Statistical Process Control Analysis Research Articles

Managing Operations and Supply Chains in Automotive Industry

Profitability, customer satisfaction, and innovation in the cutthroat automobile industry depend on well-managed operations and supply networks. Managing operations and supply chains in the automotive industry is complex, and this paper lays forth a comprehensive framework for doing so. An integral part of effective operations management in the automotive industry is demand forecasting and planning. Using collaborative forecasting methodologies, market trend analysis, and advanced analytics, automotive manufacturers can improve production schedules, minimize inventory costs, and foresee changes in demand. Reducing waste, enhancing process efficiency, and managing low inventory levels are all achieved through the use of lean manufacturing techniques like Just-in-Time (JIT) production and Total Productive Maintenance (TPM). Collaboration with suppliers, uninterrupted material flow, and supply chain innovation can all be achieved through supplier relationship management (SRM). Automakers may enhance product quality, cut costs, and lessen supply chain risks by communicating openly, working together to improve processes, and forming agreements that benefit all parties involved. Automobile companies can't afford to have any product flaws that damage their reputation or the loyalty of their customers, which is why quality management is so important in this industry. Statistical Process Control (SPC), Failure Mode and Effects Analysis (FMEA), and Six Sigma are a few of the rigorous quality control methods that manufacturers use to find and rectify flaws early

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...

Performance assessment of surgical tracking systems based on statistical process control and longitudinal QA

A system for performance assessment and quality assurance (QA) of surgical trackers is reported based on principles of geometric accuracy and statistical process control (SPC) for routine longitudinal testing. A simple QA test phantom was designed, where the number and distribution of registration fiducials was determined drawing from analytical models for target registration error (TRE). A tracker testbed was configured with open-source software for measurement of a TRE-based accuracy metric ε and Jitter ( J ). Six trackers were tested: 2 electromagnetic (EM – Aurora); and 4 infrared (IR − 1 Spectra, 1 Vega, and 2 Vicra) – all NDI (Waterloo, ON). Phase I SPC analysis of Shewhart mean ( x ¯ ) and standard deviation ( s ) determined system control limits. Phase II involved weekly QA of each system for up to 32 weeks and identified Pass, Note, Alert, and Failure action rules. The process permitted QA in <1 min. Phase I control limits were established for all trackers: EM trackers exhibited higher upper control limits than IR trackers in ε (EM: x ¯ ε ∼ 2.8–3.3 mm, IR: x ¯ ε ∼ 1.6–2.0 mm) and Jitter (EM: x ¯ jitter ∼ 0.30–0.33 mm, IR: x ¯ jitter ∼ 0.08–0.10 mm), and older trackers showed evidence of degradation – e.g. higher Jitter for the older Vicra (p-value < .05). Phase II longitudinal tests yielded 676 outcomes in which a total of 4 Failures were noted − 3 resolved by intervention (metal interference for EM trackers) – and 1 owing to restrictive control limits for a new system (Vega). Weekly tests also yielded 40 Notes and 16 Alerts – each spontaneously resolved in subsequent monitoring.

An Outlier Detection Study of Ozone in Kolkata India by the Classical Statistics, Statistical Process Control and Functional Data Analysis

Air pollution is prevalent throughout the entire world due to the release of various gases such as NOx, PM, SO2, tropospheric ozone (O3), etc. Ground-stage ozone is the predominant issue in smog and is the product of the interplay between sunlight and emissions. The destructive impact on the health of the populace might also still occur in cities with noticeably clean air and where ozone levels hardly ever exceed safe limits. Therefore, the findings of small variations in air quality and the technique of regulating air contamination are thought-provoking. The study employs various techniques to effectively observe and assess strategies for detecting and eliminating outliers in ozone emissions from pollution episodes. This technique helps to describe the sources and exceedance values and enhance the value of monitoring the data. In this study, the data have some missing observations. The method of imputation, the classical statistical technique, the statistical process control (SPC) technique, functional data analysis (FDA), and functional process control help to fill in the data and detect outliers, trend deviations, and changes in ozone concentration at ground level. A comparison study is carried out using these three techniques: classical analysis, SPC, and FDA, and the results show how the statistical process control and functional data methods performed better than the classical technique for the detection of outliers and also in what way this methodology can enable an additional, comprehensive method of defining air pollution control measures and water pollution control measures.

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.

ANALYSIS OF QUALITY CONTROL OF TAPIOCA FLOUR PRODUCTS AT PT GUNUNG SUGIH

PT Gunung Sugih is one of the industry players that produces tapioca flour in the form of 50 kg. Researchers conducted research on tapioca flour production in the input, process and output sections. The production process at PT Gunung Sugih has problems with raw materials, humans, machines, methods and the environment, causing damage to the product. The purpose of this study was to identify whether the level of damage that occurs in PT Gunung Sugih tapioca flour products is still within tolerance limits or not and to identify the factors that cause the most dominant damage. The method used in this study is the Statistical Process Control (SPC) method, with Check Sheet analysis tools, histograms, control charts and causal diagrams so that product damage that occurs can be indicated. The data sources used in this study are primary data and secondary data from PT Gunung Sugih in April 2023. Based on the existing data, statistical process control (SPC) analysis has been carried out, it is known that the damage that occurred in PT Gunung Sugih's tapioca flour production still within tolerance limits, and it is known that the main factors of product damage come from raw materials, people, machines and methods. The most dominant damage is damage to the water content that comes from the human factor, tapioca flour agglomerates from the machine and human factors, while the color damage is from the raw material and human factors, thus it is hoped that PT Gunung Sugih will improve operator supervision on raw materials, production processes and production results, work instructions can be given in writing and explained verbally at the beginning of each production and the end of work, hold regular and periodic meetings with employees, carry out periodic machine maintenance and provide safety equipment and silencers on the machine. this is to maintain product quality to remain good.

Efficacy and Impact of a Multimodal Intervention on CT Pulmonary Angiography Ordering Behavior in the Emergency Department

ObjectiveTo evaluate the efficacy of a multimodal intervention in reducing CT pulmonary angiography (CTPA) overutilization in the evaluation of suspected pulmonary embolism in the emergency department (ED). MethodsPrevious mixed-methods analysis of barriers to guideline-concordant CTPA ordering results was used to develop a provider-focused behavioral intervention consisting of a clinical decision support tool and an audit and feedback system at a multisite, tertiary academic network. The primary outcome (guideline concordance) and secondary outcomes (yield and CTPA and D-dimer order rates) were compared using a pre- and postintervention design. ED encounters for adult patients from July 5, 2017, to January 3, 2019, were included. Fisher’s exact tests and statistical process control charts were used to compare the pre- and postintervention groups for each outcome. ResultsOf the 201,912 ED patient visits evaluated, 3,587 included CTPA. Guideline concordance increased significantly after the intervention, from 66.9% to 77.5% (P < .001). CTPA order rate and D-dimer order rate also increased significantly, from 17.1 to 18.4 per 1,000 patients (P = .035) and 30.6 to 37.3 per 1,000 patients (P < .001), respectively. Percent yield showed no significant change (12.3% pre- versus 10.8% postintervention; P = .173). Statistical process control analysis showed sustained special-cause variation in the postintervention period for guideline concordance and D-dimer order rates, temporary special-cause variation for CTPA order rates, and no special-cause variation for percent yield. ConclusionOur success in increasing guideline concordance demonstrates the efficacy of a mixed-methods, human-centered approach to behavior change. Given that neither of the secondary outcomes improved, our results may demonstrate potential limitations to the guidelines directing the ordering of CTPA studies and D-dimer ordering.

Quality Matters: Examining the Impact of Nurse Staffing Challenges on Clinical Outcomes.

The purpose of this study was to examine nurse staffing while describing the relationships that exist in staffing and quality associated with nursing care during the COVID-19 pandemic, a significantly challenging time for nurse staffing. We examined the relationship between permanent registered nurse (RN) and travel RN staffing during the pandemic and the nursing-sensitive outcomes of catheter-associated urinary tract infections (CAUTIs), central line-associated bloodstream infections (CLABSIs), falls, and hospital-acquired pressure injuries (HAPIs) and length of stay and compared the cost of CAUTIs, CLABSIs, falls, and HAPIs in fiscal years 2021 and 2022. We used a descriptive, observational design to retrospectively examine permanent nurse staffing volume and CAUTI, CLABSI, HAPI, and fall counts from October 1, 2019, to February 28, 2022, and travel nurse volume for the most current 12 months, April 1, 2021, to March 31, 2022. Descriptive statistics, Pearson correlation, and statistical process control analyses were completed. Pearson correlation showed a statistically significant, moderately strong negative correlation (r = -0.568, p = .001) between the active registered nurse full-time equivalents (RN FTEs) and average length of stay (ALOS), and a moderately strong positive correlation (r = 0.688, p = .013) between the travel RN FTEs and ALOS. Pearson correlations were not statistically significant, with low to moderate negative correlations for CAUTIs (r = -0.052, p = .786), CLABSIs (r = -0.207, p = .273), and falls (r = -0.056, p = .769). Pearson correlation for active RN and HAPI showed a moderately strong, statistically significant positive correlation (r = 0.499, p = .003). We observed common cause variation in CAUTIs and CLABSIs, with HAPIs and falls showing special cause variation via statistical process control. Despite the challenges associated with the lack of available nurse staffing accompanied by increasing responsibilities including unlicensed tasks, positive clinical outcomes can be maintained by staff adherence to evidence-based quality improvement.

Quality control analyisis of crab meat products in Mitra Bersama Miniplant Bandar Surabaya, Central Lampung

In this increasingly sophisticated era of globalization, Small, Micro and Medium Enterprises (MSMEs) can be found in various places, from big cities to remote villages. This is what encourages business people to improve the quality of the products they produce in order to compete in the midst of intense competition in the business world. Mitra Bersama Miniplant is an MSME engaged in the processing of marine products, especially crabs with crab meat output. Mitra Bersama Miniplant continues to maintain and improve product quality by conducting supervision, but there is still a high level of damage that requires strict quality control to obtain high quality products. In controlling product quality, it can be done by using the Statistical Process Control analysis tool. The purpose of this study was to analyze whether the level of damage to crab meat products is still within tolerance limits or not and to determine the factors that influence the occurrence of defective products. This research was conducted for 30 days of production starting on 15 December 2022 to 15 January 2023 which obtained the result that the level of product defects was still within tolerance limits. The dominant factors that cause defects in crab meat can be seen from the cause and effect diagram, namely humans (labor), raw materials, work methods and machines. The most dominant product defect is soft crab meat (crushed) with a total of 68,03 kg of defective product. Therefore, it is expected that quality control at Mitra Bersama Miniplants will be improved again by carrying out stricter supervision of the production process, especially on labor factors, production process methods, raw materials, machinery and the environment so that the level of product defects decreases and the product remains good.

Improving the Quality of People's Salt Using the Blue Economy Concept in East Java Province, Indonesia

Assessment of the quality of people's salt in East Java Province is only seen based on color and shape, even though the NaCl level determines whether or not the quality of the salt is good. Implementing the production process is often counterproductive, with reusing "bittern" for production affecting quality. Still, some also throw away "bittern" which can cause ecosystem pollution, contrary to the blue economy concept. This study aims to determine the quality control of people's salt, the implementation of blue economy principles in the salt sector, and solutions to improve the quality of people's salt in East Java Province by considering the blue economy principles. The research approach uses mixed methods with quantitative descriptive and qualitative descriptive. Data is collected through interviews, observation, documentation, and audio and visual materials. Quantitative descriptive data analysis techniques used statistical process control and capability analysis, while qualitative descriptive data analysis used the Interactive Model, including data condensation, data display, and conclusion drawing/verification. The results of this study indicate that it must improve people's salt quality control in East Java Province because the average is still in the K3 quality category. NaCl levels &lt; 85% and 85%-89.99% and Mg levels 0.080%-0.099% are a top priority for quality control. Analysis of process capability shows that production is inadequate, and the people's salt in East Java Province has not been able to meet the quality standards for iodized consumption salt and industrial salt for various foods due to personnel, measurements, methods, materials, and environmental factors. Solutions to improve the quality of people's salt by referring to the blue economy principle through increasing the competence of farmers, preparing production SOPs, applying semi-modern production technologies, improving techniques for transferring water and raw materials, washing and recrystallization, providing assistance with production facilities, technical guidance, and having a policy for determining salt as a basic need and salt commodity reference price.

Feasibility on Statistical Process Control Analysis of Delivery Quality Assurance in Helical Tomotherapy

Feasibility on Statistical Process Control Analysis of Delivery Quality Assurance in Helical Tomotherapy

Implementation of a 24-hour infection diagnosis protocol in the pediatric cardiac intensive care unit (CICU).

To reduce unnecessary antibiotic exposure in a pediatric cardiac intensive care unit (CICU). Single-center, quality improvement initiative. Monthly antibiotic utilization rates were compared between 12-month baseline and 18-month intervention periods. A 25-bed pediatric CICU. Clinically stable patients undergoing infection diagnosis were included. Patients with immunodeficiency, mechanical circulatory support, open sternum, and recent culture-positive infection were excluded. The key drivers for improvement were standardizing the infection diagnosis process, order-set creation, limitation of initial antibiotic prescription to 24 hours, discouraging indiscriminate vancomycin use, and improving bedside communication and situational awareness regarding the infection diagnosis protocol. In total, 109 patients received the protocol; antibiotics were discontinued in 24 hours in 72 cases (66%). The most common reasons for continuing antibiotics beyond 24 hours were positive culture (n = 13) and provider preference (n = 13). A statistical process control analysis showed only a trend in monthly mean antibiotic utilization rate in the intervention period compared to the baseline period: 32.6% (SD, 6.1%) antibiotic utilization rate during the intervention period versus 36.6% (SD, 5.4%) during the baseline period (mean difference, 4%; 95% CI, -0.5% to -8.5%; P = .07). However, a special-cause variation represented a 26% reduction in mean monthly vancomycin use during the intervention period. In the patients who had antibiotics discontinued at 24 hours, delayed culture positivity was rare. Implementation of a protocol limiting empiric antibiotic courses to 24 hours in clinically stable, standard-risk, pediatric CICU patients with negative cultures is feasible. This practice appears safe and may reduce harm by decreasing unnecessary antibiotic exposure.

An Interactive Visualization Web Application for Industrial-Focused Statistical Process Control Analysis

Statistical process control (SPC) implementation plays a major role in quality assurance during the manufacturing process. Nevertheless, the adoption rate of SPC commercial software solutions is unsatisfactory in most Malaysian manufacturing companies due to high software subscription costs and difficulties in applying the software without proper know-how, guidance, and training. This study proposes the development of a purpose-built interactive data visualization web application for rapid SPC analysis in the manufacturing industry using open-sourced software packages. An agile software development model is applied as the software development methodology. In the requirement phase, an interview session was conducted to identify project requirements among stakeholders, i.e. industrial practitioners that are involved with SPC analysis. Based on the feedback and expectations from stakeholders, a design of a web application for SPC analysis that incorporates interactive parameter settings and automated reporting was proposed. The web application was developed using the R programming language and the Shiny package library, and deployed at ShinyApps.io, a web service provider. For evaluation, a usability testing procedure was designed and conducted with five industrial SPC practitioners to determine the usefulness of the web application. The outcome of the usability testing indicated positive results and feedback from evaluators. In conclusion, the developed web-app can assist users, particularly from the manufacturing industry sectors, to perform fast SPC data analytics, visualization, and reporting with ease.

Collaborative to Increase Lethal Means Counseling for Caregivers of Youth With Suicidality.

The number of youth presenting to hospitals with suicidality and/or self-harm has increased substantially in recent years. We implemented a multihospital quality improvement (QI) collaborative from February 1, 2018 to January 31, 2019, aiming for an absolute increase in hospitals' mean rate of caregiver lethal means counseling (LMC) of 10 percentage points (from a baseline mean performance of 68% to 78%) by the end of the collaborative, and to evaluate the effectiveness of the collaborative on LMC, adjusting for secular trends. This 8 hospital collaborative used a structured process of alternating learning sessions and action periods to improve LMC across hospitals. Electronic medical record documentation of caregiver LMC was evaluated during 3 phases: precollaborative, active QI collaborative, and postcollaborative. We used statistical process control to evaluate changes in LMC monthly. Following collaborative completion, interrupted time series analyses were used to evaluate changes in the level and trend and slope of LMC, adjusting for covariates. In the study, 4208 children and adolescents were included-1314 (31.2%) precollaborative, 1335 (31.7%) during the active QI collaborative, and 1559 (37.0%) postcollaborative. Statistical process control analyses demonstrated that LMC increased from a hospital-level mean of 68% precollaborative to 75% (February 2018) and then 86% (October 2018) during the collaborative. In interrupted time series analyses, there were no significant differences in LMC during and following the collaborative beyond those expected based on pre-collaborative trends. LMC increased during the collaborative, but the increase did not exceed expected trends. Interventions developed by participating hospitals may be beneficial to others aiming to improve LMC for caregivers of hospitalized youth with suicidality.

Implementation of Standardized Care for the Medical Stabilization of Patients With Anorexia Nervosa.

Introduction:Approaches to refeeding patients with anorexia nervosa for medical stabilization vary across institutions, and there is no established standard of care. This study assessed the impact of a refeeding pathway on hospital length of stay and transfer to the psychiatry unit.Methods:This quality improvement intervention sought to standardize care for adolescents with anorexia nervosa at a tertiary care, free-standing children’s hospital from Spring 2017 to Fall 2018. The pathway specified admission criteria, nutritional advancement, activity restriction, laboratory monitoring, readiness to transfer to the psychiatry unit, and discharge criteria. Statistical process control analysis was utilized to identify system-level changes over time. We used linear regression to assess pre- and postpathway differences in length of stay and transfer to the psychiatry unit.Results:There were 161 patient encounters for anorexia nervosa admitted for medical stabilization. 84% of the sample were female with median age of 15.2 (IQR 14.0–17.0) years. There was no difference in hospital length of stay between the pre- and postpathway groups. There was a statistically significant increase in the proportion of patients transferred to the psychiatry unit over the study period.Conclusion:Clinical pathway use to deliver standardized care to achieve medical stability for patients with anorexia nervosa did not shorten hospital length of stay. Multiple potentially confounding medical and psychosocial factors may have contributed to this lack of improvement.

Time-course assessment of 3D-image distortion on the 1.5 T Marlin/Elekta Unity MR-LINAC

PurposeThe efficacy of MR-guided radiotherapy on a MR-LINAC (MR-L) is dependent on the geometric accuracy of its MR images over clinically relevant Fields-of-View (FOVs). Our objectives were to: evaluate gradient non-linearity (GNL) on the Elekta Unity MR-L across time via 76 weekly measurements of 3D-distortion over concentrically larger diameter spherical volumes (DSVs); quantify distortion measurement error; and assess the temporal stability of spatial distortion using statistical process control (SPC). MethodsMR-image distortion was assessed using a large-FOV 3D-phantom containing 1932 markers embedded in seven parallel plates, spaced 25 mm × 25 mm in- and 55 mm through-plane. Automatically analyzed T1 images yielded distortions in 200, 300, 400 and 500 mm concentric DSVs. Distortion measurement error was evaluated using median absolute difference analysis of imaging repeatability tests. ResultsOver the measurement period absolute time-averaged distortion varied between: dr = 0.30 – 0.49 mm, 0.53 – 0.80 mm, 1.0 – 1.4 mm and 2.28 – 2.37 mm, for DSVs 200, 300, 400 and 500 mm at the 98th percentile level. Repeatability tests showed that imaging/repositioning introduces negligible error: mean ≤ 0.02 mm (max ≤ 0.3 mm). SPC analysis showed image distortion was stable across all DSVs; however, noticeable changes in GNL were observed following servicing at the one-year mark. ConclusionsImage distortion on the MR-L is in the sub-millimeter range for DSVs ≤ 300 mm and stable across time, with SPC analysis indicating all measurements remain within control for each DSV.

Variability in the unregulated opioid market in the context of extreme rates of overdose

Background: Drug checking uses analytical chemistry technologies to report on the composition of drugs from the unregulated market to reduce substance use-related risks, while additionally allowing for monitoring and reporting of the supply. In the context of an overdose crisis linked to fentanyl, we used drug checking data to examine variability within the illicit opioid supply.Methods: In this time-series analysis, data was collected from a drug checking service in Victoria, Canada from November 2020 to July 2021. Drugs reported as opioids by participants of the service (N = 454) were analyzed to determine sample composition and paper spray mass spectroscopy was used to quantify low-concentration actives. Interquartile and statistical process control (SPC) analysis, namely standard deviation control charts, were used to examine the degree of variability among samples.Results: Fentanyl was found in 96% of samples reported to be opioids, with a median concentration of 9%. Concentrations varied significantly, with a standard deviation of 7% for fentanyl and where nearly 20% of data points fell outside the control limits. Over half of the samples contained an additional and unexpected active, most commonly etizolam (43% of samples). Etizolam also showed a large level of variability, uncorrelated to that of fentanyl.Conclusions: Based on our chemical quantification and SPC analysis, a high degree of variability was found in opioid samples from the unregulated market in both the drugs detected and the concentrations of those drugs. This demonstrated the opioid crisis to be less attributable to a bad batch of drugs but rather the general variability found in the unregulated market.

Prediction of Process Quality Performance Using Statistical Analysis and Long Short-Term Memory

In the manufacturing industry, the process capability index (Cpk) measures the level and capability required to improve the processes. However, the Cpk is not enough to represent the process capability and performance of the manufacturing processes. In other words, considering that the smart manufacturing environment can accommodate the big data collected from various facilities, we need to understand the state of the process by comprehensively considering diverse factors contained in the manufacturing. In this paper, a two-stage method is proposed to analyze the process quality performance (PQP) and predict future process quality. First, we propose the PQP as a new measure for representing process capability and performance, which is defined by a composite statistical process analysis of such factors as manufacturing cycle time analysis, process trajectory of abnormal detection, statistical process control analysis, and process capability control analysis. Second, PQP analysis results are used to predict and estimate the stability of the production process using a long short-term memory (LSTM) neural network, which is a deep learning algorithm-based method. The present work compares the LSTM prediction model with the random forest, autoregressive integrated moving average, and artificial neural network models to convincingly demonstrate the effectiveness of our proposed approach. Notably, the LSTM model achieved higher accuracy than the other models.

Quality and Safety Outcomes of a Hospital Merger Following a Full Integration at a Safety Net Hospital

Hospital consolidations have been shown not to improve quality on average. To assess a full-integration approach to hospital mergers based on quality metrics in a safety net hospital acquired by an urban academic health system. This quality improvement study analyzed outcomes for all nonpsychiatric, nonrehabilitation, non-newborn patients discharged between September 1, 2010, and August 31, 2019, at a US safety net hospital that was acquired by an urban academic health system in January 2016. Interrupted time series and statistical process control analyses were used to assess the main outcomes and measures. Data sources included the hospital's electronic health record, Centers for Medicare & Medicaid Services Hospital Compare, and nursing quality reports. A full-integration approach to the merger that included: (1) early administrative and clinical leadership integration with the academic health system; (2) rapid transition to the academic health system electronic health record; (3) local ownership of quality metrics; (4) system-level goals with real-time actionable analytics through combined dashboards; and (5) implementation of value-based and other analytic-driven interventions. The primary outcome was in-hospital mortality. Secondary outcomes included 30-day readmission, patient experience, and hospital-acquired conditions. The 122 348 patients in the premerger (September 2010 through August 2016) and the 58 904 patients in the postmerger (September 2016 through August 2019) periods had a mean (SD) age of 55.5 (22.0) years; the total sample of 181 252 patients included 112 191 women (61.9%), the payor mix was majority governmental (144 375 patients [79.7%]), and most admissions were emergent (121 469 patients [67.0%]). There was a 0.71% (95% CI, 0.57%-0.86%) absolute (27% relative) reduction in the crude mortality rate and 0.95% (95% CI, 0.83%-1.12%) absolute (33% relative) in the adjusted rate by the end of the 3-year intervention period. There was no significant improvement in readmission rates after accounting for baseline trends. There were fewer central line infections per 1000 catheter days, fewer catheter-associated urinary tract infections per 1000 discharges, and a higher likelihood of patients recommending the hospital or ranking it 9 or 10. In this quality improvement study, a hospital merger with a full-integration approach to consolidation was found to be associated with improvement in quality outcomes.

Learning Curve of Surgeons Performing Laparoscopic Ovarian Tissue Transplantation in Women with Premature Ovarian Insufficiency: A Statistical Process Control Analysis

Study ObjectiveTo analyze patient safety in laparoscopic ovarian tissue transplantation surgery by tracking the rate of postoperative complications and the learning curves of the surgeons by statistical process control analysis. DesignA retrospective study. SettingA university-affiliated hospital. PatientsA total of 100 patients with premature ovarian insufficiency who underwent ovarian tissue cryopreservation by vitrification and then autologous transplantation of frozen-thawed ovarian tissues with in vitro activation. InterventionsOvarian tissue cryopreservation, in vitro activation, and transplantation. Measurements and Main ResultsWe assessed the surgery complications, differences in total surgery time, transplantation time, and transplantation time per ovarian sheet in operations performed by 3 experienced laparoscopic surgeons. Surgeon A performed 80 operations; surgeon B, 29 operations; and surgeon C, 20 operations. Complications occurred in 1.55% of the procedures. Although all 3 surgeons’ performance never fell below the unacceptable failure limit, only surgeon A became competent after 66 cases. ConclusionThe laparoscopic ovarian tissue transplantation surgery was generally safe given that the postoperative complications were infrequent (1.55%). Although the performance of all 3 surgeons was acceptable, only surgeon A attained the level of competency after 66 cases. The transplantation method may not be the key factor for reducing surgery time in this surgery. An efficient ovarian tissue transplantation team is more important in reducing the surgery time than the surgeon's surgical technique alone.