Statistical Process Control Methodology Research Articles

Reducing intravenous antibiotics in neonates born ≥35 weeks' gestation: A quality improvement study.

To assess the impact of the Early Onset Sepsis (EOS) calculator, implemented as a quality improvement study, to reduce the rate of unnecessary antibiotics in neonates born ≥35 weeks' gestation. An audit of routinely collected hospital data from January 2008 to March 2014 (retrospective) and from January 2018 to September 2019 (prospective) determined baseline incidence of EOS intravenous antibiotic use in neonates born ≥35 weeks' gestation in a tertiary level perinatal centre. Plan-do-study-act (PDSA) cycles were applied to implement the EOS calculator. Statistical process control methodology and time series analysis assessments were used to assess the potential impact of the PDSA cycles on the rate of intravenous antibiotics, blood culture collection, EOS, length of stay and health care costs (not adjusted for potential confounders). In the study population, from January 2008 to March 2014, the baseline incidence of intravenous antibiotic use was 10.49% (2970/28290), whilst only 0.067% (19/28290) neonates had culture proven EOS. From January 2018 to October 2019, prior to implementation of the EOS calculator, 13.3% (1119/8411) neonates were treated with intravenous antibiotic and the use decreased to 8.3% (61/734) post-implementation. The rate of blood culture collection decreased from 14.4% (1211/8411) to 11.9% (87/734). There were no cases of missed EOS. Length of stay decreased from 2.68 to 2.39 days, with an estimated cost saving of $366 per patient per admission. Implementing the EOS calculator in a tertiary hospital setting reduced invasive investigations for EOS and intravenous antibiotic use among neonates ≥35 weeks' gestation. This can result in reduced length of neonatal hospital stays, and associated health care cost savings and may reduce separation of mother and baby.

Enhanced recovery program in ambulatory pediatric urology: A quality improvement initiative

Enhanced Recovery After Surgery (ERAS) was established in 2001 for adult patients undergoing complex procedures. ERAS in adult ambulatory surgery later followed with similar positive outcomes. For the pediatric population, ERAS implementation has shown promising results in complex surgeries such as bladder reconstruction. Its application in pediatric ambulatory surgery has only recently been reported. We hereby report a Quality Improvement initiative in implementing an Enhanced Recovery Protocol (ERP) for pediatric urology in an ambulatory surgery center. A project was launched to evaluate and implement enhanced recovery elements into an institutional Enhanced Recovery Protocol (ERP). These included reliance on peripheral nerve blocks for all inguinal and genital cases and reduction of opioids intraoperatively and postoperatively. Improvements were placed into a project plan broken into one preparation phase to collect baseline data and three implementation phases to enhance existing and implement new elements. The implementation phase went through iterative Plan-Do-Study-Act (PDSA) cycles for all sub-projects. Team countermeasures were based on available evidence. A consensus process was used to resolve disagreement. Monthly meetings were held to share real-time data, gather new feedback, and modify plans as needed. The primary outcome measures selected were percent intraoperative opioid use, percent opioid prescribing, mean PACU length of stay, and average number of opioid doses prescribed. Secondary outcome measures were mean maximum pain score in PACU, PACU rescue rate for PONV, and patient/family satisfaction scores. Post-implementation data for 18 months was included for evaluation. Statistical process control methodology was used. The total number of participants was 3306: 561 (baseline), 220 (Phase 1) 356 (Phase 2) and 527 (Phase 3), 1642 (post-implementation). Intraoperative opioid use was eliminated in >99% of cases. Post-operative opioid prescribing was reduced from 30% to 15% of patients. The number of opioid doses was also reduced from an average of 7.6 to 6.1 doses. There was no change for the mean maximum pain score in the recovery room despite elimination of opioids. Patient/family satisfaction scores were high and sustained throughout the period of study (9.8/10). Balancing measures such as return to the operating room within 30 days and return to the emergency department within 7 days were unchanged. This QI project demonstrated the feasibility of a pediatric enhanced recovery protocol in a urology ambulatory surgery setting. With implementation of this protocol, intraoperative opioid use was virtually eliminated, and opioid prescribing was reduced without affecting pain scores or post-operative complications.

Improving anthropometric measurements in hospitalized children: A quality-improvement project.

The objective of this quality-improvement project was to increase documentation rates of anthropometrics (measured weight, length/height, and body mass index [BMI], which are critical to identify patients at malnutrition (undernutrition) risk) from <50% to 80% within 24 hours of hospital admission for pediatric patients. Multidisciplinary champion teams on surgical, cardiac, and intensive care (ICU) pilot units were established to identify and iteratively test interventions addressing barriers to documentation from May 2016 to June 2018. Percentage of patients with documented anthropometrics <24 h of admission was assessed monthly by statistical process control methodology. Percentage of patients at malnutrition (undernutrition) risk by anthropometrics was compared by χ2 for 4 months before and after intervention. Anthropometric documentation rates significantly increased (P < 0.001 for all): BMI, from 11% to 89% (surgical), 33% to 57% (cardiac), and 16% to 51% (ICU); measured weight, from 24% to 88% (surgical), 69% to 83% (cardiac), and 51% to 67% (ICU); and length/height, from 12% to 89% (surgical), 38% to 57% (cardiac), and 26% to 63% (ICU). Improvement hospital-wide was observed (BMI, 42% to 70%, P < 0.001) with formal dissemination tactics. For pilot units, moderate/severe malnutrition (undernutrition) rates tripled (1.2% [24 of 2081] to 3.4% [81 of 2374], P < 0.001). Documentation of anthropometrics on admission substantially improved after establishing multidisciplinary champion teams. Goal rate (80%) was achieved within 26 months for all anthropometrics in the surgical unit and for weight in the cardiac unit. Improved documentation rates led to significant increase in identification of patients at malnutrition (undernutrition) risk.

Mapping pre-consumer food waste in quick service restaurants on a university campus: Two Australian case studies

Mapping and monitoring the process of pre-consumer food waste generation in the foodservice sector is needed to fully understand food waste, identify hotspots, and strengthen the evidence-base in this sector of the food supply chain. The purpose of this study was to validate a tool for separation and quantifying pre-consumer food waste in a quick service restaurant (QSR) setting, and to map the food waste generation process using statistical process control methodology. This included consideration of food waste categories and edible versus inedible waste. The study also explored key foodservice and menu practices which may impact food waste production. Food waste audits were undertaken in two food outlets (FOs) in an Australian university campus over a two-week operating period for each outlet using a direct weighing method. Foodservice operation and menu practices occurring in the outlets during the audit period were also recorded. These observations validated practices reported by the owner-manager of the FOs during interviews. The amount of waste collected separately from each outlet was analysed using statistical process control methodology. While each FO was treated as a separate case study, the same methodology was applied to each, allowing some comparison between outlets. Despite differences in foodservice style and menus, the average daily pre-consumer food waste produced from all food waste categories was approximately 25 kg for both outlets, with about 60% from inedible waste. This equated to approximately 5.5–6.1 kg of pre-consumer waste per full-time-equivalent employee (FTE) per day. Used coffee grounds was the largest single contributor of total pre-consumer waste for both FOs. Both FOs demonstrated compliance with Australian best practice in foodservice operations and menu design. The study concludes that the method used to separate pre-consumer food waste into different categories and quantify this waste was a practical tool for these QSRs and allowed researchers to validate both the separation process and the amount of waste collected. Analysis of data using statistical process control allowed differentiation between common and special cause of variations. These findings can help inform processes which generate food waste in these types of foodservice settings and assist with the development of food waste reduction initiatives.

Evaluation of Remotely Piloted Aircraft for Agricultural Spraying in Corn Cultivation in the Brazilian Savannah

This study aimed to evaluate the quality of application using both RPA and ground techniques in corn cultivation using different spray nozzles in Brazilian savannah (Cerrado). The experiment was conducted using a completely randomized design, with four treatments and eight repetitions. The treatments involved two methods of application: aerial (RPA, 10 L ha-1) and ground (backpack sprayer, 100 L ha-1); and two types of nozzles: the standard flat fan nozzle XR 11001 and the air induction flat fan nozzle AirMix 11001. To study the quality of the application, the deposition was evaluated using a tracer and spectrophotometry, and the droplet spectrum, evaluated through the analysis of water-sensitive paper. Furthermore, a study on application quality was conducted using the Statistical Process Control methodology. The results demonstrated that with RPA, the deposition was higher, and the AirMix 11001 nozzle also stood out in this variable. No non-random behavior was observed in the deposition. Ground application showed the best performance in terms of target coverage and droplet density. The XR 11001 nozzle resulted in a higher droplet density. Overall, the XR11001 nozzle and the RPA application showed smaller volume median diameters (VMDs), indicating a higher potential for drift, which should be taken into account. Given the results obtained, it can be stated that the use of RPAs for agricultural spraying is viable for application.

Use of Unmanned Aerial Vehicle for Pesticide Application in Soybean Crop

The use of unmanned aerial vehicles (UAVs) for pesticide application has increased substantially. However, there is a lack of technical information regarding the optimal operational parameters. The aim of this study was to evaluate the quality of pesticide application on a soybean crop using a UAV employing different spray nozzles. The experiments were conducted using a completely randomized design with four treatments and eight repetitions. The trial was conducted in a soybean growing area during the soybean reproductive stage (1.1 m tall). The treatments included aerial application (rate: 10 L hm−2) using an Agras MG1-P UAV with XR 11001 (flat fan), AirMix 11001 (air-induction flat fan), and COAP 9001 (hollow cone spray) nozzles; for comparison, ground application (rate of 100 L hm−2) using a constant pressure knapsack sprayer with an XR 110015 (flat fan) nozzle was performed. The deposition was evaluated by quantifying a tracer (brilliant blue) using spectrophotometry and analyzing the droplet spectrum using water-sensitive paper. Furthermore, the application quality was investigated using statistical process control methodology. The best deposition performance was exhibited by the application via UAV using the COAP 9001 and AirMix 11001 nozzles. For all the treatments, the process remained under statistical control, indicating commendable adherence to quality standards. The aerial application provided greater penetration of the spray into the crop canopy. With the use of the UAV, the coverage on the water-sensitive paper was &lt;1%; moreover, the AirMix 11001 and XR 110015 nozzles had the lowest drift potential.

Addressing knowledge gaps in Surgical Safety Checklist use: statistical process control analysis of a surgical quality improvement programme in Ethiopia.

The WHO Surgical Safety Checklist reduces morbidity and mortality after surgery, but uptake remains challenging. In particular, low-income countries have been found to have lower rates of checklist use compared with high-income countries. The aim of this study was to determine the impact of educational workshops on Surgical Safety Checklist use implemented as part of a quality improvement initiative in five hospitals in Ethiopia that had variable experience with the Surgical Safety Checklist. From April 2019 to September 2020, each hospital implemented a 6-month surgical quality improvement programme, which included a Surgical Safety Checklist workshop. Statistical process control methodology was used to understand the variation in Surgical Safety Checklist compliance before and after workshops and a time-series analysis was performed using population-averaged generalized estimating equation Poisson regression. Checklist compliance was defined as correctly completing a sign in, timeout, and sign out. Incidence rate ratios of correct checklist use pre- and post-intervention were calculated and the change in mean weekly compliance was predicted. Checklist compliance data were obtained from 2767 operations (1940 (70 per cent) pre-intervention and 827 (30 per cent) post-intervention). Mean weekly checklist compliance improved from 27.3 to 41.2 per cent (mean difference 13.9 per cent, P = 0.001; incidence rate ratio 1.51, P = 0.001). Hospitals with higher checklist compliance at baseline had the greatest overall improvements in compliance, more than 50 per cent over pre-intervention, while low-performing hospitals showed no improvement. Surgical Safety Checklist workshops improved checklist compliance in hospitals with some experience with its use. Workshops had little effect in hospitals unfamiliar with the Surgical Safety Checklist, emphasizing the importance of multifactorial interventions and culture-change approaches. In receptive facilities, short workshops can accelerate behaviour change.

Predictive quality assurance for linear accelerator target failure using statistical process control

The performance of a linear accelerator (Linac) depends on the integrity of its x-ray target. The sudden failure of its target not only breaks down the Linac but also could contribute significant disruptions to patient care. This work is to develop a predicative quality assurance (QA) method using Statistical Process Control (SPC) and AutoRegressive Integrated Moving Average (ARIMA) modeling to identify the risk of target failure before it occurs. In the past years, we observed two incidents of target failure among our Linacs. Retrospectively, we collected past daily QA data (from both open fields and enhanced dynamic wedge (EDW) measurements) and analyzed its historical trend using methods of SPC and ARIMA. SPC is a technique that monitors process performance based on statistical analysis. ARIMA is a time-series forecasting algorithm that can be used to estimate future values based on its past pattern. Both have been evaluated for predictive QA in radiotherapy. Application of SPC on open beam QA data would not yield an early warning signal to the pending target failures. However, when the same SPC methodology applies to EDW measurements, the control limits were breached a couple of weeks before the target failed. EDW mechanism introduces nonuniform magnification factors over its wedge-directed beam profiles and is responsible for the sensitivity of its profile to changing beam properties induced by a degrading target. Further extension of the warning period may be possible by using ARIMA modeling. Predicative QA for EDW daily data using SPC and ARIMA methods may provide an early QA warning to incoming Linac target failure.

Evaluation of Microbiological Cleanliness of Machines/Equipment through Rinse Technique Using Statistical Process Control

To guarantee that patients receive safe therapy with predictable and acceptable medicinal properties, monitoring the quality standards in the healthcare sector and the pharmaceutical business, in particular, is essential. Medicinal products are no exception from these crucial characteristics and hence mitigation of the sources of microbial contamination is a mandatory strategy to avoid harming already-ill populations. Machines, equipment and tools that are used in the industry must be appropriately cleaned to ensure that they will not contaminate the product under processing. The study herein aimed to establish an evaluation system for cleaning efficiency through the rinse technique using Statistical Process Control (SPC) methodologies. A database was established and created for the recorded cleaning process over 20 months of the monitoring period. The control charts were constructed and evaluated from processed data using SPC software. A rare event control chart was used to track the cleaning process intervals with event probability estimated to be 0.080. Concerning the monitoring of the bioburden of rinse samples, the most appropriate fitting attribute chart is U type with Laney modification of over-dispersion to correct for tight control limits that increase alarming false points. Understanding the inspection property is inevitable for the right interpretation of trends.

Protocol-Driven Initiation and Weaning of High-Flow Nasal Cannula for Patients With Bronchiolitis: A Quality Improvement Initiative.

Bronchiolitis is the most common cause for nonelective infant hospitalization in the United States with increasing utilization of high-flow nasal cannula (HFNC). We standardized initiation and weaning of HFNC for bronchiolitis and quantified the impact on outcomes. Our specific aim was to reduce hospital and ICU length of stay (LOS) by 10% between two bronchiolitis seasons after implementation. A quality improvement (QI) project using statistical process control methodology. Tertiary-care children's hospital with 24 PICU and 48 acute care pediatric beds. Children less than 24 months old with bronchiolitis without other respiratory diagnoses or underlying cardiac, respiratory, or neuromuscular disorders between December 2017 and November 2018 (baseline), and December 2018 and February 2020 (postintervention). Interventions included development of an HFNC protocol with initiation and weaning guidelines, modification of protocol and respiratory assessment classification, education, and QI rounds with a focus on efficient HFNC weaning, transfer, and/or discharge. A total of 223 children were included (96 baseline and 127 postintervention). The primary outcome metric, average LOS per patient, decreased from 4.0 to 2.8 days, and the average ICU LOS per patient decreased from 2.8 to 1.9 days. The secondary outcome metric, average HFNC treatment hours per patient, decreased from 44.0 to 36.3 hours. The primary and secondary outcomes met criteria for special cause variation. Balancing measures included ICU readmission rates, 30-day readmission rates, and adverse events, which were not different between the two periods. A standardized protocol for HFNC management for patients with bronchiolitis was associated with decreased hospital and ICU LOS, less time on HFNC, and no difference in readmissions or adverse events.

Statistical process control implementations within the aviation industry

In 1931, Walter Shewhart introduced his work in statistical process control (SPC) through his book, Economic Control of Quality of Manufactured Product. A common confusion in the use of SPC is that it does not fit every business or industry. Since Shewhart's work was published, various companies and industries have implemented such practices as a method to control their manufacturing quality of products, service quality, and design quality. In 2017, a supply chain quality organization from a well-known business jet manufacturer discovered that vendors of its supply base were posting ostensibly statistical process control charts on metric walls in their facilities. The charts were not error-free. Out-of-date data placed on the charts, the preponderance appeared to be weeks or months old, and incorrect use of control and specification limits indicated there might be a gap. The purpose of this research was to discover why businesses in the aviation industry are not taking advantage of SPC practices and methodologies. To identify the potential barriers inhibiting the deployment or growth of SPC implementations in the aviation industry, data was gathered from a survey of original equipment manufacturers (OEM) and members of the aviation supply base. The major challenges or barriers to implementing SPC in the aviation supply base were recognized as leadership commitment, cultural mindset and behaviors, understanding the benefits of SPC, and a lack of knowledge.

Completion of an Enhanced Recovery Program in a Pediatric Ambulatory Surgery Center: A Quality Improvement Initiative.

Enhanced Recovery After Surgery (ERAS) was first established in 2001 focusing on recovery from complex surgical procedures in adults and recently expanded to ambulatory surgery. The evidence for ERAS in children is limited. In 2018, recognized experts began developing needed pediatric evidence. Center-wide efforts involving all ambulatory surgical patients and procedures have not previously been described. A comprehensive assessment and gap analysis of ERAS elements in our ambulatory center identified 11 of 19 existing elements. The leadership committed to implementing an Enhanced Recovery Program (ERP) to improve existing elements and close as many remaining gaps as possible. A quality improvement (QI) team was launched to improve 5 existing ERP elements and to introduce 6 new elements (target 17/19 ERP elements). The project plan was broken into 1 preparation phase to collect baseline data and 3 implementation phases to enhance existing and implement new elements. Statistical process control methodology was used. Team countermeasures were based on available evidence. A consensus process was used to resolve disagreement. Monthly meetings were held to share real-time data, gather new feedback, and modify countermeasure plans as needed. The primary outcome measure selected was mean postanesthesia care unit (PACU) length of stay (LOS). Secondary outcomes measures were mean maximum pain score in PACU and patient/family satisfaction scores. The team had expanded the pool of active ERP elements from 11 to 16 of 19. The mean PACU LOS demonstrated significant reduction (early in phase 1 and again in phase 3). No change was seen for the mean maximum pain score in PACU or surgical complication rates. Patient/family satisfaction scores were high and sustained throughout the period of study (91.1% ± 5.7%). Patient/family and provider engagement/compliance were high. This QI project demonstrated the feasibility of pediatric ERP in an ambulatory surgical setting. Furthermore, a center-wide approach was shown to be possible. Additional studies are needed to determine the relevance of this project to other institutions.

Prioritizing Hormone Therapy Over Vigabatrin as the First Treatment for Infantile Spasms: A Quality Improvement Initiative.

Infantile spasms (IS) are early childhood seizures with potentially devastating consequences. Standard therapies (adrenocorticotropic hormone [ACTH], high-dose prednisolone, and vigabatrin) are strongly recommended as the first treatment for IS. Although this recommendation comes without preference for one standard therapy over another, early remission rates are higher with hormone therapy (ACTH and high-dose prednisolone) when compared with vigabatrin. Using quality improvement (QI) methodology that included hormone therapy as the first treatment, we sought to increase the percentage of children with new-onset nontuberous sclerosis complex (TSC)-associated IS achieving 3-month electroclinical remission from a mean of 53.8% to ≥70%. This was an observational consecutive sample cohort study at a single academic tertiary care hospital that compared a prospective intervention cohort (May 2019-January 2022, N = 57) with a retrospective baseline cohort (November 2015-April 2019, N = 67). Our initiative addressed key drivers such as the routine use of vigabatrin over hormone therapy as first treatment and the common initiation of a second treatment after 14 days for initial nonresponders. We included consecutive children without TSC presenting with new-onset IS diagnosed and treated between ages 2 and 24 months. We displayed our primary outcome and process measures as control charts in which the centerline is the quarterly (previous 3 months) mean based on statistical process control methodology. QI interventions that included the standardization of hormone therapy as the first treatment resulted in higher rates of 3-month remission, rising from 53.8% (baseline cohort) to 75.9% (intervention cohort). Process measure results included an increased rate of children receiving hormone therapy as first treatment (mean, 44.6%-100%) and a decreased number of days to both clinical follow-up after first treatment (mean, of 16.3-12.6 days) and starting a second treatment within 14 days for initial nonresponders (mean, 36.3-17.2 days). For children with IS, improved rates of 3-month electroclinical remission can be achieved with QI methodology. Implementation of similar QI initiatives at other centers may likewise improve local remission rates.

Reducing Pediatric Emergency Department Prescription Errors.

Prescription errors are a significant cause of iatrogenic harm in the health care system. Pediatric emergency department (ED) patients are particularly vulnerable to error. We sought to decrease prescription errors in an academic pediatric ED by 20% over a 24-month period by implementing identified national best practice guidelines. From 2017 to 2019, a multidisciplinary, fellow-driven quality improvement (QI) project was conducted using the Model for Improvement. Four key drivers were identified including simplifying the electronic order entry into prescription folders, improving knowledge of dosing by indication, increasing error feedback to prescribers, and creating awareness of common prescription pitfalls. Four interventions were subsequently implemented. Outcome measures included prescription errors per 1000 prescriptions written for all medications and top 10 error-prone antibiotics. Process measures included provider awareness and use of prescription folders; the balancing measure was provider satisfaction. Differences in outcome measures were assessed by statistical process control methodology. Process and balancing measures were analyzed using 1-way analysis of variance and χ2 testing. Before our interventions, 8.6 errors per 1000 prescriptions written were identified, with 62% of errors from the top 10 most error-prone antibiotics. After interventions, error rate per 1000 prescriptions decreased from 8.6 to 4.5 overall and from 20.1 to 8.8 for top 10 error-prone antibiotics. Provider awareness of prescription folders was significantly increased. QI efforts to implement previously defined best practices, including simplifying and standardizing computerized provider order entry (CPOE), significantly reduced prescription errors. Synergistic effect of educational and technological efforts likely contributed to the measured improvement.

Effects of COVID-19 pandemic restrictions on an Australian neonatal and paediatric retrieval service.

AimThe COVID‐19 pandemic and associated travel and social distancing restrictions have reduced paediatric intensive care unit admissions for respiratory illnesses. The effects on retrieval (transport) services remain unquantified. Our study examined the utility of statistical process control in assessing the impact of the COVID‐19 pandemic on the number of neonatal and paediatric transfers in an Australian retrieval service.MethodsData collected prospectively from the SA Ambulance Service MedSTAR Emergency Retrieval database in South Australia were analysed from January 2015 to June 2021. Statistical process control methodology, a combination of a time series analysis and assessment for common and special cause variation, was used to assess the impact of the COVID‐19 pandemic on retrieval workload (primary outcome of interest).ResultsA total of 5659 neonatal and paediatric transfers occurred during the study period and were included. A significant decrease in paediatric transfers occurred after the initial lockdown measures in March 2020 were announced in South Australia (special cause variation). However, a similar reduction was not observed for neonatal transfers (common cause variation).ConclusionOur study demonstrates that statistical process control may be effectively used to understand the effects of external events and processes on usual activity patterns in the retrieval setting. We found a reduction in retrieval numbers for paediatric transfers but no effect on neonatal transfer numbers. The decline in paediatric transfers was primarily attributed to reduced respiratory cases.

Precipitation Trend Analysis of India - A Climate Change Study

Objectives: To identify the trend and variability of precipitation in the Indian subcontinent. Methods: To identify the trend component the non-parametric test statistic Mann - Kendall and Statistical Process Control (SPC) methodologies are used to conduct a statistical study. Findings: Precipitation of India has shown decreasing trend throughout the winter, monsoon, and on an annual basis, and an increasing tendency was observed during the rest of the seasons. During the winter season, there was more variation in precipitation with Coefficient of Variance (CV) is 33.7919%. Novelty: The long period (120 years) average data from 1901 - 2020 is used to know the long run trend and distribution pattern variation of precipitation in India with the proposed statistical methods. Applications: This mechanism is suitable to change the crop pattern and manage the adverse effects in associated sectors. Keywords: Statistical Process Control; India; Mann Kendall Statistic; Precipitation; Trend

High-Speed Monitoring of Multidimensional Processes Using Bayesian Updates

The advent of modern data acquisition and computing techniques has enabled high-speed monitoring of high-dimensional processes. The short sampling interval makes the samples temporally correlated, even if there is no underlying autocorrelation among covariates. In this study, we introduce a new process monitoring scheme in a Bayesian framework. The key strategy of this study is to incorporate sequential observations into the estimation procedure for the parameters of interest to update the prior distribution. Based on the updated prior, we obtain the most appropriate estimation of the process parameters at each sampling epoch by maximizing the posterior probability. In addition, conventional statistical process control and monitoring methodologies suffer from the “curse of dimensionality.” The closed form of the estimate developed in this study through Bayesian updates enables the proposed method to be effective for high-dimensional process monitoring. Various simulation studies demonstrate the superiority of the proposed scheme in the high-speed monitoring of high-dimensional processes. Moreover, a few sample paths of the estimated mean in a procedure of the proposed method are illustrated to provide practitioners with insights into the monitoring and control of the process. Finally, we provide a real-life application to illustrate the proposed method.

Shifting the Paradigm: A Quality Improvement Approach to Proactive Cardiac Arrest Reduction in the Pediatric Cardiac Intensive Care Unit.

Children with cardiac conditions are at higher risk of in-hospital pediatric cardiopulmonary arrest (CA), resulting in significant morbidity and mortality. Despite the elevated risk, proactive cardiac arrest prevention programs in the cardiac intensive care unit (CICU) remain underdeveloped. Our team developed a multidisciplinary program centered on developing a quality improvement (QI) bundle for patients at high risk of CA. This project occurred in a 26-bed pediatric CICU of a tertiary care children's hospital. Statistical process control methodology tracked changes in CA rates over time. The global aim was to reduce CICU mortality; the smart aim was to reduce the CA rate by 50% over 12 months. Interprofessional development and implementation of a QI bundle included visual cues to identify high-risk patients, risk mitigation strategies, a new rounding paradigm, and defined escalation algorithms. Additionally, weekly event and long-term data reviews, arrest debriefs, and weekly unit-wide dissemination of key findings supported a culture change. After bundle implementation, CA rates decreased by 68% compared to baseline and 45% from the historical baseline. Major complications decreased from 17.1% to 12.6% (P < 0.001) and mortality decreased from 5.7% to 5.0% (P = 0.048). These results were sustained for 30 months. Cardiac arrest is a modifiable, rather than inevitable, metric in the CICU. Reduction is achievable through the interprofessional implementation of bundled interventions targeting proactive CA prevention. Once incorporated into widespread efforts to engage multidisciplinary CICU stakeholders, these patient-focused interventions resulted in sustained improvement.

STUDY OF TELLURIUM-129m (129mTe) GROUND DEPOSITION FOLLOWING FUKUSHIMA NUCLEAR DISASTER: DESCRIPTIVE ANALYSIS OF UNSCEAR DATABASE USING STATISTICAL PROCESS TECHNIQUES

One of the most shocking accidents that have impacted the world recently was the devastation of the Fukushima-Daiichi nuclear power plant following a major earthquake followed by a strong 15-meter Tsunami wave affecting the east coast region. One of the major adverse consequences of this catastrophic event is the release and dissemination of radioactive materials in the surrounding environment. Tellurium-129m is one of the comprehensively traced fission products to assess the magnitude of spreading by measuring ground soil deposition of radioactivity. Radiation level/location relationship study was tested using a simple and inexpensive statistical software package using unique Statistical Process Control methodologies for the United Nations Scientific Committee on the Effects of Atomic Radiation database that demonstrated spiking in radioactivity. Sampling points were geographically associated with the radioactivity level with the spot of the maximum radionuclide concentration could be linked with the damaged plant location. More than three-fifths of the measured radioactivity are confined in an area of about 640 km2 covering five municipalities namely Namie, and Futaba towns, Litate village and Iwaki city. The latitude-oriented chart showed a sudden rise in deposition followed by a gradual decline. Excessive Tellurium-129m activity could be observed in the area of the catastrophic event.

Bayesian sequential monitoring of density estimates

AbstractIn this paper, we consider sequentially estimating the density of univariate data. We utilize Pólya trees to develop a statistical process control (SPC) methodology. Our proposed methodology monitors the distribution of the sequentially observed data and detects when the generating density differs from an in‐control standard. We also propose an approximation that merges the probability mass of multiple possible changepoints to curb computational complexity while maintaining the accuracy of the monitoring procedure. We show in simulation experiments that our approach is capable of quickly detecting when a changepoint has occurred while controlling the number of false alarms, and performs well relative to competing methods. We then use our methodology to detect changepoints in high‐frequency foreign exchange (Forex) return data.