NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initiative Proposal
NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initiative Proposal Student name Capella University NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initiative Proposal Professor’s Name Submission Date Data Analysis and Quality Improvement Initiative Proposal Slide 1 Hello all. My name is ______. I am a nurse at the Riverside Community Hospital. I’d like to take this opportunity to talk about a new proposed Quality Improvement (QI) initiative that I have spearheaded to minimize the occurrence of insulin-related medication errors at my facility. The initiative is a direct product of the analysis of our hospital dashboard data. The dashboard data demonstrated the existence of several near-miss medication events in the pharmacy reports. The aim of this Quality Improvement initiative is to utilize evidence-based communication along with the integration of bar-coded medication administration (BCMA) technology and interprofessional teamwork. The primary focus of this initiative is the ongoing refinement of the safety of the systems used to deliver medication and to improve the overall quality of care that is provided to our patients. Slide 2 Summary of Riverside Community Hospital Dashboard Data According to Table 01, for the Riverside Community Hospital Quality Management Department, dashboards for 2024 have been prepared using National Data Benchmarks generated by The Joint Commission (2023) and the Institute for Safe Medication Practices (ISMP) (2022). Table 01 Insulin Medication Safety Dashboard Data Metric National Benchmark 2022 Rate 2024 Rate Insulin Medication Error Rate ≤ 1.0 per 1,000 doses 3.2 per 1,000 doses 2.1 per 1,000 doses BCMA Compliance Rate ≥ 95% 74% 88% SBAR Handoff Adherence ≥ 90% 61% 79% Hypoglycemia Incident Rate < 5% inpatients 9.4% 6.8% Near-Miss Reporting Rate ≥ 80% 42% 58% Table 1 shows that while all indicators improved from 2022 to 2024, the indicators were still below the national benchmarks. The error rate for insulin as a medication had decreased from 3.2 to 2.1 for every 1000 doses. The national goal for this category is to have a rate of less than or equal to 1 for every 1000 doses. The compliance rate for the Bar Code Medication Administration (BCMA) policy increased from 74% to 88%, with a benchmark of 95% still unmet. Compliance with the SBAR (Situation, Background, Assessment, Recommendation) policy increased from 61% to 79%, with a benchmark of 90% unfulfilled. The rate of hypoglycaemia decreased from 9.4% to 6.8%, with a goal of less than or equal to 5%. Near Miss reporting increased from 42% to 58%, with a benchmark goal of 80% unfulfilled. The remaining gaps demonstrate that a more structured and enhanced quality improvement initiative is needed to reduce the gap between the hospital’s national benchmarks and performance. Slide 3 Identified Issues in Riverside Community Hospital Our dashboard findings indicate that the ordering, administering, and transferring of insulin among staff members is among the highest patient safety risks. The majority of identified patient safety risks can be attributed to: (1) the administration of the incorrect medication to the patient among the numerous interactions that comprise the administration of the medication, and (2) failure to communicate during the transfer of care among the various interactions that comprise the nurse-to-nurse handover. The failure to effectively communicate and the numerous near misses, almost exclusively attributed to the staff responsible for patient safety, suggest that there are not only communication issues, but a culture and a pronounced lack of safety among the staff of the organization (Ferreira et al., 2025). Furthermore, the evidence collected from the Dashboard Analyses is consistent with the Joint Commission Standards and the Health Canada National Patient Safety Goals- Safe Medication Administration. Evaluation of the Quality of Data The analysis of data quality uncovered strengths and weaknesses of dashboard data. Of the metrics, the eHealth record and trend data corroborated the dashboard data, which validated the internal quality management records. Currently, near-miss reporting shows 58%. This means that the actual errors that occurred are probably much less than what has been reported. Underreporting has been consistently identified by hospitals as a patient safety problem. This could be attributed to an employee being scared of retaliation in the form of punitive measures or the lack of an effective reporting system (Braiki et al., 2024). This does suggest that the reported insulin error rate is likely a gross underestimate, and corroborates the case for immediate and sustained QI initiatives. Slide 4 Outline a Quality Initiative Proposal The insulin safety bundle QI initiative contains combined QI effort data from the dashboard, as well as root cause analysis data from a near-miss incident. The specific objectives of this initiative are: To reduce the rate of insulin medication errors to ≤ 1.0 errors per 1,000 doses. To achieve an increase in BCMA compliance to ≥ 95% To achieve an increase in compliance with the SBAR handoff standard to ≥ 90% in the next 12 months. QI initiative is consistent with the Joint Commission and ISMP standards. The QI initiative will be guided by the Plan-Do-Study-Act (PDSA) model. The PDSA model is the most utilized iterative testing process model prior to the full-scale adoption of an intervention. The reason for the popularity of this model is the small “test of change” that is suggested, which allows the organization to evaluate the data and make informed changes in the organization as a result of what is learned (Albaadani et al., 2024). This initiative will be implemented in the two hospital units over a 30-day planning and training phase, and will continue to be tested for the 90-day PDSA cycle, followed by a six-month implementation with continuous data collection. The bundle strategies will utilize evidence-based methods to improve insulin safety. All shift changes will standardize communication using SBAR, along with an insulin-specific checklist for all insulin patients. Multiple studies suggest SBAR communicates clinically with a 77-100% handoff accuracy rate (Hidalgo-Tapia et al., 2025). As a no-exception rule, the independent double-check of insulin delivered by two licensed nurses will remain in place for the administration of all insulin doses. The electronic



