ANIA 2026 Annual Conference

P01 - Health Care’s Parallel Reality: Digital Twin Environments for Clinical Innovation

Emily Ayre, MS | Jessica Serrao, MS

Updated: 03/05/26

Digital twin environments, particularly in the form of virtual hospitals or biological systems, are emerging as a transformative force in healthcare innovation. This system replicates the structure and function of actual hospital units, including rooms, patient populations, and the flow of health data from connected medical devices. By creating these data-driven replicas of physical healthcare systems, digital twins allow us to obtain knowledge and understanding without disrupting clinical operations.
Our work centers on the development of a comprehensive virtual hospital environment using a cloud-based digital twin platform. Health level seven (HL7) data feeds are integrated to mirror real-time operations and provide a dynamic simulation environment that reflects the complexity of clinical settings.
We will present how our group has successfully implemented a digital twin environment designed to support healthcare research, clinical workflow modeling, and technology evaluation. This environment enables controlled experimentation, allowing clinicians to utilize informatics to evaluate “what-if” scenarios, measure key performance indicators, and validate the impact of proposed changes before they are implemented in live settings.
We will share case examples demonstrating how the digital twin has supported research initiatives, improved system reliability, and enhanced preparedness through high-fidelity simulation. This will support the intended learning outcome of illustrating how this approach offers a safe, scalable, and evidence-based method to refine care delivery and ensure clinical excellence.
In summary, our digital twins-based virtual hospital environment offers a robust and scalable solution for healthcare simulation, system validation, and retrospective research. It represents a significant advancement in how clinical technology can be tested, refined, and optimized—safely and efficiently—before ever reaching the bedside.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P02 - Improving Social Drivers of Health Screening in an Inpatient Setting for SDOH Data

John Lussier, DNP, FHIMSS, RN, NI-BC, Director of Clinical Informatics, Sharp HealthCare

Updated: 03/24/26

Purpose: This evidence-based practice project aimed to increase social drivers of health (SDoH) screening compliance by redesigning the workflow to distribute responsibility between nursing and case management, ultimately improving identification and referral of patients with supportive service needs.
Background: Screening for SDoH needs facilitates provision of appropriate supportive services. The existing workflow required nurses to conduct initial screening in five domains (housing stability, utility difficulties, food insecurity, interpersonal safety, and transportation needs), with positive responses triggering additional investigative questions. These follow-up questions created discomfort for both patients and nurses, leading to deferred or incomplete screenings. In 2024, the Centers for Medicaid and Medicare Services (CMS) began linking inpatient prospective payment system (IPPS) reimbursement to SDoH screening compliance, further emphasizing the importance of improvement.
Methods: The Advancing Research and Clinical Practice through Close Collaboration (ARCC) evidence-based practice model guided implementation. Following a literature review conducted from July 2024 to March 2025, a workflow redesign was implemented that limited nursing responsibility to initial screening questions while shifting follow-up assessment to case management. Implementation occurred at a Southern California hospital with adult inpatients. Data on screening completion rates and subsequent referrals were collected.
Results: Reducing the number of questions asked by the nursing care team on patient intake from 12 to 5 increased the rate of screening. Positive screenings, indicating a need, also had increased follow-up by case management.
Pre-implementation screening rates averaged around 50%. The workflow redesign yielded a significant increase in SDoH screening completion rates from an average for all hospitals of 58% to 62% in a two-month period, with some individual hospitals showing a 25% to 35% increase by the end of the evaluation period. Additionally, follow-up assessments for patients with positive screenings improved resulting in more patients receiving appropriate resource referrals before discharge.
Evaluation: The redistribution of screening responsibilities between nursing and case management proved effective in increasing both initial screenings and follow-up assessments. This collaborative approach enhanced the identification of patient needs and facilitated timely connection to resources. Findings suggest that interprofessional collaboration can improve SDoH screening processes and ultimately enhance health equity.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P03 - Flowsheet Macros in Electronic Health Records: A Strategy for Enhancing Nursing Documentation Efficiency

Raelle Carlino-Filippone, MSN, BS, RN, CMSRN

Updated: 03/05/26

Background: Nursing documentation is vital for patient care, legal compliance, and workflow efficiency, yet it can take up to 50% of a nurse’s shift. Increased EHR demands from technology and regulations have added to nurse workload, stress, and reduced patient interaction. This project aimed to improve documentation efficiency by implementing flowsheet macros—customizable templates in the EHR system—to streamline routine charting. Focused on inpatient nurses in medical-surgical, telemetry, PCU, and ICU units at a South Jersey healthcare organization, the initiative sought to reduce documentation burden, improve nurse well-being, and increase time for direct patient care.
Purpose: This project evaluated whether implementing flowsheet macros in the EHR improves nursing documentation efficiency, accuracy, and standardization, while reducing burnout and increasing time for direct patient care. Inefficient documentation often leads to excessive non-clinical tasks, less patient interaction, and increased cognitive load. While physician EHR use is well-studied, nursing documentation remains underexplored. Research shows documentation burdens contribute to burnout but tailored electronic tools and proper training can improve efficiency, nurse well-being, and patient outcomes. This project addressed these issues by implementing flowsheet macros in the EPIC EHR to streamline workflows, ensure consistent data entry, and support patient-centered care.
Framework: Flowsheet macros in the EHR use user-centered design and clinical decision support to align with nursing workflows, streamlining repetitive tasks, reducing cognitive load, and enabling faster, accurate documentation aligned with best practices.
Methods: The project involved the design and implementation of a customized system of flowsheet macros within the EHR platform to streamline nursing documentation by automating frequent and repetitive charting tasks. Developed in close collaboration with front-line nurses, the macros were tailored to align with real-world workflows, reduce redundancy, enhance data consistency, and significantly decrease the time spent on routine documentation.
Results: Initial results from the first three months post-go-live indicate an increased use of flowsheet macros among inpatient nurses following the implementation of the new documentation system. Feedback from nurses highlights a reduction in time spent on non-clinical tasks, allowing for more direct patient care. These post-implementation findings align with existing literature on the positive impact of effective documentation tools on nursing practice. The significant increase in both system-wide and personalized macro usage suggests improved adoption of standardized documentation practices, contributing to greater workflow efficiency and consistency in data entry. These results support the conclusion that well-designed and properly implemented documentation tools can enhance nursing efficiency and improve the quality of care delivery. (Results data will be more up to date at time of presentation).
Conclusion: This project demonstrated the potential of flowsheet macros within the EHR system to enhance nursing documentation efficiency, reduce burnout, and increase the time available for direct patient care. The results underscore the practical value of thoughtfully integrated health IT solutions in streamlining clinical workflows and improving care quality. Next steps include analyzing pre- and post-intervention data to evaluate impact, refining the macros based on user feedback, and exploring opportunities to expand the intervention to additional departments or healthcare facilities.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P04 - Addressing Nursing Burnout through Informatics Engagement

Mary Keckeisen, MS, BSN, RN, CCRN, CAHIMS

Updated: 03/02/26

Updated: 03/04/26

Purpose: Nursing burnout is a multifaceted challenge in health care, driven not only by emotional demands but also by administrative burden, unrealistic workloads, time constraints, and a lack of autonomy. While many articles focus on stress relief and wellness at the unit level, few address how informatics can support nurses in reducing burnout. At a large academic medical center, the clinical informatics (CI) department has implemented a model that promotes nurse autonomy and engagement through active participation in informatics decisions.
Description: The CI team has created multiple pathways for bedside staff to contribute to informatics-related improvements. This includes formal committee participation, direct feedback channels, and relationship-building efforts. Nurses can present ideas to the super user committee or the clinical EHR optimization committee (CEOC), both of which reserve time for front-line staff to raise concerns. Additionally, the CEOC inbox allows nurses to email suggestions or EHR requests, which CI staff route to the appropriate committee, such as CEOC or SMUG (surgical medical user group).
Beyond structured meetings, CI staff routinely round throughout the hospital, engaging directly with clinical teams. These rounds are designed to foster trust and visibility, with CI staff encouraged to learn names, ask about workflow challenges, and maintain an “open door” policy. This accessibility helps nurses feel heard and supported, reinforcing a culture of collaboration.
Participation also extends to testing new builds and providing feedback on informatics products. By involving nurses in the development and refinement of tools they use daily, CI staff promote a sense of ownership and relevance in the informatics process.
Evaluation/outcome: Feedback from bedside nurses has highlighted themes of empowerment, autonomy, and improved morale. One nurse shared that participating in CI committees helped her understand the rationale behind workflow changes, which reduced her feelings of burnout. Another nurse noted that sharing informatics updates with her unit led to increased recognition from peers and boosted her confidence, making work more enjoyable.
These outcomes suggest that involving nurses in informatics decisions can positively impact their sense of agency and reduce burnout. By creating accessible channels for input and fostering strong relationships between CI staff and clinicians, this facility's model demonstrates a feasible and impactful strategy for improving nurse well-being. Empowering nurses to shape the systems they use daily not only enhances engagement but also contributes to a more resilient and responsive healthcare environment.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P05 - Applying Lean Six Sigma Methodology to Reduce Documentation Burden and Elevate Student Experience

Kimberly Taylor, DNP, RN, NEA-BC, CNOR, CLSSBB

Updated: 03/05/26

Learning objective: By the end of this session, participants will be able to identify how an informatics-driven Lean Six Sigma (LSS) initiative reduced the clinical documentation burden and enhanced the experience of healthcare leadership graduate students.
Purpose: Utilizing a LSS approach, the primary objective was to reduce the clinical documentation burden, optimize efficiencies, and streamline the clinical documentation process to enhance students’ satisfaction with their learning experience. The secondary objective was to simplify the process for validating the completion of clinical hours for faculty.
Description: Course evaluations and verbal student feedback indicated negative experiences with the documentation process and time for clinical courses. Students spent an average of 150 minutes/weekly on clinical documentation and utilized three distinct methods to complete it. A recently adopted electronic clinical documentation system had been launched, presenting an opportunity to streamline student documentation. However, the electronic system was not being optimized and created additional learning challenges for students. Applying the LSS methodology through Define, measure, analyze, improve, and control (DMAIC), the documentation processes were analyzed to identify redundancies, documentation burden, and cycle time. The define component of this structured approach to improvement included a value stream analysis, a project charter, and the identification of the primary metric, focused on documentation time per week in minutes. The measures incorporated a spaghetti chart, 5 whys, Gemba from the student perspective, tracking documentation time, gathering qualitative data, and reviewing all items used to document. During the improve stage, non-value-added steps were removed, the documentation template was standardized, and training was provided to students on best practices. To ensure ongoing control, a student policy was created, weekly documentation continued to be tracked, monthly reviews of the process were conducted, and quarterly student meetings for feedback were scheduled.
Outcome: This transactional effect cycle time reduction project successfully eliminated six steps from the clinical documentation process, thereby streamlining the workflow. This reduction in steps contributed to a 50% decrease in documentation time, significantly bringing it closer to the target of 60 minutes per week. In addition to the time savings, the optimization of the electronic documentation system enhanced efficiencies, reduced unnecessary complexities, and improved the user experience. Students reported a more positive experience with the process, leading to increased satisfaction with their clinical documentation requirements.
These improvements directly support the program's goal of maintaining quality while simultaneously enhancing the student learning experience. These courses have been taught three times since the improvements were initiated and continue to receive positive feedback. Likewise, the faculty experience has been enhanced, and communication with students has been strengthened.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P06 - Designing for Better Outcomes: EHR Solutions for Geriatric Surgery Verification

Kelly Colacino, MSN, RN, PCCN, CCRN | Erica Zippo, MS, RN, NI-BC, CPHIMS

Updated: 03/05/26

Purpose: Our organization began the journey to become a geriatric surgery verification (GSV) comprehensive excellence hospital in 2022. The American College of Surgeons developed the GSV program to provide evidence-based standards that guide the care of older adults undergoing surgery. The GSV program standards span multiple domains from leadership to comprehensive management plans. An assessment of program requirements revealed the need for an extensive and interdisciplinary EHR design to support clinician workflows and data review.
Description: A project was initiated and stakeholders were identified, including EHR and business intelligence analysts, informatics, IT project management, clinical subject matter experts from the operational multidisciplinary team, and quality. We utilized the GSV program standards to identify documentation requirements and establish priorities. The multidisciplinary team met two to four times per month over a six-month period to review and develop the needs of the program. The EHR project team similarly met weekly to interpret the needs into an overall design strategy. The design strategy was guided by usability heuristics and iterative feedback from end users to enhance user experience. A GSV patient registry was created for overall patient tracking. Tools created to support documentation efficiency included a GSV navigator and flowsheet for the screening and assessment documentation and advisories to automate appropriate care plans. A mix of practice advisories, orders, and tasks were used to provide clinician support in meeting program requirements. A GSV banner was created, visible to anyone who opens the chart, to identify GSV patients and the GSV patient lists display the vulnerability screenings statuses and are used during interdisciplinary rounds. System smart phrases and order sets standardize provider and nursing documentation. Finally, reports were built for data tracking and reporting.
Evaluation/outcome: We successfully implemented our GSV EHR build in 2023 and saw a 78% increase in overall documentation compliance. This contributed to our success in becoming a GSV comprehensive excellence hospital in early 2025. EHR advisories designed to support automatic care plans have saved 91,000 clicks for nursing in the last six months and ensure patients have plans of care supporting their unique age-related needs. The EHR project took close to a year to complete, but the finished product allowed us to accurately document the necessary items for our GSV program and provided us with an easy way to track GSV patients before, during, and after surgery to better monitor their progress.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P07 - Leveraging Generative AI into Introductory Informatics Education: Designing Hands-On Programing Experiences

Anfel Crews, DNP, APRN, FNP-BC, NI-BC

Updated: 03/05/26

Introduction/background: The growth of generative artificial intelligence (AI) tools such as ChatGPT offers new opportunities to enhance digital literacy, programming capability, and critical thinking within nursing and health informatics education. Nursing students often struggle to see the relevance of programming within the clinical informatics context. Educators require innovative strategies that integrate pedagogy, content, and technology to engage learners effectively. AI tools such as ChatGPT enable the design of meaningful, context-specific learning activities that strengthen informatics competencies.
Purpose: To demonstrate how ChatGPT can be used to design a Python programming assignment aligned with nursing informatics competencies, guided by the technological pedagogical content knowledge (TPACK) framework.
Methods: Using TPACK principles, a Python-based assignment titled health data tracker was developed with ChatGPT to teach basic programming concepts while applying them to health data management. Students used Replit, a browser-based platform, to write and execute code with no installation required. The assignment aligns with the AACN Essentials (2021) domain 8.3, which emphasizes decision-making in technology selection, implementation, and evaluation of impact on quality and safety, as well as the ANA Nursing Informatics Scope and Standards of Practice (2022) competency related to system design and evaluation.
Results/impact: Nearly half of students described the programming assignment as enjoyable and meaningful. The assignment reduced faculty workload through AI-assisted design. The process demonstrated scalability for other informatics topics, such as EHR simulation and data visualization.
Conclusion: AI tools such as ChatGPT, guided by the TPACK framework, can enhance nursing informatics education by fostering programming skills, computational thinking, and engagement with technology-driven learning.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P08 - Virtual Nursing Integration: An Informatics Approach to Workforce Optimization and Patient Engagement

Juliana Hernandez, MSN, RN, OCN

Updated: 03/05/26

The American Nurses Association (2025) defines virtual nursing as the use of remote technology to deliver safe, high-quality care through the nursing process emphasizing communication, compassion, and collaboration across all stages of care. Memorial Sloan Kettering Cancer Center (MSKCC) characterizes virtual nursing as the integration of remotely located expert registered nurses (RNs) into acute care settings through technology. This innovative approach enabled the organization to identify workforce optimization opportunities by supporting bedside nurses and patients with non-direct care tasks. Virtual nurses at MSK provided patient education, completed nursing assessments, coordinated care, and offered RN mentorship.
The eight-week pilot was implemented on an inpatient medical-surgical unit to enhance staff support, improve patient education, and identify sustainable technology-enabled workflows. The nursing informatics team led the design, implementation, and optimization of supporting technology using the systems development life cycle (SDLC) framework. A budget-neutral approach guided evaluation of available tools—teleconferencing platforms, clinical documentation systems, and communication devices. Cisco Jabber was selected as the teleconferencing solution for its secure, reliable functionality and alignment with the organization’s telemedicine infrastructure. Workstations on wheels (WOWs) were upgraded with cameras, microphones, and speakers to enable video encounters, and designated carts were configured for exclusive pilot use.
Workflow analysis identified gaps in communication and documentation processes. To address these, the team implemented secure text messaging for equipment coordination and availability updates. A critical barrier emerged in the electronic health record (EHR): only one nurse could document and sign the initial nursing assessment (INA). Nursing informatics collaborated with the CIS clin doc team to create a custom INA that allowed shared documentation, color-coded role delineation, dual electronic signatures, and the ability to save progress as “incomplete” for continued collaboration. This improvement enhanced role clarity and staff engagement, strengthening buy-in and driving interest in expanding the pilot.
Dedicated virtual nursing workspaces were established within the administrative suite, equipped with dual monitors, headsets, webcams, telephones, and Vocera devices to ensure secure connectivity. Daily huddles reviewed issue lists and workflow challenges, while informatics-led check-ins promoted transparency, responsiveness, and continuous improvement throughout the pilot.
Impact evaluation focused on productivity, staff satisfaction, and patient experience. Virtual nurses completed 254 video encounters over eight weeks, saving bedside nurses 109 hours and 20 minutes. Patient teaching accounted for the majority of activities, emphasizing the role’s contribution to education and workload relief. Staff satisfaction was reflected in improved engagement and reduced overtime, while patient feedback demonstrated high satisfaction with virtual communication and support.
This initiative highlights how informatics-driven design can operationalize virtual nursing to enhance clinical efficiency, optimize technology, and elevate patient-centered care.
Learning outcome: Participants will be able to identify informatics-led strategies to design, implement, and evaluate virtual nursing workflows that enhance collaboration, efficiency, and patient experience.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P09 - National Collaborative Leadership to Advance Clinical AI Governance and Workforce Competency: A Joint Role for ANIA and CHIME

Katherine Taylor Pearson, DNP, RN, NI-BC, CLSBB, CPHIMS, CKM, Assistant Professor, Texas Tech University Health Science Center | Nicole Kerkenbush, MHA, MN, BSN, RN, CDH-E, CENP

Updated: 03/17/26

Artificial intelligence (AI) adoption continues to accelerate across health care, influencing clinical decision support, documentation automation, predictive deterioration modeling, cybersecurity threat detection, capacity management, and population health surveillance. While AI innovation is rapidly advancing, US health systems lack consistent national standards for clinical governance, usability validation, risk mitigation, post-deployment monitoring, and nursing workforce readiness. However, neither nursing nor executive digital leadership can achieve responsible AI adoption alone. A structured sector-level partnership between the American Nursing Informatics Association (ANIA) president and the College of Healthcare Information Management Executives (CHIME) vice president provides a unique national influence opportunity to align nursing operational readiness with executive strategic governance and safety expectations for AI-enabled care delivery.
This abstract proposes development of a national ANIA–CHIME collaborative clinical ai safety and workforce preparedness framework designed to unify AI competency expectations, support equitable deployment, and strengthen digital trust. Key strategic pillars of the proposed initiative include 1) embedding structured, competency-based AI training and literacy within prelicensure, graduate, and continuing nursing professional development programs; 2) creating interdisciplinary governance and shared accountability models between nursing, medicine, cybersecurity leadership, and technology executives; 3) establishing national “AI safety clinical rounds” to proactively evaluate workflow risk, unintended consequence emergence, model drift, bias behaviors, and ethical harms; 4) developing transparent vendor partnerships, and 5) integrating federal alignment consistent with guidance from the assistant secretary of technology (AST) and standards articulated within the National Institute of Standards and Technology (NIST) artificial intelligence risk management framework.
This collaboration recommends national adoption and diffusion of the N.U.R.S.E.S. AI literacy framework (normalizing AI vocabulary, understanding data & risk, recognizing bias, safeguarding privacy & security, evaluating performance and outcomes, and sustaining human-centered care) as a unifying model to guide nursing AI competency development. Integrating this into health system governance structures used by chief information officers (CIOs), chief medical informatics officers (CMIOs), chief nursing informatics officers (CNIOs), chief technology officers (CTOs), and chief information security officers (CISOs) creates an interdisciplinary competency alignment capable of transforming the national readiness landscape. This joint model operationalizes nurses not only as technology end users, but as proactive clinical safety stewards, equity protectors, human factors experts, and AI workflow co-designers.

Establishing a shared national leadership voice between ANIA and CHIME positions nursing and executive system leadership to co-drive national AI safety, accelerate scalability, and create consistent workforce capability benchmarks. The proposed collaborative framework supports the future of intelligent health care by protecting safety, elevating trustworthiness, supporting interoperability, and advancing equitable outcomes across diverse clinical populations.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.

P10 - Scaling Faculty AI Development: From Local Innovation to Statewide Impact through the AIM-High Program

Charlotte Seckman, PhD, RN, NI-BC, CNE, FAAN | Cory Stephens, DNP, MSN, RN, CNE, NI-BC, CPHIMS, FHIMSS, Assistant Professor, Informatics Nursing, University of Maryland School of Nursing

Updated: 03/05/26

Purpose: Artificial intelligence (AI) is reshaping how nurse educators teach, evaluate, and prepare learners for data-driven, technology-enabled practice. Led by nursing informatics experts, this initiative illustrates how a university-based innovation evolved into a statewide model for developing AI literacy, innovation capacity, and workforce readiness among nurse educators. The purpose of this poster is to share a scalable, evidence-based approach to professional development in AI. As a learning outcome, participants will be able to describe how structured AI training for nurse educators can be expanded from a single-institution pilot to a coordinated statewide program.
Description: The faculty AI champion program was created to address a gap in educator preparedness for integrating AI into teaching and learning. Supported by an innovation seed grant, the program applied the ADDIE framework and social constructivist principles to deliver interactive workshops, peer mentoring, and ethical discussions. Participants demonstrated a significant increase in AI understanding (M = 4.25) compared to the pre-assessment (M = 3.40) on a 5-point scale and reported high satisfaction (M = 9.50/10), confirming the model’s effectiveness in improving confidence and competence in responsible AI use.
Building on this success, a higher education commission grant supported the statewide AI in Maryland Higher Education (AIM-High) program, which expands the original model through five coordinated pillars: 1) foundations webinars, 2) masterclass series, 3) innovation lab, 4) symposium, and 5) AIM-High network. Each pillar integrates formative and summative evaluation using pre/post assessments, satisfaction surveys, and documentation of AI-enabled curricular adoption. By equipping nurse educators with AI-enabled tools and pedagogical strategies to enhance teaching efficiency, innovation, and workforce development, the program addresses persistent challenges in nursing education such as educator shortages, limited enrollment capacity, and digital skill gaps.
Evaluation/outcome: The faculty AI champion program demonstrated that structured, ethics-anchored AI training enhances teaching efficiency, innovation, and scholarly productivity. The AIM-High program extends this success across Maryland, preparing 100 nurse educators and producing 20 replicable AI teaching projects by 2028. Early implementation has already engaged interprofessional mentors and aligned activities with the Institute of Medicine’s call to strengthen the nursing workforce through technological innovation. Anticipated outcomes include increased educator teaching capacity, expanded student enrollment, and the establishment of a statewide AI-ready network that fosters collaboration, research, and innovation in nursing education. Ongoing evaluation will monitor competency growth, curricular diffusion, and sustainability. Building on the success of a small-scale innovation, AIM-High exemplifies how local nurse educator development can evolve into a statewide infrastructure for AI competency and collaboration.

Learning Objective:

After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and the potential of implementing the improvements into practice.