas A&M University places a strong emphasis on cross-disciplinary capstone projects that allow students to integrate knowledge and skills from multiple fields to solve real-world problems. These types of projects provide invaluable experience for students as they prepare to enter a workforce that increasingly demands collaboration and innovative thinking.

One example of a large cross-disciplinary capstone project undertaken by Texas A&M students in recent years was developing accessible technology solutions for people with disabilities. A team of students from computer science, engineering, industrial distribution, and spatial sciences came together to design and prototype new assistive devices. They conducted user research, developed prototypes using 3D printing and other methods, and tested their solutions with people who have disabilities. The project addressed real needs and pushed the students to think beyond their individual disciplines.

Another notable project involved designing off-grid renewable energy solutions for rural communities in developing nations that lack access to traditional electricity infrastructure. Students from fields like mechanical engineering, construction science, agriculture, and geospatial science worked as an interdisciplinary team. They proposed customized energy systems combining solar, wind, biomass, and battery technologies that could provide power for vital community services like schools and medical clinics. Part of their work involved researching the technical specifications needed as well as evaluating socioeconomic and environmental sustainability factors.

Texas A&M students have also taken on ambitious global health challenges through cross-disciplinary collaboration. One capstone project brought together students from fields such as biomedical engineering, architecture, nutrition, and health promotion. They partnered with a non-profit organization helping rural communities in sub-Saharan Africa. The goal was to develop an integrated approach for addressing multiple health issues like waterborne diseases, malnutrition, and limited access to medical care. Their proposed solutions included designing inexpensive water filtration systems, educational programs on hygiene and nutrition, and preliminary plans for a multi-purpose health clinic. Getting input from local community members was also a key part of their work.

Yet another example of an impactful cross-disciplinary project involved developing flood prevention and response strategies for parts of India that regularly suffer damages from seasonal monsoon rains and river flooding. An international team of civil engineering, geoscience, hydrology, agricultural, and public policy students worked on this challenge. They created sophisticated hydrological and risk modeling to map flood-prone areas and help with evacuation planning. The group also proposed more permanent solutions such as improved drainage systems, flood walls, raising homes on stilts, and implementing agricultural best practices to reduce erosion during heavy rains. Coordinating with local governments was a significant aspect of validating their recommendations.

Staying within the state of Texas, one capstone brought together students from disciplines like construction science, landscape architecture, urban planning, and business administration. They partnered with the city of Bryan to develop a strategic revitalization plan for its downtown area aimed at improving economic, social and environmental sustainability. Proposals included renovating historic buildings, introducing mixed-use redevelopment projects, upgrading parks and public spaces, developing the arts district, enhancing walkability and bicycle infrastructure, recruiting targeted businesses and entrepreneurs, and capitalizing on events and cultural amenities to drive visitation to the area. Careful financial modeling and buy-in from key local stakeholder groups were crucial dimensions of the project.

Moving to a more technology-focused example, computer science and electrical engineering students teamed up with kinesiology and sports management majors on a project centered around developing new performance analytics and training tools for athletes. They designed smartphone apps, wearable sensors, and data visualization dashboards to help quantify physical metrics like speed, distances covered, jumps completed, heart rate variability, and more during games and practice. Machine learning algorithms were also applied to identify patterns and optimally target areas for improvement. Coaches and athletes testing the prototypes found them highly useful for gaining new data-driven insights into physical performance, injury prevention and developing personalized training regimens.

This covers just a sampling of the extensive cross-disciplinary work undertaken in capstone projects at Texas A&M University. As this overview illustrates, bringing together diverse areas of expertise to address complex challenges mirrors real-world problems that do not fall neatly into single disciplines. These collaborative experiences provide immense value in preparing Aggie graduates to be innovative leaders capable of driving meaningful change.