Purpose: The purpose of this project was to optimize nursing documentation within flowsheets in the electronic health record. The flowsheets are essential for capturing structured data; however, redundancies and over-reliance on free-text options were identified, contributing to complex documentation and burden. We aimed to optimize six core flowsheet templates—vital signs, pain, assessment, vascular access, general cares, and intake—by consolidating redundant entries, improving template usability, aligning with Epic foundations where possible and minimizing free-text requirements. Through evidence-based practices, benchmarking, and a review of “within defined limits” (WDL) values and definitions, we sought to streamline documentation workflows and enhance the efficiency of data entry for clinicians, thereby freeing up more time for patient care.
Description: This project focused on redesigning the six most used inpatient nursing flowsheet templates in the EHR, informed by clinician feedback, best practice standards, and benchmarking data from peer institutions. Our efforts centered on two primary consolidation efforts: first, combining four separate vital signs templates into a single, streamlined version; and second, reducing the vascular access flowsheet groups from 40 different lines, devices, and assessments (LDAs) groups down to 14 essential entries. These consolidations addressed redundancies, reduced confusion, and made it easier for clinicians to document and locate critical patient information. Another key component was revising WDL values and definitions across all six templates. This revision aligned the WDLs more closely with current clinical standards, reducing ambiguity and the need for free-text clarifications. By standardizing these values, we minimized the number of comments and unnecessary entries. The entire process was iterative, involving regular clinician feedback and testing to ensure that the updated templates aligned well with clinical workflows.
Evaluation/outcome: The project’s success was evaluated through pre- and post-optimization analysis, comparing data from March 1–31, 2023, and June 5–15, 2024. Key outcomes included: Total rows across templates: Overall number of rows increased slightly from 9,980 to 10,421 (an addition of 441 rows). Documented rows: Documented rows decreased from 6,010 to 5,414, a net reduction of 596 rows. Removed rows: Rows removed increased from 1,513 to 1,712. Rows with comments: Number of rows containing comments decreased from 2,781 to 1,320, a reduction of 1,461 rows. Individual comments: Number of comments decreased substantially, from 383,647 pre-optimization to 34,433 post-optimization. Comments per day: Comments per day dropped by 9,245.4, from 12,375.7 to 3,130.3, a 75% reduction. Reduction in flowsheet values: The project reduced over 2 million documented values across flowsheets between June and July 2024, highlighting the impact of consolidation on reducing data entry volume.
Purpose: This study aims to assess the feasibility of using a contact-free, passive sensor system to continuously monitor falls among older adults in long-term care facility.
Background/significance: Falls are a significant health concern for adults over 60, with one-third over 65 experiencing a fall annually and 10% of these resulting in serious injury. Falls are the leading cause of injury and death in this age group, contributing to 65,000 hip fractures annually. Each year, the US treats nearly 3 million older adults for fall-related injuries, as the risk escalates with age. Among those aged 90 and older, 30% who cannot get up after a fall remain on the ground for over an hour, significantly increasing the risk of serious injuries and hospitalizations. This underscores the urgent need for effective fall monitoring and assistance solutions.
Methods: The research was conducted in two long-term care facilities in Missouri and Arizona, concentrating on the remote monitoring of older adults, including those with dementia and/or mobility aids. Sensors built by Signify were installed in the residents' rooms, including a ceiling light integrated with a radar sensor in the bedroom and a time-of-flight sensor in the bathroom. These sensors tracked falls in the environment for 6 to 9 months, and data collected was used to evaluate fall detection algorithm. We also recruited and trained healthy adults as stunt actors to perform both fall and non-fall activities, mimicking the typical movement patterns of older persons, to obtain an adequately sized fall for validation. Their training encompassed executing several scripted falls, including those from standing and seated positions and falls resulting from tripping or falling. Using these controlled simulations made sure that the fall detection algorithms were tested in a thorough and organized way, since real falls among residents might not happen often enough to be reliable. Sensitivity and specificity are reported for each group.
Results: This study enrolled 20 residents (70% female, mean age 83.46 years, SD = 8.64) who were at high risk for falls and 13 stunt actors who executed a total of 1,125 scripted activities, comprising 662 fall actions and 463 non-fall actions. The radar sensor exhibited a sensitivity of 74.42% and a specificity of 100%, based on the analysis of 650 stunt simulation actions, including both falls and non-falls. The ToF sensor demonstrated a sensitivity of 95.24% and a specificity of 100%, based on the analysis of 104 stunt simulation actions. The radar sensor demonstrated 100% sensitivity for actual falls among residents over a 6- to 9-month period, with a false alarm rate of less than one per sensor month.
Conclusions/implications: This study demonstrates that contactless sensors proficiently detect falls, attaining high sensitivity and specificity in both actual and simulated conditions. This non-invasive, continuous fall monitoring approach has potential for improving safety, lowering healthcare expenses, and enhancing outcomes for high-risk groups in long-term care contexts. Despite problems such as gradual falls, movements from low heights, and occasional device offline, improving detection algorithms can significantly augment system efficacy and reliability.
In the fast-changing healthcare landscape, integrating data and technology is vital for improving patient care and clinical workflows. Recognizing this necessity, a Magnet-designated, tertiary care teaching hospital in Los Angeles, introduced a 24-week nursing informatics residency program tailored for bedside nurses. This innovative initiative aimed to equip nurses with the essential skills and knowledge to harness the power of informatics, enabling them to utilize technology to drive positive change within their clinical practice.
Despite the growing dependence on accessible, accurate, timely data, and technology in healthcare delivery, there is a notable shortage of skilled informaticists who can effectively utilize these tools at the frontline of patient care. Bedside nurses, although highly experienced, often lack formal training in informatics, which limits their ability to fully harness technological advancements to enhance patient outcomes and streamline clinical processes.
The nursing informatics residency program aimed to address the growing need for skilled informaticists by providing bedside nurses with a structured pathway to develop informatics skills. By integrating clinical practice with technology, the program empowered nurses to make informed decisions and drive innovation in health care. Supporting emerging nursing informaticists can enhance patient care, reduce turnover and burnout, and ensure sustainable leadership.
Flyers invited candidates to apply for the residency program, requiring a resume, manager approval, and a brief statement of interest in informatics. Accepted residents committed to a 24-week program based on the American Nurses Association Nursing Informatics Scope and Standards of Practice.
Applying an organized framework to design nurse residency programs ensures the integration of evidence-based practices that align with organizational goals, enhancing patient safety, supporting key objectives, and fostering a healthy workplace environment. The program consisted of three phases, clinical immersion, mentorship, and evaluation, which guided the participants through designing, developing, implementing, and assessing data and information systems. Residents demonstrated their informatics proficiencies by applying acquired tools to a final project aimed at improving outcomes and experiences for both patients and clinicians.
The nursing informatics residency program provided several valuable insights and lessons. Key areas of focus that emerged throughout the program include adaptability, administrative support, and time management. These insights will guide future iterations, ensuring the program evolves to meet the needs of residents and the healthcare organization.
By the end of the program, nursing informatics residents gained a deeper understanding of their role in the hospital. They created projects aligned with the organization’s strategic goals, demonstrating their ability to drive change. Participants showcased leadership potential through public speaking, poster presentations, and contributions to the Magnet redesignation process.
Purpose: This study aimed to establish perceived workload and ambulatory care registered nurse (RN) and medical assistant (MA) emotions about electronic health record (EHR) patient portal messages and provide insight on end user archetypes for leadership to tailor change management prior to widespread adoption/integration of large language models (LLMs) into EHRs.
Background: As healthcare experiences a critical workforce shortage aggravated by pandemic-related burnout, the increasing reliance on electronic health records has intensified stress among clinicians, especially with the burgeoning volume of patient communications facilitated by patient portals. This academic health science center experienced an exponential increase in patient messages from 332,000 messages total between fiscal years (FY) 2014 to 2018 to 1.6 million messages in FY 2023; thereby significantly adding to RN and MA administrative responsibilities. The release of the generative artificial intelligence (AI) product ChatGPT in November of 2022 and the subsequent explosion of large language models hold the potential to transform health care by enhancing patient care through improved diagnostic support, personalized treatment recommendations, and more efficient management of clinical data. Existing discussions around AI's role in health care have largely centered on licensed independent practitioners, leaving a gap in understanding the needs and sentiments of vital support staff like RNCs and PCCs.
Methods: This is descriptive study using validated survey instruments (Joyful Workplace Mini Z 2.0, Knowledge and Perception of AI, and Technology Readiness Index [TRI] 2.0) and investigator-designed questions about burnout and technology readiness. Participants were recruited via convenience sampling from ambulatory care clinics at a large academic health science center.
Results: Data collection is currently in progress with 281 participants, RNs=125 (44.48%) and MAs (n=156, 55.52%), with a target of 300 respondents.
Conclusion: The rapid adoption of AI and large language models is transforming various aspects of life, including health care, where systems are restructuring electronic health records to enhance workflow efficiencies. It is essential to consider the input of ambulatory care nurses and medical assistants regarding these potentially transformative tools for drafting responses to patient portal messages before their further adoption or deployment.
In the fourth quarter of 2023, nurses at Texas Children’s Hospital reported an increase in the frequency of IV pump errors, significantly affecting confidence in the existing equipment's ability to safely deliver medications. In response, a meeting with our IV pump vendor was held in January 2024, where we requested a trial of the vendor's latest FDA-approved IV pump. From January 1, 2023, to March 4, 2024, a total of 114 IV pump-related events were logged, underscoring the critical need for updated equipment.
On March 5, 2024, the vendor conducted a clinical unit tour, approving a trial of the new IV pumps. Our hospital received the updated pumps on April 30, 2024, and immediately initiated configuration, testing, and simulation protocols. The trial officially began on May 14, 2024, focusing on critical patients in the cardiac intensive care unit (CICU). The trial pumps were used on patients transferred from the cardiovascular operating room (CVOR) or admitted to CICU until the trial concluded on June 27, 2024.
Why conduct a trial? The high number of errors and safety events associated with the current IV pumps. Nurses and physicians had lost confidence in the pumps' reliability, directly affecting patient care. The potential for these issues to impact patient safety, especially among critically ill patients, required an immediate solution.
How was the trial conducted? The trial was carefully designed to ensure accurate monitoring and results. The CICU was selected due to its critical patient population and willingness to participate. The trial was confined to a closed unit to prevent pump movement, with daily inventory tracking and server connection monitoring. Systematic pump changes were made from old to new equipment, with staff education provided beforehand. Nursing staff completed surveys to assess their experience and perceptions of the new pumps.
Trial outcomes: The 45-day trial proved successful, with 34 patients receiving care using the new pumps, administering a total of 6,000 infusions. These included some of the most critical patients, such as those on ECMO and VAD support. The trial revealed only four events, with one being directly attributed to the pump’s network card, while the others were related to connectivity and ID mismatches. The new IV pump was recommended to our hospital executives for selection.
Key learnings: Results from the nurse shift surveys were overwhelmingly positive, with 270 responses, 99% of which supported the adoption of the new pump. Additionally, 100% of respondents indicated the pumps adequately supported the complexity of their patients' infusion needs. The pumps met critical care demands without altering nursing workflows, while errors and system failures decreased significantly compared to previous equipment.
Conclusion: This trial demonstrated the value of involving front-line nursing staff and ensuring rigorous control in product/equipment evaluations. The collaborative effort between nursing, leadership, biomedical, informatics, and supply chain teams contributed to the trial’s effectiveness, resulting in greater confidence in the IV pump’s safety and performance.
Like most organizations, one of the premier children’s hospitals in the United States generates a lot of data of varying types, from clinical to staffing and operations. However, these data sets are separated, preventing effective analytics. To improve workforce management and care delivery, the hospital's nursing department collaborated with the organization's data and analytics team to create a dashboard-based platform for analyzing workforce metrics and patient outcomes, aiding nursing leaders in decision-making.
This project involved multiple phases with contributions from nursing, data and analytics, the data trust office, and human resources. Key performance indicators were identified, and various data sources were aggregated to provide a comprehensive view of the nursing enterprise. The resulting platform offers automated, current, and reliable analytics on various aspects, including nursing demographics, education, survey results, staffing actuals by job group, and patient and family experience data.
The platform's usability was assessed using a modified health information technology usability evaluation scale survey, with a 29% response rate primarily from senior directors and managers. The findings showed high usability and satisfaction, indicating the dashboard is a valuable decision-support tool. Lessons learned include the need for analytics education for nurses and mid-managers, the inclusion of critical nursing-specific metrics (and the development of the data pipelines making them possible), and the integration of multidisciplinary team metrics for comprehensive nursing analytics.
Learning outcome: Explain the importance of usability in health information technology adoption.
Purpose: Healthcare teams enhanced the quality and safety of care by using a data-driven approach to improve timely documentation of weights and vital signs upon admission.
Background: Centers for Medicare & Medicaid Services (CMS) mandates require hospitals to submit electronic health record (EHR) data for inpatients’ weight and vital signs. This highlights the importance of prompt clinical documentation to determine medication doses and monitoring changes in health over time.
Methods/project milestones: In May 2023, Hartford HealthCare (HHC) received feedback from CMS which identified system-wide opportunities to improve timely documentation of weights and vital signs upon admission. Review of CMS hybrid readmission measurements began via Epic-released reports that were shared with quality leaders. In November 2023, HHC established a multidisciplinary work group to analyze data and develop strategies to increase data completeness. In January 2024, the quality team engaged with executive nursing leadership to disseminate hospital and unit-specific performance reports, initially sharing monthly data then increasing the frequency to biweekly distributions. Nursing leadership rounding addressed equipment and clinical workflow challenges. A revised policy was issued to align with requirements and workflows for weight and vital signs documentation.
In February 2024, HHC established a nursing subgroup, and best practice advisories (BPAs) were implemented to support timely EHR documentation. The subgroup monitored BPA metrics and adjusted criteria during the silent period in which BPAs did not appear to clinical end users. This allowed the subgroup to capture data and optimize BPAs accordingly. Effective March 18, 2024, BPAs displayed to nurses and patient care technicians (PCTs). Weekly monitoring of BPA performance and end user feedback were drivers to plan, do, study, and adjust.
Conclusion: CMS requirements were a catalyst to overcome logistical and technical challenges associated with obtaining weight and vital signs upon admission for all inpatients ≥18 years old. Continuous improvement was achieved at all seven acute care hospitals, with ≥90% data completeness noted. Leveraging a system approach, data, and feedback were crucial in developing sustainable solutions that meet regulatory demands while supporting quality and safe care and without compromising workflow efficiencies.
Purpose: Medication administration errors are a significant risk in nursing practice, and barcode medication administration (BCMA) has long proven to be an effective intervention in reducing these errors. This project is a retrospective analysis and program evaluation aimed at assessing the impact of mobile devices on BCMA compliance. Given that the type of device used can influence nurses' adoption of this technology, we hypothesized that the widespread use of mobile devices would significantly improve BCMA compliance rates. In 2020, a new mobile technology was introduced, enabling nurses to use their smartphones for medication administration. However, due to the COVID-19 pandemic, no formal evaluation was conducted to assess staff engagement with this device or its effect on BCMA compliance. This project addresses this gap, driven by the need to optimize technology solutions in healthcare settings.
Description: Proctor’s Framework for Program Evaluation defines a successful program based on three key outcomes: achieving the desired clinical outcomes (e.g., improved BCMA compliance), successful implementation (e.g., adoption of the technology), and long-term sustainability (e.g., cost-effectiveness). Using this framework, nurses from the emergency and mother/baby departments were surveyed to assess their adoption of mobile devices for BCMA. A comparative analysis was conducted to evaluate BCMA compliance rates before and after implementing mobile devices and compare their use with traditional computer systems. Additionally, correlations among nurses' age, years of experience, and adoption of mobile devices were examined to identify factors influencing technology acceptance in nursing practice.
Evaluation: Following the implementation of the mobile application, BCMA compliance notably increased from 87% to 93% in the emergency department and reached 98% in the mother/baby unit with mobile device usage, compared to 85% with the computer on wheels. Additionally, nurses reported no scanner issues with the mobile device, compared to a 6% scanner failure rate with computers. Correlations were identified between nurses' age and their acceptance of the device, as well as generational differences in preference for the mobile device, suggesting a greater inclination toward technological adoption among younger nursing staff (H(3)= 8.69, p=.034; rs(72)= -.235, p=.044).
Learning outcome: Integrating mobile devices into medication administration enhances patient safety by reducing errors and increasing nurse satisfaction with scanning. This project's findings underscore the importance of equipping nurses for technological advancements in health care and provide valuable insights into the impact of mobile devices on medication administration practices.
Purpose: The purpose of this presentation is to describe how one medical center successfully utilized technology and evidence-based practices to decrease fall rates.
Learning objective: At the end of this presentation, the attendee will be able to describe how technology can be utilized to improve evidence-based practice compliance with rounding and decrease falls.
Background: Falls are a common problem in hospital care, occurring at a rate of 3-5 per 1000 bed days. Falls cause patient harm and can increase direct costs over $35,000. Despite intensive research and quality improvement efforts, falls continue to be a problem. Evidence-based practices for fall prevention programs are available through AHRQ. The program’s success depends on consistent execution of appropriate patient interventions. Consistent execution of patient interventions has been enhanced with regular patient rounding by nursing. Nurse rounding has been shown to be a positive intervention in reducing falls. The aim of this quality improvement project is to use technology in promoting nurse rounding for the reduction of falls.
Description/methods: After months of gradually increasing patient falls and failing adoption of a new nurse call system, leadership of this approximate 100-bed teaching medical center decided to improve both. It was determined that the nurse call system could be programmed to remind RNs and PCTs that patient rounds needed to be completed. The nurse call technology was programmed so that a rounding button in the patient rooms could be used to register in/out each time the RN/PCT conducted rounds. If the RN or PCT did not register in within 60”, a reminder light was triggered and flashed at the patient room in the corridor. The light continued to flash until the “rounds” button was deactivated/reactivated in the patient room. Education on purposeful rounding was conducted with staff. Leadership made themselves available to model behavior and ask questions; they also developed a tool to track adoption of rounds and shared in daily huddles. Rounding adoption success was set at 70% completion per shift.
Results: At four months, adoption rates reached >80% and remained above threshold. The fall rate went from 3.92 to 1.94 with a p value of .013. Additionally, nurses found that they were able to get their work done in a more timely fashion due to fewer interruptions.
Learning objective: To discern the benefits and challenges of a multi-platform clinical decision support system and nurse driven workflow process to drive evidence-based practice.
Purpose and description: A novel informatics integration project to improve patient flow was the purpose of this quality improvement (QI) initiative. A new nurse-driven process was developed to address identification of high-need, high (acute) care (HNHU) patients’ emergency department/hospitalization (ED/H) utilization from disparate electronic platforms while facilitating remote triage (RT), in-person (IPT) nurse triage and patient navigation to care coordination. These software platforms include Microsoft Teams, CRISP Health Information Exchange, Methasoft, Epic, and Excel. For context, people with substance use disorders (PSUD) often represent a HNHU population requiring adaptive approaches to facilitate transition of care services. In a large, urban methadone clinic integrating primary care, a retrospective analysis found 23% of clinic patients were high emergency department (ED) users (4 or more ED visits per year) and 17% were extremely high ED (10 or more visits per year). High ED users had fewer onsite outpatient visits than non-high ED users: 1.44 versus 1.88.
Centers for Medicare and Medicaid Services incentivizes reducing unnecessary ED/HA to improve patient outcomes and reduce healthcare costs by increasing reimbursement for billable services. Literature indicates that there is evidence that patient navigation reduces ED visits and hospitalizations, and nurses prefer a standardized communication tool which reduces errors and is best done electronically. Evidence in the literature also supports a real-time locating system (RTLS) in healthcare settings is perceived by staff to reduce workload and increase productivity.
Preliminary outcomes/evaluation: Initial aims of engaging different staff units to communicate real-time alerts via an additional electronic Microsoft TEAMS channel was not deemed feasible in low-staffing environment undergoing construction. An adjusted workflow of systematic real-time tracking of ED/H across multiple e-notification platforms was more amenable to both patients and staff facilitating RT and IPT. This approach retained low-barrier methadone access for patients and allowed the staff to provide optimal patient experience. At the time of this writing, RT increased fivefold from week 1 (3) to week 8 (15), as did identification of rising ED/H by HNHU patients. This system allowed for the first-time integration of information from multiple software platforms to facilitate health assessment of ED/H patients while maintaining low-barrier methadone access.