Capella FPX 4045 Assessment 4

Capella FPX 4045 Assessment 4 Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Informatics and Nursing-Sensitive Quality Indicators Introduction to Nursing-Sensitive Quality Indicators (NSQIs) Hello, my name is _____. In this discussion, I will explore Nursing-Sensitive Quality Indicators (NSQIs), emphasizing their role in evaluating patient outcomes influenced by nursing care. This session will provide an overview of NSQIs, discuss their importance in healthcare, and highlight how nurses contribute to the collection and documentation of these quality measures. Understanding NSQIs and Their Relevance The National Database of Nursing Quality Indicators (NDNQI), developed by the American Nurses Association (ANA), is a nationwide resource that evaluates nursing care standards by collecting data from hospitals across the United States (Montalvo, 2020). This tool supports healthcare organizations in benchmarking their performance against national standards and identifying areas needing improvement. NSQIs primarily focus on outcomes affected by nursing activities, offering insights into how nursing interventions impact patient safety and recovery. These indicators assess factors such as pressure injuries, infection rates, patient falls, and nurse staffing levels (Press Ganey, 2024). One essential NSQI addressed in this guide is Patient Falls with Injury (PFI), a measure that captures both the occurrence and the severity of patient falls. Injuries from falls may involve head trauma, fractures, or other complications. With over 14 million individuals aged 65 and older experiencing falls annually, resulting in about 9 million injuries, the significance of this indicator is evident (CDC, 2024). Falls can delay recovery, lengthen hospital stays, and increase healthcare expenses. Monitoring PFI helps identify risk areas and improve patient safety through enhanced nurse vigilance and environmental safety strategies (Oner et al., 2020). Empowering New Nurses Through NSQIs For newly practicing nurses, understanding PFI is essential. Being at the forefront of patient care, they must be proficient in identifying risk factors and applying preventive strategies. This includes conducting routine assessments, using assistive devices, and educating patients and families about fall prevention (Li & Surineni, 2024). Awareness of NSQIs like PFI fosters accountability, strengthens clinical decision-making, and supports a culture of safety. Gathering and Sharing Quality Indicator Data Methods of Data Collection for PFI In most healthcare environments, PFI-related data is gathered using electronic health records (EHRs), incident reporting systems, and real-time observations. Nurses document falls immediately, detailing the event’s time, location, injuries, and follow-up actions. These entries are stored in centralized databases and undergo review by quality improvement teams. Data validation through audits ensures the accuracy and completeness of documentation (Krakau et al., 2021). Sharing and Utilizing QI Data Collected data are summarized into reports and shared within the organization to encourage transparency and guide clinical improvements. These reports are presented through dashboards, scorecards, or graphs, often displayed on hospital intranet systems or during team meetings (AHRQ, 2025). Nurses are instrumental in reporting accurate data and executing prevention strategies such as hourly rounding, bed alarms, and using non-slip footwear. Omissions in documentation—such as failure to log a fall risk assessment—can misrepresent fall trends and compromise intervention effectiveness (Takase, 2022). Table 1. Data Collection and Reporting of PFI Data Collection Method Description Electronic Health Records (EHRs) Used to log fall incidents, patient status, and interventions in real time. Incident Reporting Systems Provide structured forms for recording fall-related events and injuries. Observational Monitoring Nurses and staff monitor patient behavior for fall risks or signs of distress. Chart Audits and Reviews Quality assurance teams validate accuracy and completeness of entries. Adapted from Krakau et al. (2021); AHRQ (2025) Role of the Multidisciplinary Team in NSQI Implementation Collaborative Approach to PFI Management Addressing PFI requires collaboration among nurses, physicians, therapists, risk managers, and informatics professionals. Nurses often identify falls first and document events, while physicians handle treatment, and therapists assess mobility needs. Risk managers and quality teams evaluate trends to update prevention protocols (Krakau et al., 2021). Informatics teams manage the systems used to collect and track data efficiently. Communication and Coordination Effective communication ensures thorough and timely data collection, resulting in accurate analytics. By combining expertise, the care team develops personalized fall prevention strategies and incorporates them into care routines. This interdisciplinary cooperation improves patient safety and promotes a culture of continuous improvement. Administrative Engagement in NSQI Implementation Use of NSQIs for Performance Improvement Healthcare administrators use NSQI data, such as PFI, to guide decision-making and enhance patient care. Leadership reviews fall trends to adjust staffing levels, revise care protocols, or invest in preventive technologies when necessary (Woltsche et al., 2022). For example, an increase in nighttime falls may prompt a shift in staff allocation or improved lighting systems. Integrating Evidence-Based Guidelines Organizations integrate evidence-based practices (EBPs) based on NSQI data. Common EBP strategies include fall risk assessments on admission, utilizing bed alarms, and ensuring access to call lights (Takase, 2022). These interventions are embedded into training, EHR templates, and patient care routines to promote consistent and effective fall prevention strategies. Establishing Evidence-Based Practices Through PFI Developing Preventive Protocols The PFI indicator informs the creation of EBPs that use both clinical assessment tools and technological support. For instance, the Morse Fall Scale is used to evaluate fall risk during admission and daily assessments. Based on risk scores, nurses activate appropriate safety measures such as sensor footwear and adjustable beds (Mao et al., 2024; Takase, 2022). Visual Identification and Staff Awareness Using visual cues such as colored wristbands or signage identifies patients at risk of falling, prompting staff to offer closer supervision. This simple intervention ensures staff can react swiftly and appropriately, reducing the likelihood of injury (Boot et al., 2023). Table 2. Evidence-Based Interventions for Fall Prevention EBP Intervention Application in Practice Morse Fall Scale Used to assess patient fall risk at admission and daily; guides intervention levels. Bed/Chair Alarms Alerts staff when high-risk patients attempt to mobilize independently. Colored Wristbands/Signage Visually flags high-risk patients for increased monitoring. Hourly Rounding and Call Lights Ensures patient needs are addressed proactively to prevent unsupervised movement. Adapted from Mao et al. (2024); Boot et al. (2023) Conclusion Patient Falls with Injury (PFI) is

Capella FPX 4045 Assessment 3

Capella FPX 4045 Assessment 3 Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Evidence-Based Proposal and Annotated Bibliography on Technology in Nursing Introduction to the Selected Technology Topic Recent advancements in healthcare technology have significantly improved the management of chronic respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD). Among these innovations are sensor-enabled inhalers and wearable devices like smartwatches, which play a critical role in tracking vital signs and promoting medication adherence. These technologies help patients maintain their treatment routines while allowing clinicians to access real-time data for better clinical decisions (Chan et al., 2021). This interest was triggered during the Sentinel U simulations, specifically involving the case of Lynn Tan, which prompted a deeper examination of these tools’ clinical applications. A thorough literature review was conducted using Capella University Library resources, including databases such as PubMed, CINAHL, and SpringerLink. Key terms in the search included “digital inhalers,” “COPD technology adherence,” “remote monitoring,” and “smartwatches in nursing care.” Articles selected for the annotated bibliography were peer-reviewed, published within the last five years, and focused on the effectiveness of digital technologies in treating asthma and COPD. Assumptions The underlying assumptions include the belief that integrating smart technologies—such as wearable devices and digital inhalers—significantly improves the clinical management of chronic respiratory illnesses. It is presumed that enhanced patient monitoring and increased adherence via these tools contribute to better outcomes. Furthermore, it is assumed that the real-time data collected is both usable and valuable to both healthcare providers and patients. Another assumption is that the selected research from credible academic databases is current and applicable to modern nursing practices. Annotation Elements Study Summary Relevance to Nursing Practice Aung et al. (2024) This systematic review evaluates remote digital interventions aimed at improving medication adherence in COPD patients. The evidence suggests such interventions significantly boost treatment compliance and symptom control. The study emphasizes real-time data sharing through digital inhalers, aiding nursing teams in adjusting treatment plans proactively. Chan et al. (2021) This review explores how digital inhalers improve patient adherence and offer real-time feedback. It discusses these technologies’ ability to support remote monitoring and clinical decision-making. It provides insights into remote disease management and how interdisciplinary teams can use inhaler data for individualized care plans. Cokorudy et al. (2024) Through analysis of digital biomarkers, the study highlights patterns that predict asthma exacerbations, enabling early intervention. Parameters like heart rate and cough frequency proved significant. This resource enhances proactive asthma care strategies in nursing by identifying early warning signs and facilitating timely responses. Erbay et al. (2025) Investigates the reliability of SpO2 readings from smartwatches versus clinical tools in COPD patients. The findings support smartwatch use as a non-invasive, moderately accurate tool. Nurses can utilize this technology for continuous oxygen monitoring, empowering patient engagement and safety through home-based care. Feng et al. (2021) Reviews AI integration into chronic respiratory disease management, emphasizing predictive analytics and patient-specific interventions. AI identifies patterns in device usage to optimize care. Highlights the synergy between AI and digital inhalers, showing how nurses can use these tools for precision care and early intervention. Artificial Intelligence Artificial intelligence (AI) has emerged as a critical asset in enhancing digital healthcare tools, particularly in respiratory disease management. AI-enabled systems can assess data from digital inhalers and wearable sensors to predict exacerbations and track medication usage. These intelligent platforms can identify deviations in patient behavior and alert healthcare teams for timely interventions. As discussed by Feng et al. (2021), AI not only improves clinical accuracy but also eases the nursing workload by automating monitoring and customizing treatment strategies. These innovations support better patient outcomes through anticipatory care and real-time analytics, further reinforcing the value of digital tools in chronic care environments. Summary of Recommendations The compiled literature demonstrates that incorporating digital inhalers, wearable technology, and AI into healthcare settings yields substantial benefits in managing asthma and COPD. These tools collectively foster medication adherence, allow for the early identification of symptom deterioration, and facilitate personalized care strategies. Organizational adoption depends on adequate technical resources, policy support for digital health, and staff readiness for interdisciplinary collaboration. Studies such as Aung et al. (2024) and Chan et al. (2021) confirm enhanced medication adherence and fewer disease exacerbations. Meanwhile, Cokorudy et al. (2024) and Erbay et al. (2025) provide strong evidence for the clinical use of digital biomarkers and wearable devices. Feng et al. (2021) further illustrates how AI augments these technologies by enabling predictive and personalized care. Together, these findings advocate for broader adoption of digital innovations in nursing practice to improve patient satisfaction, clinical outcomes, and workforce efficiency. References Aung, H., Tan, R., Flynn, C., Wright, A., Murphy, A., Shaw, D., Ward, T. J. C., & Greening, N. J. (2024). Digital remote maintenance inhaler adherence interventions in COPD: A systematic review and meta-analysis. European Respiratory Review, 33(174). https://doi.org/10.1183/16000617.0136-2024 Chan, A. H. Y., Pleasants, R. A., Dhand, R., Tilley, S. L., Schworer, S. A., Costello, R. W., & Merchant, R. (2021). Digital inhalers for asthma or chronic obstructive pulmonary disease: A scientific perspective. Pulmonary Therapy, 7(2). https://doi.org/10.1007/s41030-021-00167-4 Cokorudy, B., Harrison, J., & Hai, A. (2024). Digital markers of asthma exacerbations – A systematic review. European Respiratory Journal Open Research, 10(6). https://doi.org/10.1183/23120541.00014-2024 Capella FPX 4045 Assessment 3 Erbay, Ü. T., Parspur, Ş., Arikan, İ., Yılmaz, Z. Y., Koçak, H., Marim, F., Kaya, İ., & Doğan, M. (2025). Are smart watches really smart? Comparison of blood oxygen saturation values measured by smart watch, pulse oximetry and arterial blood gases in patients with chronic obstructive pulmonary diseases. International Journal of COPD, 20, 1457–1463. https://doi.org/10.2147/COPD.S500643 Feng, Y., Wang, Y., Zeng, C., & Mao, H. (2021). Artificial intelligence and machine learning in chronic airway diseases: Focus on asthma and chronic obstructive pulmonary disease. International Journal of Medical Sciences, 18(13), 2871–2889. https://doi.org/10.7150/ijms.58191

Capella FPX 4045 Assessment 2

Capella FPX 4045 Assessment 2 Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Root-Cause Analysis and Safety Improvement Plan 1. Sentinel Event Analysis and Contributing Factors A sentinel event refers to an unexpected occurrence involving death or serious physical or psychological injury, not related to the patient’s underlying condition. These incidents can significantly impact not only patients and their families but also the health care professionals involved. The core purpose of examining such events is to identify flaws in the care system and implement changes to prevent similar occurrences. In this case, the event occurred in the Emergency Department (ED) due to a miscommunication during patient handoff. A critical septic patient did not receive timely care as essential information was omitted during shift transition. The patient’s condition deteriorated, resulting in an extended hospital stay and additional medical interventions. Family members experienced emotional distress, and the healthcare team faced increased workloads, reputational concerns, and the potential for disciplinary action. Investigation into why the event occurred revealed several human, systemic, and cultural factors. The outgoing nurse, burdened by fatigue and an excessive workload, failed to communicate critical data effectively. There was a lack of structured communication tools, such as SBAR, and documentation was incomplete. Moreover, the hospital lacked a robust safety culture and leadership oversight. Cultural diversity and varying communication styles among staff also influenced the event. Physical layout challenges, understaffing, and malfunctioning equipment further complicated care delivery, as did unclear hospital policies and a lack of regular monitoring or surveillance. 2. Breakdown of Factors and Root Causes To understand the event comprehensively, various components were analyzed. It was evident that the hospital’s SBAR protocol was not consistently used. The outgoing nurse failed to conduct a bedside handoff or double-check care plans. The incoming nurse did not seek clarification, assuming the information was complete. Vital signs were inadequately monitored, and alarms went unanswered due to alarm fatigue. Staff involved included the two nurses and a physician whose medication orders were not effectively communicated. Supervisors failed to reinforce training or audit the handoff process. Furthermore, policies were not followed due to lack of accessibility and clarity. Staff reported difficulties locating updated guidelines, which led to inconsistencies. These lapses were compounded by environmental issues such as distant nurse stations and faulty equipment. Training gaps were also evident, particularly in handoff communication and patient monitoring. Collectively, these breakdowns highlight an organizational failure to enforce safety protocols and support staff adequately. 3. Strategies for Improvement and Preventive Measures To prevent recurrence of such events, several systemic changes and quality improvements must be implemented. Evidence-based best practices like structured SBAR communication should be standardized. Studies, such as the one by Mulfiyanti and Satriana (2022), have demonstrated significant improvements in handoff efficiency and healthcare quality after implementing SBAR. Additionally, regular simulation-based training can enhance staff competency in emergency responses. To address alarm fatigue, improved alarm management systems and prioritization protocols are needed. Introducing fail-safe mechanisms such as automatic alerts for critical values and consistent audits will support early detection of patient deterioration. Educational programs should be mandated regularly, focusing on emergency protocols and communication skills. Finally, fostering a culture that encourages transparent reporting of errors without fear of punishment can lead to continual learning and safer practices. Tabular Summary of Root Causes and Contributing Factors Root Cause / Contributing Factor Category Code Breakdown in communication between care team Human Factor – Communication HF-C Insufficient training on updated protocols Human Factor – Training HF-T Malfunctioning equipment causing delayed intervention Environment / Equipment E Staff fatigue due to poor scheduling Human Factor – Fatigue HF-F/S Failure to follow safety protocols Rules / Policies / Procedures R Organizational barriers to effective teamwork Barriers B Evidence-Based Strategy Table Strategy Objective Supporting Evidence SBAR Handoff Protocol Standardize communication during patient handoffs Mulfiyanti & Satriana, 2022 Simulation-Based Emergency Training Improve staff response to critical incidents Mulfiyanti & Satriana, 2022; AHRQ, 2020 Alarm Management Systems Reduce alarm fatigue and increase responsiveness AHRQ, 2020 Continuous Education and Refresher Courses Maintain up-to-date knowledge on medication protocols WHO, 2021 Structured Reporting and Feedback Culture Encourage non-punitive incident reporting The Joint Commission, 2019 References Agency for Healthcare Research and Quality. (2020). TeamSTEPPS®: Strategies and tools to enhance performance and patient safety. https://www.ahrq.gov/teamstepps/index.html Mulfiyanti, R., & Satriana, I. W. (2022). The effect of SBAR communication on handoff quality at Tabanan Hospital. Griyatama Nursing Journal, 12(3), 150–156. NURS FPX 4035 Assessment 2 Root-Cause Analysis and Safety Improvement Plan The Joint Commission. (2019). Sentinel Event Policy and Procedures. https://www.jointcommission.org/sentinel_event_policy World Health Organization. (2021). Patient safety: Global action on patient safety. https://www.who.int/publications/i/item/9789240025710      

Capella FPX 4045 Assessment 1

Capella FPX 4045 Assessment 1 Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Nursing Informatics in Health Care Nursing informatics plays a crucial role in linking advanced health technologies with direct patient care. It allows for the streamlined application of data and digital tools in clinical settings to improve the quality and efficiency of care delivery. By integrating informatics into clinical practice, nurses can make informed, data-driven decisions, enhance communication processes, and uphold patient safety standards. Nurse Informaticists (NIs) are instrumental in protecting patient privacy while fostering interdisciplinary communication aimed at improving clinical outcomes (Nashwan et al., 2025). This exploration focuses on how NIs contribute to healthcare by supporting collaborative care and safeguarding sensitive patient information. The Role of Nurse Informaticists Nurse informatics combines scientific expertise, clinical judgment, and data management to facilitate the effective use of health technology. Nurse Informaticists act as critical bridges between clinical and IT teams, ensuring the seamless adoption of healthcare technologies. Their responsibilities include developing user-friendly digital interfaces, guiding technology integration in clinical practice, and promoting effective communication between providers and patients. With tools like patient portals and mobile apps, NIs help enhance treatment adherence, decrease rehospitalization rates, and elevate patient satisfaction (Nashwan et al., 2025). Their educational efforts also empower clinical staff to utilize technology effectively, making care delivery more efficient and collaborative. Contribution to Improving Communication NIs significantly improve healthcare communication through the adoption of secure, real-time messaging tools such as Voalte and TigerText. These platforms enable faster, more accurate clinical interactions that enhance coordination across care teams. Nurse Informaticists also lead training on telehealth platforms, enabling staff to deliver better virtual care and engage patients in collaborative decision-making. Systems like MyChart allow patients to interact with providers, manage appointments, and access medical information. Similarly, HealthTap offers on-demand consultations, improving accessibility and convenience. NIs play a pivotal role in customizing and implementing these technologies while ensuring that communication remains patient-centered and secure (Haleem et al., 2021). Engagement of Nurse Informaticists in Interdisciplinary Teamwork NIs are central to fostering interdisciplinary collaboration. They design digital systems tailored to team needs, enabling seamless workflow and efficient adoption of new technologies. Their work with IT professionals, physicians, and administrators ensures that user interfaces are intuitive for both clinicians and patients. These collaborations result in better access to care, improved patient satisfaction, and fewer readmissions (Ferreira et al., 2025). Furthermore, NIs help develop safety protocols that protect digital communication, and their feedback-driven improvements ensure that systems remain responsive to team and patient needs. In telehealth environments, NIs identify workflow inefficiencies and co-design communication tools that support timely, coordinated, and high-quality care. Evidence-Based Strategies to Protect Protected Health Information NIs implement strong data security measures to protect Protected Health Information (PHI). One key approach is the use of Symmetric Key Encryption (SKE), which secures data on patient portals and mobile applications. These encryption methods prevent unauthorized access and are foundational to PHI protection. Additionally, NIs promote access controls like two-factor authentication, biometric systems, and single sign-on processes to ensure that only authorized personnel can view sensitive information. By conducting training sessions on HIPAA compliance and data privacy responsibilities, NIs help healthcare staff uphold legal and ethical standards, thereby minimizing risks associated with data breaches (Shojaei et al., 2024). The Growing Need for Nurse Informaticists in Healthcare Organizations As technology becomes more deeply embedded in healthcare, the demand for Nurse Informaticists continues to grow. These professionals play a vital role in ensuring that clinical teams can adopt and effectively use new technologies. NIs help design communication platforms tailored to both patients and providers, leading to better system usability and more efficient care delivery. Their involvement reduces the financial and operational costs associated with data breaches by overseeing cybersecurity initiatives and managing EHR systems. With telehealth gaining traction, NIs ensure its secure implementation, enhancing both access and quality while safeguarding patient trust (Wubineh et al., 2023). Conclusion Nurse Informaticists are essential contributors to modern healthcare systems. They enhance care quality through the strategic use of digital tools, secure patient data, and support multidisciplinary teams. By integrating innovative technologies and ensuring data privacy, NIs drive improvements in patient engagement, treatment compliance, and overall satisfaction. As healthcare continues to evolve, the critical role of NIs in promoting efficient, secure, and patient-centered care becomes increasingly indispensable. References Ferreira, J. C., Elvas, L. B., Correia, R., & Mascarenhas, M. (2025). Empowering health professionals with digital skills to improve patient care and daily workflows. Healthcare, 13(3), 329. https://doi.org/10.3390/healthcare13030329 Haleem, A., Javaid, M., Singh, R. P., & Suman, R. (2021). Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sensors International, 2, 100–117. https://pmc.ncbi.nlm.nih.gov/articles/PMC8590973/ Nashwan, A. J., Cabrega, J. A., Othman, M. I., Khedr, M. A., Osman, Y. M., El‐Ashry, A. M., Naif, R., & Mousa, A. A. (2025). The evolving role of nursing informatics in the era of artificial intelligence. International Nursing Review, 72(1), e13084. https://doi.org/10.1111/inr.13084 Capella FPX 4045 Assessment 1 Shojaei, P., Gjorgievska, E. V., & Chow, Y.-W. (2024). Security and privacy of technologies in health information systems: A systematic literature review. Computers, 13(2), 41. https://www.mdpi.com/2073-431X/13/2/41 Wubineh, B. Z., Deriba, F. G., & Woldeyohannis, M. M. (2023). Exploring the opportunities and challenges of implementing artificial intelligence in healthcare: A systematic literature review. Urologic Oncology: Seminars and Original Investigations, 42(3), 48–56. https://doi.org/10.1016/j.urolonc.2023.11.019  

NURS FPX 4045 Assessment 4 Informatics and Nursing-Sensitive Quality Indicators

NURS FPX 4045 Assessment 4 Informatics and Nursing-Sensitive Quality Indicators Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Informatics and Nursing-Sensitive Quality Indicators The National Database of Nursing-Sensitive Quality Indicators (NDNQI), initiated by the American Nurses Association (ANA) in 1998, serves as a vital framework for measuring nursing contributions to patient care quality and safety. These indicators include structural, process, and outcome categories. Structural indicators refer to aspects like staffing ratios and nurse education levels. Process indicators track the implementation of interventions, such as fall prevention protocols. Outcome indicators evaluate the impact of nursing care, for example, the frequency of patient falls or pressure ulcers. Patient falls with injury represent a crucial metric in acute care settings, reflecting the quality of safety practices. Acute hospitals cater to diverse patient needs, making fall prevention critical. Falls act as both process and outcome indicators; even minor falls expose system vulnerabilities and improvement areas. By investigating these incidents, nurses and teams can address root causes and strengthen prevention programs to reduce high-risk occurrences. The consequences of falls go beyond physical harm, leading to increased healthcare costs and workflow disruptions. Studies reveal that hospital-based falls are among the most common preventable incidents, costing from \$352 to \$13,617 per patient (Dykes et al., 2023). Effective fall prevention, through interventions such as assistive devices and staff education, not only enhances patient safety but also reduces length of stay and resource utilization. Consequently, addressing patient falls is both a quality and financial imperative. Data Collection, Reporting, and Interdisciplinary Collaboration Falls with injury impact regulatory compliance and institutional reputation. Organizations like The Joint Commission and CMS factor fall rates into accreditation and reimbursement processes. Therefore, facilities must constantly improve fall prevention strategies. Nurses are on the frontline of these efforts. Their responsibilities include assessing patient risk, applying preventive protocols, and documenting incidents comprehensively. Evidence-based practices, supported by accurate reporting, help teams develop and refine strategies. New nurses must understand Nursing-Sensitive Quality Indicators (NSQIs) and their importance in maintaining safety standards. Knowledge of fall prevention empowers them to apply best practices and collaborate effectively. Tools like the Morse Fall Scale help in evaluating risk, while electronic health records (EHRs) ensure complete documentation. Bedside reports, safety briefings, and incident tracking systems allow staff to respond promptly and monitor trends over time. Interdisciplinary teamwork enhances these efforts. Nurses, risk managers, physical therapists, and administrators work together using EHRs, direct assessments, and incident reviews. This approach enables better policy development and resource allocation. It creates a safety culture where fall prevention becomes integral to daily practice. Sharing findings with governing bodies and using digital dashboards for benchmarking further supports institutional performance and accountability. Technology, Evidence-Based Practice, and Administration’s Role Administrative support is essential for optimizing fall prevention initiatives. Hospital leadership can drive performance improvements by using data from NSQIs to shape policy and training. This includes employing safety technologies such as bed alarms, lighting adjustments, and fall alert systems. Data from incident reports and digital dashboards inform leadership of progress, enabling comparison with national benchmarks. NSQIs also facilitate Evidence-Based Practice (EBP), ensuring consistency and quality. Innovations like wearable monitors and sensor-based detection systems allow for real-time responses to potential falls. EHR integration offers clinical decision support alerts, while environmental adjustments such as impact-absorbing flooring reduce injury severity. Early risk identification through stratification tools ensures targeted care within the first 24 hours of admission (Satoh et al., 2022). When nurses use NSQIs and data-driven insights, they can proactively tailor interventions, increasing patient satisfaction and outcomes. Predictive analytics and early alerts enhance fall prevention strategies. This structured, technology-supported approach strengthens safety and aligns with regulatory expectations. Ultimately, the integration of NSQIs with EBP and administrative leadership establishes a framework for continuous quality improvement. Table: Overview of NSQI Concepts and Practices Aspect Details Significance Indicator Types Structural (staffing), Process (protocols), Outcome (fall rates) Helps standardize nursing assessment and evaluate care effectiveness Fall Prevention Interventions Bed alarms, assistive devices, environmental changes, patient education Reduce injury risks, improve patient outcomes, and lower costs Reporting Tools & Methods EHRs, Morse Fall Scale, STRATIFY, incident tracking, safety briefings Enable consistent and detailed data capture for accurate trend analysis Multidisciplinary Involvement Nurses, QI experts, risk managers, therapists, administrators Ensures thorough data review, resource allocation, and evidence-based response Technological Integration Sensor-based systems, clinical alerts, real-time dashboards, predictive analytics Facilitates timely response and improves fall prevention strategies Organizational Impact Improved safety metrics, compliance with CMS/Joint Commission, reduced liability Strengthens institutional reputation, lowers costs, and sustains regulatory accreditation References Alanazi, F. K., Sim, J., & Lapkin, S. (2021). Systematic review: Nurses’ safety attitudes and their impact on patient outcomes in acute‐care hospitals. Nursing Open, 9(1), 30–43. https://doi.org/10.1002/nop2.1063 Alshammari, S. M. K., Aldabbagh, H. A., Anazi, G. H. A., Bukhari, A. M., Mahmoud, M. A. S., & Mostafa, W. S. E. M. (2023). Establishing standardized Nursing Quality Sensitive Indicators. Open Journal of Nursing, 13(8), 551–582. https://doi.org/10.4236/ojn.2023.138037 Informatics and Nursing-Sensitive Quality Indicators Basic, D., Huynh, E. T., Gonzales, R., & Shanley, C. G. (2021). Twice‐weekly structured interdisciplinary bedside rounds and falls among older adult inpatients. Journal of the American Geriatrics Society, 69(3), 779–784. https://doi.org/10.1111/jgs.17007 Dykes, P. C., Bowen, M. C., Lipsitz, S., Franz, C., Adelman, J., Adkison, L., … & Bates, D. W. (2023). Cost of inpatient falls and cost-benefit analysis of implementation of an evidence-based fall prevention program. JAMA Health Forum, 4(1), e225125. https://doi.org/10.1001/jamahealthforum.2022.5125 Ghosh, M., O’Connell, B., Yamoah, E., Kitchen, S., & Coventry, L. (2022). A retrospective cohort study of factors associated with severity of falls in hospital patients. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-16403-z Gormley, E., Connolly, M., & Ryder, M. (2024). The development of nursing-sensitive indicators: A critical discussion. International Journal of Nursing Studies Advances, 7(7), 100227–100227. https://doi.org/10.1016/j.ijnsa.2024.100227 Hassan, Ch. A. U., Karim, F. K., Abbas, A., Iqbal, J., Elmannai, H., Hussain, S., Ullah, S. S., & Khan, M. S. (2023). A cost-effective fall-detection framework for the elderly using sensor-based technologies. Sustainability, 15(5). https://doi.org/10.3390/su15054489 O’Connor, M., Norman, K., Jones, T., & Johnston, K. (2022). Smart flooring and wearable sensors for fall prevention in hospitals. Journal of Biomedical Informatics, 130, 104082. https://doi.org/10.1016/j.jbi.2022.104082 Informatics

NURS FPX 4045 Assessment 3 Technology in Nursing

NURS FPX 4045 Assessment 3 Technology in Nursing Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Technology in Nursing Introduction to the Selected Technology Topic Telehealth videoconferencing systems were chosen for this analysis due to their ability to expand patient access to healthcare, improve clinical outcomes, and ensure patient safety. This technology has gained prominence in response to the growing need for remote healthcare, especially in rural and underserved areas. By reducing barriers such as geographical distance, videoconferencing supports timely medical interventions and reinforces patient-centered care delivery models. What makes this technology particularly compelling is its facilitation of real-time interactions between patients and healthcare providers, thereby enhancing continuity of care and reducing preventable hospital readmissions. In researching this topic, databases including PubMed, CINAHL, and ScienceDirect were utilized. Keywords such as “telehealth videoconferencing in nursing,” “videoconferencing system and patient safety,” and “telehealth technology in quality care” were used to locate peer-reviewed articles emphasizing its significance in nursing practice and interdisciplinary settings. Summary of Annotated Literature The table below summarizes the main findings from five peer-reviewed studies related to telehealth videoconferencing and its impact on nursing practice. Study Key Findings Implications for Nursing Practice Ådnanes et al. (2024) Videoconferencing improved access to mental health services for children in welfare systems; boosted functioning but raised concerns over rapport-building. Nurses working with vulnerable populations can use VC to promote timely care and communication, but must address the limitations in therapeutic relationships. Cubo et al. (2021) Reviewed 26 videoconferencing tools; emphasized benefits for neurological care but flagged cybersecurity risks. Nurses must select secure platforms that comply with regulations to ensure data protection and support remote patient management. Newbould et al. (2021) Explored sustainability of VC in care homes; success tied to leadership, training, and organizational culture. Nurses benefit from enhanced care coordination and specialist input, especially in long-term care settings, when implementation is backed by leadership. Payne & Clarke (2023) Video consultations are effective for urgent primary care triage and foster patient trust. Supports remote triage, timely referrals, and visual assessments; nurses can use it to improve care delivery and patient engagement. Tenfelde et al. (2023) Patient satisfaction with VC linked to communication quality and minimal technical issues. Nurses should focus on building strong communication skills and ensure reliable technology use to improve satisfaction and health outcomes. Integration with Artificial Intelligence (AI) and Summary Recommendations Artificial Intelligence (AI) serves as a powerful complement to videoconferencing in healthcare. AI-driven tools enhance nursing workflows by improving triage, supporting personalized care plans, and enabling predictive analytics to detect early health deterioration. Features like AI-generated real-time captions increase accessibility for patients with hearing impairments, while chatbots offer support for medication guidance and general health inquiries, thereby reducing the routine workload of nurses (Burrell, 2023). According to Tenfelde et al. (2023), successful implementation of video consultations hinges on minimizing technical disruptions and maximizing effective communication between patients and providers. AI technologies can enhance these dimensions by optimizing video quality, automating technical troubleshooting, and facilitating patient engagement. These advancements not only improve patient outcomes but also increase provider satisfaction and system efficiency. The collected literature underscores videoconferencing’s potential to transform healthcare delivery through better access, safety, and interdisciplinary collaboration. However, challenges such as cybersecurity risks (Cubo et al., 2021) and the potential loss of in-person rapport must be addressed through thoughtful implementation. Key enablers for success include leadership support, ongoing staff training, and robust technical infrastructure (Payne & Clarke, 2023). When combined with AI innovations, videoconferencing becomes a critical tool in delivering effective, efficient, and equitable healthcare. References Ådnanes, M., Kaasbøll, J., Kaspersen, S. L., & Krane, V. (2024). Videoconferencing in mental health services for children and adolescents receiving child welfare services: A scoping review. BMC Health Services Research, 24(1). https://doi.org/10.1186/s12913-024-11157-y Burrell, D. N. (2023). Dynamic evaluation approaches to telehealth technologies and artificial intelligence (AI) telemedicine applications in healthcare and biotechnology organizations. Merits, 3(4), 700–721. https://doi.org/10.3390/merits3040042 NURS FPX 4045 Assessment 3 Technology in Nursing Cubo, E., Arnaiz-Rodriguez, A., Arnaiz-González, Á., Díez-Pastor, J.-F., Spindler, M., Cardozo, A., Garcia-Bustillo, A., Mari, Z., & Bloem, B. R. (2021). Videoconferencing software options for telemedicine: A review for movement disorder neurologists. Frontiers in Neurology, 12. https://doi.org/10.3389/fneur.2021.745917 Newbould, L., Ariss, S., Mountain, G., & Hawley, M. S. (2021). Exploring factors that affect the uptake and sustainability of videoconferencing for healthcare provision for older adults in care homes: A realist evaluation. BMC Medical Informatics and Decision Making, 21(1). https://doi.org/10.1186/s12911-020-01372-y Payne, R., & Clarke, A. (2023). How and why are video consultations used in urgent primary care settings in the UK? A focus group study. BJGP Open, 7(3). https://doi.org/10.3399/bjgpo.2023.0025 Tenfelde, K., Bol, N., Schoonman, G., Erik, J., & Antheunis, M. L. (2023). Exploring the impact of patient, physician and technology factors on patient video consultation satisfaction. Digital Health, 9. https://doi.org/10.1177/20552076231203887 NURS FPX 4045 Assessment 3 Technology in Nursing

NURS FPX 4045 Assessment 2 Protected Health Information

NURS FPX 4045 Assessment 2 Protected Health Information Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Protected Health Information Understanding Protected Health Information (PHI) and HIPAA Guidelines Protected Health Information (PHI) refers to any patient-specific data that can identify an individual and relates to their healthcare services, treatments, or payment records. This includes details such as names, contact information, birth dates, diagnostic assessments, prescribed medications, treatment plans, insurance, and billing information (Pool et al., 2024). Managing PHI responsibly, especially during telehealth services, is fundamental to maintaining patient trust and adhering to HIPAA standards. The Health Insurance Portability and Accountability Act (HIPAA) plays a critical role in ensuring the confidentiality, security, and accessibility of PHI in the United States (Lindsey et al., 2025). It prohibits the disclosure of PHI without patient consent, granting individuals the right to access and control their medical information. HIPAA is especially important in the digital age, as telehealth introduces new vulnerabilities. Key components include: Security Rule: Mandates protection against unauthorized access to electronic health information (EHI). Privacy Rule: Restricts sharing of PHI without appropriate consent. Confidentiality Rule: Ensures that data exchange during care processes remains secure. For example, using unencrypted platforms for telehealth can lead to hacking risks. Likewise, discussing patient data in public spaces may result in unauthorized exposure (Alder, 2025). Role of Interdisciplinary Collaboration and Social Media Misuse Interdisciplinary collaboration is vital for safeguarding EHI, especially in telehealth. Professionals from various sectors—clinical, administrative, security, and IT—must work together to ensure robust data protection. Clinical staff engage in cybersecurity training to apply secure practices like encryption and password management. Administrators develop safety policies and allocate resources, while IT experts implement advanced tools such as firewalls and encryption systems. Institutions like the Cleveland Clinic have implemented such holistic strategies to uphold patient confidentiality (Cleveland Clinic, 2023). Unfortunately, social media misuse continues to be a serious breach point. Healthcare professionals, especially nurses, must refrain from posting patient-related content online. Violations can lead to severe consequences including job termination, license revocation, financial penalties, and legal action. Notable incidents include: A nursing assistant terminated for sharing a Snapchat video of an Alzheimer’s patient (Moore & Frye, 2020). An oral surgeon fined \$10,000 for sharing PHI on a public review platform. Organizations fined for broad PHI exposure—such as Green Ridge Behavioral Healthcare being penalized for disclosing data of over 14,000 patients (Alder, 2025). These incidents highlight the importance of maintaining professional boundaries and respecting patient privacy in all communications, including on social platforms. Practices and Strategies for Securing PHI To protect PHI, especially during telehealth interactions, organizations should implement a range of security-focused strategies: Use Robust Security Systems: Employing secure platforms with SSL encryption safeguards patient information. The Mayo Clinic utilizes such systems to maintain secure data transmission (Mayo Clinic, 2024). Conduct Safety Audits: Regular evaluations and feedback from stakeholders help ensure continuous HIPAA compliance. MGH, for instance, performs internal audits to ensure patient privacy (MGH, n.d.). Cybersecurity Training: Educating healthcare staff on data safety principles helps reduce breaches during digital communication. Additional social media-specific strategies include: Instituting strict policies prohibiting PHI sharing or discussing work online. Using encrypted communication channels for all patient-related dialogue. Establishing a clear reporting protocol for suspected breaches to minimize exposure and facilitate rapid responses. Together, these measures help create a culture of privacy and accountability in healthcare settings. Summary Table Category Key Details Examples/Implications Protected Health Information (PHI) Patient-identifiable data including treatments, diagnostics, and insurance Requires secure handling during telehealth sessions (Pool et al., 2024) HIPAA Components Security Rule, Privacy Rule, Confidentiality Rule Prevents unauthorized access or sharing of PHI (Lindsey et al., 2025; Alder, 2025) Interdisciplinary Collaboration Involves clinicians, administrators, security, and IT Cleveland Clinic uses team-based privacy approaches (Cleveland Clinic, 2023) Social Media Violations PHI posted online can lead to penalties, termination, jail Nurses, surgeons, and institutions have faced legal actions (Moore & Frye, 2020) Prevention Practices Encryption, audits, cybersecurity workshops Mayo Clinic uses SSL; MGH performs privacy audits (Mayo Clinic, 2024; MGH, n.d.) Social Media Guidelines Avoid posting or discussing patient info online; report breaches Strict internal policies reduce exposure and disciplinary risks (Alder, 2025) References Alder, S. (2023). HIPAA and social media rules – Updated for 2023. The HIPAA Journal. https://www.hipaajournal.com/hipaa-social-media/ Alder, S. (2023). HIPAA privacy rule – updated for 2023. The HIPAA Journal. https://www.hipaajournal.com/hipaa-privacy-rule/ Cleveland Clinic. (2023). Holistic, multidisciplinary approach protects patient data and privacy. ClevelandClinic.org. https://consultqd.clevelandclinic.org/holistic-multidisciplinary-approach-protects-patient-data-and-privacy/ NURS FPX 4045 Assessment 2 Protected Health Information Lindsey, D., Sniker, R., Travers, C., Budhwani, H., Richardson, M., Quisney, R., & Shukla, V. V. (2023). When HIPAA hurts: Legal barriers to texting may reinforce healthcare disparities and disenfranchise vulnerable patients. Journal of Perinatology, 45(2), 278–281. https://doi.org/10.1038/s41372-024-00805-5 Mayo Clinic. (2024). Privacy policy. MayoClinic.org. https://www.mayoclinic.org/about-this-site/privacy-policy MGH. (n.d.). Protect our patients’ privacy. Massachusetts General Hospital. https://www.massgeneral.org/assets/MGH/pdf/research/mgh-privacy-presentation.pdf Moore, W., & Frye, S. (2020). Review of HIPAA, part 2: Infractions, rights, violations, and role for the imaging technologist. Journal of Nuclear Medicine Technology, 48(1), 7–13. https://doi.org/10.2967/jnmt.119.227827 NURS FPX 4045 Assessment 2 Protected Health Information Pool, J., Akhlaghpour, S., Fatehi, F., & Burton-Jones, A. (2023). A systematic analysis of failures in protecting personal health data: A scoping review. International Journal of Information Management, 74, 102719–102719. https://doi.org/10.1016/j.ijinfomgt.2023.102719

NURS FPX 4045 Assessment 1 Nursing Informatics in Health Care

NURS FPX 4045 Assessment 1 Nursing Informatics in Health Care Name Capella university NURS-FPX4045 Nursing Informatics: Managing Health Information and Technology Prof. Name Date Nursing Informatics in Health Care Integrating a Clinical Decision Support System (CDSS) into healthcare organizations is essential for enhancing patient outcomes and safety. CDSS technology significantly contributes to improving diagnostic accuracy, refining treatment protocols, and supporting clinical decisions (Laraichi et al., 2024). The implementation of this system requires skilled Nurse Informaticists (NI), who play a vital role in minimizing clinical errors, delivering real-time medication alerts, and ensuring overall patient safety. In nursing practice, informatics merges nursing science with information technology to improve the delivery of healthcare. Nurse Informaticists are equipped with both clinical and technological expertise and serve as intermediaries between IT systems and clinical practice (Nashwan et al., 2025). They oversee the implementation of tools like CDSS, train healthcare personnel, and develop strategies for data-informed decision-making. Notably, Dr. Virginia Saba contributed to this field by developing the Clinical Care Classification (CCC) system to enhance documentation precision (Lopez et al., 2023). NIs ensure that CDSS platforms are designed for user-friendliness and meet clinical needs, boosting decision accuracy and reducing errors. Leading health organizations such as the Cleveland Clinic and Mayo Clinic have adopted nursing informatics to enhance clinical performance. Cleveland Clinic uses nursing informatics to streamline Electronic Health Records (EHRs), while Mayo Clinic uses CDSS to tailor care for patients with Acute Kidney Injury (Mayo Clinic, 2024). These systems assist in predicting risk factors and offering timely, evidence-based recommendations. The presence of Nurse Informaticists in these settings ensures that CDSS is integrated smoothly, aligning patient care strategies with technology and enhancing clinical outcomes. Nurse Informaticists and Healthcare Collaboration Nurse Informaticists act as liaisons between technology developers and healthcare professionals. They collaborate across disciplines—nurses, physicians, and IT experts—to develop systems that are clinically relevant and functionally efficient (Laraichi et al., 2024). By applying their dual expertise, they ensure that CDSS tools are effectively integrated into EHRs and that systems meet the dynamic demands of patient care. Their work not only reduces clinical errors but also fosters team collaboration and boosts clinical efficiency. Training is a crucial responsibility of Nurse Informaticists. They educate nurses and other clinical staff on how to use CDSS effectively, ensuring that everyone understands how to access real-time data and apply it to clinical decision-making. According to the American Nurses Association (2024), training initiatives support the adoption of technology and increase staff competency, which translates to safer and more efficient patient care. NI-led implementation also supports change management and increases the acceptance of new tools within clinical environments. The value of full nurse participation in CDSS planning cannot be overstated. When nurses are involved in the creation and execution of clinical systems, workflows improve, and patient outcomes are optimized. Nurses’ insights help ensure that the CDSS supports practical clinical operations while reducing overhead costs. According to Zhai et al. (2022), nurse engagement is vital in every stage of implementation to ensure clinical relevance and acceptance of the tools. Moreover, such integration enhances efficiency and leads to significant cost savings. Opportunities, Challenges, and Recommendations Nurse Informaticists bring transformative opportunities to health organizations through the implementation of CDSS, including the standardization of care and the enhancement of patient safety. These professionals help streamline care workflows and ensure real-time, data-driven decisions (Laraichi et al., 2024). For instance, CDSS use has reduced unnecessary testing costs, such as an annual \$300,000 saving on vitamin D testing (Lewkowicz et al., 2020). Moreover, NIs are key in maintaining data integrity, ensuring HIPAA compliance, and executing data encryption and multifactor authentication to protect sensitive patient information (Shojaei et al., 2024). Despite these advantages, challenges persist, including resistance to new technologies and data privacy concerns. These can be addressed through robust staff training and strict data security protocols. NIs conduct system audits and enforce access controls to safeguard patient records. Their collaboration with technologists ensures that tools meet clinical needs and are user-friendly, thereby improving acceptance rates. To conclude, the inclusion of Nurse Informaticists is justified based on their unique ability to integrate CDSS into healthcare systems effectively. Their involvement enhances diagnostic accuracy, patient safety, and data security. Nurse Informaticists serve as catalysts for technological adoption, enabling better outcomes through streamlined clinical workflows, data-driven decision-making, and interdisciplinary collaboration. Table: Summary of Key Concepts Heading Key Focus Areas Examples and Outcomes Nursing Informatics and CDSS – Improve diagnostics – Reduce errors – Real-time alerts CDSS tools used by Cleveland Clinic and Mayo Clinic to enhance patient-specific care and diagnostics NI Roles and Collaboration – Train staff – Optimize EHR – Design user-friendly CDSS NI ensures smooth CDSS-EHR integration, educates teams, ensures clinical relevance Opportunities and Justifications – Cost savings – Privacy and data security – Improved patient care Savings of \$300,000 annually (Lewkowicz et al., 2020); Enhanced HIPAA compliance and care quality References American Nurses Association. (2024). What is nursing informatics and why is it so important. https://www.nursingworld.org/content-hub/resources/nursing-resources/nursing-informatics/ Cleveland Clinic. (2024). Nursing informatics. https://consultqd.clevelandclinic.org/nursing/nursing-informatics Laraichi, O., Daim, T., Alzahrani, S., Hogaboam, L., Bolatan, G. I., & Moughari, M. M. (2024). Technology readiness assessment: Case of clinical decision support systems in healthcare. Technology in Society, 79, 102736. https://doi.org/10.1016/j.techsoc.2024.102736 Lewkowicz, D., Wohlbrandt, A., & Boettinger, E. (2020). Economic impact of clinical decision support interventions based on electronic health records. BMC Health Services Research, 20(1), 871. https://doi.org/10.1186/s12913-020-05688-3 NURS FPX 4045 Assessment 1 Nursing Informatics in Health Care Lopez, K. D., Langford, L. H., Kennedy, R., McCormick, K., Delaney, C. W., Alexander, G., Englebright, J., Carroll, W. M., & Monsen, K. A. (2023). Future advancement of health care through standardized nursing terminologies: Reflections from a Friends of the National Library of Medicine workshop honoring Virginia K. Saba. Journal of the American Medical Informatics Association, 30(11), 1878–1884. https://doi.org/10.1093/jamia/ocad156 Mayo Clinic. (2024). Clinical decision support systems for personalized management of patients with acute kidney injury. https://www.mayoclinic.org/medical-professionals/pulmonary-medicine/news/clinical-decision-support-systems-for-personalized-management-of-patients-with-acute-kidney-injury/mac-20524049 Nashwan, A. J., Cabrega, J. A., Othman, M. I., Khedr, M. A., Osman, Y. M., Ashry, A. M. E., Naif, R., & Mousa, A. A. (2025). The evolving role of nursing informatics in the era