Statistical Control Research Articles

ARIMA MODEL VERIFICATION WITH OUTLIER FACTORS USING CONTROL CHART

Control charts are often used in quality control processes, especially in the industrial sector because of their significant benefits in increasing industrial production. However, control charts can also be used throughout the field of time series modeling to evaluate measures of accuracy represented by a particular time series model. The application of control charts in this research meets the criteria for evaluating accuracy. However, it is not certain that the time series model will have a high level of accuracy. There are various factors that can influence this phenomenon, one of which is the potential for outliers. Therefore, it is very important to perform time series modeling by adding an outlier factor. The residuals of the time series model obtained are used to create a control chart for model verification. The aim of this research is to evaluate the validity of time series models by looking at the influence of outlier characteristics to improve their accuracy. This research studies the accuracy of a time series model built using Gross Domestic Product (GDP) data in Indonesia. There are two different models, namely the ARIMA model without outlier factors and the ARIMA model with outlier factors which are used for research purposes. Both models were performed using the same data set. The results of this study indicate that the ARIMA model with outlier factors has better accuracy than the ARIMA model without outlier factors. This conclusion can be drawn based on the observation that the residual value is within the predetermined control limits, thus indicating that the process is in a state of statistical control.

Analisis Mutu Fisik, Kimia, dan Organoleptik Kacang Ercis Goreng dengan Pendekatan SPC (Statistical Process Control) dan PCA (Principal Component Analysis)

<em>The study aims to analyze the consistency of the quality of fried peas with statistical process control aids. Samples were taken daily for 28 days from a nut frying business. The quality of samples including color, free fatty acid, peroxide value, and organoleptic is tested daily with 5 repetitions. Quantitative quality consisting of color, moisture content, free fatty acids, and peroxide value is analyzed with SPC while organoleptic quality is analyzed with PCA. Analysis with SPC results in an upper control limit and a lower control limit of 68.6%; 25;4; 43.7 and 37.7; 8,7; 22.6 for L*, a*, and b*, 2.275% and 2.072% for moisture content, 0.628% and 0.145% for free fatty acids, and 1.075 mEqO2/kg and 0.079 mEqO2/kg for peroxide value. Based on the upper control limit and the lower control limit, pea quality is inconsistent for variable moisture content, free fatty acids, and peroxide value. Analysis of PCA color, moisture content, free fatty acids, peroxide value, and sensory products did not show certain grouping and clustering patterns, which meant the samples were relatively the same as each other. Even though the variables of water content quality, free fatty acids, and peroxide value of fried peas are inconsistent, they are not detected by panelists. The causative factors of quality deviation can be known with certainty by examining each factor listed in the fishbone diagram. In addition, monitoring also needs to be done routinely and closer to the production process to find out exactly the cause of product quality deviations.</em>

TEMPORAL ANALYSIS AND PREDICTIVE MODELING OF AMBIENT AIR QUALITY IN HULU LANGAT DISTRICT, SELANGOR, MALAYSIA: A CHEMOMETRIC APPROACH

One of the most important environmental problems facing the globe today is air pollution. The centre area for the local populace is the Hulu Langat district, which borders Kuala Lumpur, the capital. The purpose of this study is to look at how the ambient air quality varies in Hulu Langat, Selangor. The Air Quality Division of the Malaysian Department of Environment provided five years' worth of secondary data on the air quality at Hulu Langat. The database included five primary air pollutant characteristics sulphur dioxide (SO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and particulate matter with a diameter of 10 microns or less (PM10), in addition to data from the Air Pollutant Index (API). Chemometric analysis was used to examine the results. According to the results, SO2, NO2 and PM10 had the greatest correlations with API readings. A statistical process known as statistical control (SPC) showed that certain PM10 values were over national recommendations and control limits. The artificial neural network method's air quality prediction model demonstrated good accuracy with real data (R2 = 0.9). The results of this investigation indicated a strong correlation between the Hulu Langat air quality data. In order to achieve sustainable environmental practices in the future, it is imperative to engage in extensive collaboration across environmental departments and relevant authorities and engage in continuous monitoring of air quality.

GJ Express: an improvement initiative to decrease sedation and anesthesia for gastrojejunostomy tube exchanges.

Overuse of sedation and anesthesia causes delays in gastrojejunostomy tube (GJ) exchanges, increased risk of complications, unnecessary use of resources, preventable hospital admissions, and an adverse impact on patient and family experience. Our hospital was over-utilizing sedation and anesthesia, and we aimed to decrease this use from 78% to 20% within two years. An interdisciplinary quality improvement team comprehensively evaluated current processes for GJ tube exchanges through a retrospective chart review for baseline data with prospective time series analysis after improvement implementation. The primary outcome measure was the percentage of pediatric patients that utilized sedation or anesthesia for routine GJ tube exchanges. A statistical process control p-chart was used to calculate and show changes over time for patients (n = 45 patients average). The median percent of pediatric GJ tube exchanges performed with sedation or anesthesia decreased from 77.8% to 11.3%. Most patients (76%) were covered by Medicaid programs; with low reimbursement rates, decreased anesthesiologist billing revenue does not have a negative financial impact. An interprofessional improvement initiative that engaged patients and families, incorporated pediatric-specific staff services, and developed systematic weaning was associated with a significant decrease in the overuse of sedation and anesthesia for GJ tube exchanges. We believe that this work is highly relevant and impactful for medical centers caring for children who require gastrojejunostomy tubes, an increasingly common approach to management of children with feeding issues. There is very little literature available on the use of sedation or anesthesia for changing these tubes. While large children's medical centers in the USA usually do not utilize sedation or anesthesia, there are likely many serious outliers, especially when children receive care outside of a pediatric specific institution. This paper brings awareness to this serious issue and provides information about how we changed care to achieve higher patient safety and lower medical costs.

Analysis of Employee Work Quality Using Statistical Process Control and Compliance with Standard Operating Procedures (Study in the Merchandise Inspection Department of the Foodhall Senayan City)

The objective of this research is to evaluate the effectiveness of employee performance in implementing Standard Operating Procedures (SOP) within the Merchandise Inspection/Receiving Department at The Foodhall Senayan City. This research is of a qualitative descriptive nature, with a focus on Statistical Process Control (SPC) as a measurement instrument. It employs the Implementation of Seven Key Elements in SOP, covering efficiency, consistency, error minimization, problem-solving, and defensive limitations. Five individuals participated in this research: Branch Manager, Receiving Supervisor, and three Receiving Staff members. Data collection techniques were based on direct observation, interviews, and documents used as references for the receiving staff's work procedures. In this study, the author used Statistical Process Control (SPC) on Attribute Control Charts, specifically using P-charts as a measurement tool for Quality Control checks on goods. The Implementation of Seven Key Elements in SOP was used to deepen the investigation into problem-solving that could not be explained using numerical data. Based on the analysis results using Statistical Process Control (SPC) for the current period, the average reversal rate is 0.02, indicating proximity to the Lower Control Limit (LCL) of 0 or zero defects. Meanwhile, regarding the usage of the Implementation of Seven Key Elements in SOP in the Merchandise Inspection/Receiving Department at The Foodhall Senayan City, it is evident that in the implementation of these seven key elements, there are still some shortcomings. These deficiencies include error minimization, process mapping, employee protection, and defensive limitations.

Homogeneously Weighted Moving Average Control Charts: Overview, Controversies, and New Directions

The homogeneously weighted moving average (HWMA) chart is a recent control chart that has attracted the attention of many researchers in statistical process control (SPC). The HWMA statistic assigns a higher weight to the most recent sample, and the rest is divided equally between the previous samples. This weight structure makes the HWMA chart more sensitive to small shifts in the process parameters when running in zero-state mode. Many scholars have reported its superiority over the existing charts when the process runs in zero-state mode. However, several authors have criticized the HWMA chart by pointing out its poor performance in steady-state mode due to its weighting structure, which does not reportedly comply with the SPC standards. This paper reviews and discusses all research works on HWMA-related charts (i.e., 55 publications) and provides future research ideas and new directions.

DISPARITY ANALYSIS OF THE LEARNING PROCESS OF ISLAMIC RELIGIOUS EDUCATION IN BANGKA BELITUNG PROVINCE: APPLICATION OF STATISTICAL PROCESS CONTROL (SPC)

The problem of disparity in the learning process between Madrasahs is one of the contributors to the low quality of Madrasahs. To get the quality of learning, variability in the learning process needs to be suppressed to a minimum. Variability in the learning process can be in the form of differences in teacher competence, availability of learning facilities or facilities, financial capabilities of Madrasah, and socio-cultural factors of the Madrasah environment. Using a quantitative approach, this study aims to analyze the disparity in the learning process between Madrasah Aliyah (MA) in Bangka Belitung Province based on the achievement of UAMBN scores. Data analysis using the Statistical Processes Control (SPC) method with statistical techniques T2. The SPC method generates a control chart that will be used to determine if there is a disparity among Madrasah. The results of data analysis show that there is a disparity in the learning and teaching process at MA in Bangka Belitung Islands Province based on UAMBN's achievements in three subjects (Qur'an Hadith, Fiqh, and Islamic Cultural History). Some things that can be done by related parties to reduce disparities are, 1) coaching all human resources (teachers and education staff) gradually, 2) equitable distribution of the number and quality of teachers, both in public and private, 3) controlling the admission of prospective students so that there is no inequality of interest, and 4) striving for proportional distribution of financial aid for each MA.

Impact of virtual care on planned rechecks in a pediatric emergency department: a quality improvement project.

In the absence of accessible urgent follow-up options, emergency physicians may use an in-person recheck (planned return visit) to the Emergency Department (ED) as a safety net for discharged patients. In-person rechecks require travel, triage, and waiting time for patients and families and contribute to ED census. Many of these visits do not result in further investigation or changes in management but can provide reassurance for the family and care providers. We aimed to reduce the volume of in-person rechecks to our ED through an urgent virtual follow-up process. We conducted a quality improvement project using iterative process mapping and Plan-Do-Study-Act cycles to develop and implement a new model of care for virtual rechecks. An interdisciplinary team tested and refined the virtual care process from December 2020 to June 2022. Outcome, process and balancing measures were tracked continuously and analyzed using statistical process control. Baseline data revealed that the majority of in-person rechecks were for young infants with bronchiolitis. Post-implementation of the new process, 50% of all virtual rechecks were for respiratory illnesses. Use of virtual rechecks increased steadily to an average of 6.5 per 1000 ED visits with 58% of all rechecks now completed virtually. The number of in-person rechecks did not decrease during the study period. Virtual rechecks triggered an in-person ED visit in 5.2% of virtual recheck instances. There was no increase in unplanned return ED visits or admissions after implementation of virtual rechecks. Virtual rechecks can be safely implemented to allow urgent reassessment of patients following an ED visit. Virtual rechecks could be a useful tool for addressing planned reassessments in the pediatric ED, especially during surges of respiratory illness.

Comments on the Effects of Variables’ Magnitude of Process Changes and Standard Deviations in “Adaptive Multivariate Statistical Process Control for Monitoring Time-Varying Processes”

Comments on the Effects of Variables’ Magnitude of Process Changes and Standard Deviations in “Adaptive Multivariate Statistical Process Control for Monitoring Time-Varying Processes”

Risk adjustment-based statistical control charts with a functional covariate

ABSTRACT In real applications, there are situations in which quality characteristics are significantly affected by function-valued covariates such as electrocardiogram (ECG) signals; however, previous surveillance methods with covariate adjustment mainly use scalar-valued covariates to construct control charts to investigate the stability of nonindustrial processes, such as in the medical and public health fields. Few existing approaches address the infinite-dimensional regression encountered with function-valued covariates. Thus, an applicable scheme needs to be developed. Here, by relaxing the assumption of normality, a novel surveillance strategy for functional logistic regression (FLR) is proposed. In this approach, the response is a binary variable, and the covariate information is obtained from functional data. To address the above problems, functional principal component analysis (FPCA) is used to extend the score test to situations with functional covariates. Moreover, the score statistic is integrated into an exponentially weighted moving average (EWMA) charting scheme to detect abnormal changes in the location and scale parameters based on additional information. The simulation results show that the proposed approach is more efficient than previous approaches in detecting small to moderate shifts. Finally, the proposed charting scheme is applied to a real case study to demonstrate its utility and applicability.

Statistical Applications in Pharmaceutical Product Development: A Comprehensive Review

The pharmaceutical industry often depends on statistics to improve product quality, optimize the compositions, streamline operations, and conform to regulatory requirements. In Bio Equivalency investigations, Statistics plays an integral role in decision-making while demonstrating the similarity between the test and reference products. In this review, we explore how statistics play a crucial role in pharmaceutical product development. We start with examining experiments, where statistics help scientists find the best combinations of ingredients and manufacturing conditions. We explored different types of experiments, like factorial designs, Plackett-Burman designs, Box-Behnken designs, and Taguchi designs. While optimizing the formulations and process parameters, these methodologies assist researchers in making meaningful conclusions supported by statistical inference. The next sections include Response Surface Methodology (RSM) and Mixture Designs, which help in the development of drug formulations and the comprehension of complex responses. The development of pharmaceuticals is made simpler by these approaches. Then, we examine optimal designs like A-optimal, I-optimal, and D-optimal. A-optimal designs save resources, I-optimal designs focus on precise estimates, and D-optimal designs are great for screening and getting accurate results. These designs help scientists make decisions based on data. The starting point for demonstrating dissolution similarity between generic and reference products is the statistical approach. This paper examines the use of model-dependent techniques, such as zero-order, first-order, Higuchi, and Weibull models, and model-independent techniques such as F1, F2, Bootstrap, MSD, and PCA techniques, it analyzes important parameters and bounds that are essential for determining the dissolution similarity. In the field of biostatistics, we discuss how statistics ensures that generic drugs are safe and work just as efficiently as brand-name drugs. Both regulatory approval and patient safety rely on this. We briefly discuss statistical process control (SPC) in closing. SPC checks that drugs/drug products are consistently of quality using graphs and figures. It facilitates the production of consistently effective pharmaceuticals by organizations. Advanced statistical techniques, including data mining, machine learning, and artificial intelligence, are revolutionizing the pharmaceutical industry. These tools enhance drug discovery, optimize manufacturing processes, and pave the way for personalized medicine. As real-time monitoring and predictive analytics become integral, the future holds exciting possibilities for improving patient outcomes. This review shows how statistics are like a guiding tool in the pharmaceutical industry. Whether it's in the lab or in manufacturing, statistics play a big role in making sure patients get the best medicines possible.

Quality analysis of BCG vaccine for bladder cancer immunotherapy using Shewhart control charts

SCIENTIFIC RELEVANCE. The complexity of standardising immunobiologicals, including bacillus Calmette–Guérin (BCG) vaccines, requires improving the approach to statistical analysis of consistency in their quality indicators. Quality analysis tools include Shewhart control charts, which can be used for real-time and retrospective identification and analysis of trends in the processes of interest.AIM. This study aimed to analyse quality indicators of a BCG vaccine for bladder cancer immuno­therapy using Shewhart control charts to monitor consistency in manufacturing processes and quality testing of vaccines.MATERIALS AND METHODS. The study involved a retrospective analysis of the bacterial concentration, dispersity index, loss-on-drying, and potency data obtained during the quality control of Imuron-vac, a BCG vaccine for bladder cancer immunotherapy, in the past 5 years. As part of the statistical data analysis, the authors calculated the means, investigated the corre­lation between the test results provided by the manufacturer and the quality control results obtained at the testing centre (TC), and checked the distributions for normality. Individuals and moving range control charts were plotted and analysed for each quality indicator.RESULTS. The correlation coefficients (r) ranged from 0.34 to 0.70 for the data submitted by the manufacturer and the data obtained at the TC. Pearson’s goodness-of-fit test showed that the distribution of the quality control results obtained at the TC was normal, with χ2 = 14.03 for the dispersity index values and χ2 = 4.93 for the loss-on-drying measurements. Shewhart control charts for loss-on-drying and potency data suggested that the production process and/or the testing process deviated from the state of statistical control. Consistency monitoring of the bacterial concentration and the dispersity index showed that the state of statistical control was achieved. The authors established control limits for further real-time monitoring of the dispersity index consistency.CONCLUSIONS. Shewhart control charts are applicable to the quality control of BCG vaccines for bladder cancer immunotherapy at the TC. Continuous monitoring of consistency in quality indicators is needed to improve the standardisation of vaccine production processes and testing methods, as this standardisation will result in high product quality.

Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments’ carbon reduction policies

Across the globe, governments are developing policies and strategies to reduce carbon emissions to address climate change. Monitoring the impact of governments’ carbon reduction policies can significantly enhance our ability to combat climate change and meet emissions reduction targets. One promising area in this regard is the role of artificial intelligence (AI) in carbon reduction policy and strategy monitoring. While researchers have explored applications of AI on data from various sources, including sensors, satellites, and social media, to identify areas for carbon emissions reduction, AI applications in tracking the effect of governments’ carbon reduction plans have been limited. This study presents an AI framework based on long short-term memory (LSTM) and statistical process control (SPC) for the monitoring of variations in carbon emissions, using UK annual CO2 emission (per capita) data, covering a period between 1750 and 2021. This paper used LSTM to develop a surrogate model for the UK’s carbon emissions characteristics and behaviours. As observed in our experiments, LSTM has better predictive abilities than ARIMA, Exponential Smoothing and feedforward artificial neural networks (ANN) in predicting CO2 emissions on a yearly prediction horizon. Using the deviation of the recorded emission data from the surrogate process, the variations and trends in these behaviours are then analysed using SPC, specifically Shewhart individual/moving range control charts. The result shows several assignable variations between the mid-1990s and 2021, which correlate with some notable UK government commitments to lower carbon emissions within this period. The framework presented in this paper can help identify periods of significant deviations from a country’s normal CO2 emissions, which can potentially result from the government’s carbon reduction policies or activities that can alter the amount of CO2 emissions.

Surveying Quality Management Methodologies in Wooden Furniture Production

Furniture production is a specific industrial sector with a high human labor demand, a wide range of materials processed, and short production runs caused by high customization of end products. The difficulty of measuring the aesthetic requirements of customers is also specific to furniture. This review of academic papers identifies and explains effective quality management strategies in furniture production. The reviewed literature highlights a range of quality management methodologies, including concurrent engineering (CE), total quality management (TQM), lean manufacturing, lean six sigma, and kaizen. These strategies encompass a variety of pro-quality tools, such as 5S, statistical process control (SPC), quality function deployment (QFD), and failure mode and effects analysis (FMEA). The strengths of these quality management strategies lie in their ability to enhance efficiency, reduce waste, increase product diversity, and improve product quality. However, the weaknesses concern implementation challenges and the need for culture change within organizations. Successful quality management in furniture production requires tailoring strategies to the specific context of the furniture production industry. Additionally, the importance of sustainability in the furniture industry is emphasized, which entails incorporating circular economy principles and resource-efficient practices. The most important finding from the literature analysis is that early detection and correction of poor quality yields the most beneficial outcomes for the manufacturer. Therefore, it is essential to strengthen the rigor of quality testing and analysis during the early stages of product development. Consequently, a deep understanding of consumer perspectives on required furniture quality is crucial. The review identified two research gaps: (1) the impact of unnecessary product over-quality on the efficiency of furniture production and (2) the influence of replacing CAD drawings with a model-based definition (MBD) format on quality management in furniture production.

Analysis of Furniture Product Quality Control with Statistical Quality Control Methods and Failure Mode and Effect Analysis

PT. Tjakrindo Mas is a manufacturing company based in Indonesia that supports the government, industrial, public, and private sectors. Established in 1984, the company produces home furniture made from various types of wood. During the period from December 2023 to May 2024, the company faced production issues with its furniture products. According to production scheduling data, the furniture production intensity was high, operating 5 days a week. During this period, the highest production rate was for the 2 Door Glass Wardrobe, totaling 5,638 units. However, despite the high production volume, the defect rate for the 2 Door Glass Wardrobe was also high, with 498 defective units, representing a defect rate of 8.83%, which exceeds the company's tolerance standard. The objective of this study is to assess the quality of the Glass Wardrobe product at PT. Tjakrindo Mas and to propose improvements to enhance the product quality. Observations identified that the highest Risk Priority Number (RPN) was associated with the close side rail rupture defect, caused by the operator not being careful when installing the close side rail to the cabinet body, and the work methods used not in accordance with the Standard Operating Procedure (SOP). Recommendations for quality control proposals based on the high RPN value of FMEA Close Side Rail Rupture is to provide supervision and guidance to workers, and Provide briefing to operators about methods that are in accordance with the standard operating procedures (SOP) used by the company.

Use of statistical process control in quality improvement projects in abdominal surgery: a PRISMA systematic review

BackgroundThe use of quality improvement methodology has increased in recent years due to a perceived benefit in effectively reducing morbidity, mortality and length of stay. Statistical process control (SPC) is...

Single-shot liposomal bupivacaine in place of rectus sheath catheters to provide non-opiate analgesia after laparotomy: a quality improvement project to reduce the need for ongoing nursing input

Opioid-sparing pain management is an integral component of enhanced recovery after colonic and rectal surgery. In our hospital, rectus sheath catheters (RSCs) are routinely placed during emergency laparotomy for colorectal...

Implementing American Academy of Neurology Quality Measures in Antigua Using Quality Improvement Methodology.

The American Academy of Neurology has developed quality measures related to various neurologic disorders. A gap exists in the implementation of these measures in the different health care systems. To date, there has been no electronic health care record nor implementation of quality measures in Antigua. Therefore, we aimed to increase the percent of patients who have epilepsy quality measures documented using standardized common data elements in the outpatient neurology clinic at Sir Lester Bird Medical Center from 0% to 80% per week by June 1, 2022 and sustain for 6 months. We used the Institute for Health care Improvement Model for Improvement methodology. A data use agreement was implemented. Data were displayed using statistical process control charts and the American Society for Quality criteria to determine statistical significance and centerline shifts. Current and future state process maps were developed to determine areas of opportunity for interventions. Interventions were developed following a "Plan-Do-Study-Act cycle." One intervention was the creation of a RedCap survey and database to be used by health care providers during clinical patient encounters. Because of multiple interventions, we achieved a 100% utilization of the survey for clinical care. Quality improvement (QI) methodology can be used for implementation of quality measures in various settings to improve patient care outcomes without use of significant resources. Implementation of quality measures can increase efficiency in clinical delivery. Similar QI methodology could be implemented in other resource-limited countries of the Caribbean and globally.

Decreasing Pain in Hospitalized Patients by Increasing Topical Anesthetic Use for Peripheral IVs.

Venous access is a common source of pain for hospitalized patients. Topical anesthetics are effective at decreasing needle pain, can improve success rate, and decrease procedure time; however, use before peripheral intravenous line (PIV) placement is inconsistent. The aim was to reduce pain experienced by hospitalized pediatric patients by increasing topical anesthetic use for PIV placement from a mean of 11% to 40% within 6 months. The Model for Improvement was utilized. An institutional clinical pathway and PIV order panel were developed. Pre-checked orders for topical anesthetics were added to order sets. Visual aids were placed on IV carts, including reminders for anesthetics, pathway use and scripting examples. Nurses received individual feedback. Statistical process control charts were posted weekly on daily management system boards on medical-surgical floors, and data were shared at daily nursing huddles to increase awareness of performance and discuss opportunities for improvement. Topical anesthetic use for PIV placement increased from a mean of 11% to 46%. Documentation of comfort measures during PIV placement increased from a mean of 6% to 13%. The percentage of PIV placements with an order for a topical anesthetic in the electronic health record increased from a mean of 14% to 54%. PIV procedures with documentation of placement attempts increased from a mean of 47% to 70%. Through systems and culture change, awareness of the importance of pain prevention for venous access procedures increased, and patient-centered care improved with greater collaboration between nurses, providers, and families for venous access planning.

Reducing Falls in Hospitalized Children and Adolescents with Cancer and Blood Disorders: A Quality Improvement Journey.

Falls in hospitalized pediatric patients represent a serious patient safety concern. Children and adolescents with cancer and blood disorders have inherent risk factors that increase the likelihood of injury from falls. The Hematology/Oncology (HO) and Stem Cell Transplant (SCT) inpatient units at Boston Children's Hospital embarked on a multiyear quality improvement journey to reduce inpatient falls in this population. A targeted Falls Reduction Task Force implemented key initiatives between 2020 and 2023. These include enhancing communication strategies to heighten awareness of the highest fall-risk patients, conducting a formal apparent cause analysis on every fall with injury, and initiating a physical therapy-led program to reduce deconditioning. Outcome measures were total falls, rate of preventable falls with injury per 1000 patient days, and days between preventable falls with injury. Our quality improvement team used statistical process control charts to track changes over time. The combined rate of preventable falls with injury per 1000 patient days decreased from 0.63 in fiscal year (FY) 2020 to 0.25 in 2023. The SCT and HO units achieved a maximum of 442 days and 410 days, respectively, between preventable falls with injury in 2021-2023, compared with 124 and 117 days in 2020. The two units observed a 51% reduction in total falls over 4 years. A multifaceted fall reduction quality initiative effectively reduced preventable falls with injury on pediatric HO and SCT inpatient units, thereby reducing avoidable harm in a vulnerable patient population.