Process Quality Indicators Research Articles

Meeting clinical needs for and sidestepping supply chain threats to COVID-19 testing through continuous process improvement

Abstract Introduction/Objective The first human case of SARS-CoV-2 infection was reported in December of 2019. By late February 2020 evidence of community transmission in the United States was documented and soon it developed into a global pandemic. On March 11, 2020, the Mayo Clinic Arizona’s Microbiology Laboratory introduced a PCR test for diagnosis of SARS-CoV-2 infection. Even as testing demands exponentially increased, the hospital relied on timely results to assist in directing patient care. In order to provide timely results in the face of continuously emerging supply chain threats, we needed to increase our capacity for SARS-CoV-2 PCR testing by reducing technologist time and reagent waste, without impacting turnaround time or other quality metrics such as repeat rate. Methods/Case Report Technologist time was measured in hands-on time per specimen. Reagent use was defined by the volume of lysis buffer (the primary rate limiting reagent due to supply chain constraints) used per sample. Turnaround time was measured from receipt in lab until result verification and the rerun rate is the percent of specimens with an internal control (IC) failure, an indicator of specimen or process quality. Unnecessary steps were determined using a process map, spaghetti diagram and waste walk. Improvements included simplifying steps, changes to protocols and lab design. Impacts of the improvements were measured for 5 months post-implementation. Results (if a Case Study enter NA) Process improvements reduced technologist time per sample by 30.8 seconds and decreased critical reagent needs by 23.6%. Improvements led to $104,000 in just reagent savings over 5 months. Turnaround time and rerun rates were not negatively impacted. Conclusion By creating the leanest possible workflow, we were able to meet the demands for accurate and timely SARS-CoV-2 results. In future workflows, we will continue to implement lean processes and ensure the most efficient use of limited resources.

Work environment challenging Irish public health nurses' care quality: First postnatal visit.

Exploring views and experiences of public health nurses of their work environment and measurement of care practices at first postnatal visits. An exploratory qualitative design. Data collected using four focus groups and analyzed using thematic analysis. Nineteen public health nurses from four health service regions in Ireland participated. Two themes emerged. Theme one identified "challenges of providing a quality service." Public health nurses identified workload demands and that the working environment can detract from the ability to provide a quality service. Challenges within the home, language barriers, and lack of support from management were key issues. Theme two identified "challenges of measuring quality of public health nursing practice." While Measuring practice through quantitative outcomes such as key performance indicators were viewed as inadequate to measure the quality of care provided, positive views of using quality process indicators to measure the quality of their practice emerged. Key issues concern the working environment of public health nurses and challenges of providing and measuring care practices. Absence of appropriate supports and resources means public health nurses work hard to provide quality care. Public health nurses were confident they would score high on quality process measurements of their practice.

Higher quality of care in emergency departments with physiotherapy service models.

To investigate the quality of care provided by EDs with physiotherapy services compared to those without, using established musculoskeletal process and outcome quality indicators (QIs). An analysis was undertaken of prospective observational and chart audit data collected from 628 patients who presented with a musculoskeletal injury in any of the eight participating EDs in Queensland in 2016-2017. The care provided was scored against 46 musculoskeletal QIs. Quality of care was first compared between EDs with physiotherapists to EDs with a limited physiotherapy service, and second between EDs with primary contact physiotherapists to EDs without. χ2 and Fisher's exact tests were used to identify significant results. In the first comparison, EDs with physiotherapists performed significantly higher on 15 QIs and EDs with only limited physiotherapy performed higher on two QIs. In the second comparison, EDs with primary contact physiotherapists performed significantly higher on 17 QIs when compared to EDs without and three QIs demonstrated significance in favour of EDs without primary contact physiotherapists. Performance differences occurred across both process and outcome QIs, including musculoskeletal assessment, diagnostics, pain assessment and management, fracture management, medication safety, mobility, patient information, referrals and follow-up, re-presentations and patient experience. EDs with physiotherapists provide at least equivalent or higher quality of care for patients with musculoskeletal injuries than those EDs with limited access to physiotherapists. This may be because of their specialised training in musculoskeletal diagnosis and treatment, as well as the impact of teaching and mentoring for other ED clinicians.

Modeling of quality indicators for water demineralization process at power reactors

Regression models of demineralizing filters for a nuclear power plant will increase the efficiency of the desalination process for turbine condensate. To identify the control object, experimental and statistical research methods were applied. To detect the presence and study the extent of relations between the process factors and output variables, the STATISTICA (StatSoft) analytical system was used. The impact of factors on the studied traits was assessed using a nonlinear estimation module. Upon the analysis of the desalination plant operation, the following initial parameters were identified. These parameters influence the control decisions in managing the object, can be predicted over time and are not random variables such as the values of specific conductivity and hydrogen index. For specific electrical conductivity: Xh is the specific electrical conductivity of the condensate after the desalination plant; Na is the concentration of sodium ions in the condensate behind the condensate electric pump of the first stage; CN2H4 is the concentration of hydrazine in the feedwater of the steam generator; CFe is the concentration of iron ions in the condensate on the condensate electric pump of the first stage; T is the temperature of the condensate sample on the condensate electric pump of the first stage; CCl is the concentration of chlorine ions in the purge water of the salt compartment of the steam generator; and CSO4 is the concentration of sulfate ions in the purge water of the salt compartment of the steam generator. For the hydrogen index: pH is the hydrogen index of the condensate after the desalination plant; CN2H4 is the concentration of hydrazine in the feedwater of the steam generator; T is the temperature of the condensate sample on the condensate electric pump of the first stage; and CFe is the concentration of iron ions in the condensate behind the condensate electric pump of the first stage. To detect the presence and study the extent of relations between the selected factors of relevant process and output variables, a correlation analysis was conducted and input factors were subsequently ranked. The correlation analysis allowed ranking all the variables and their possible interaction effects in a descending degree of impact on the outputs. In accordance with the selected system outputs, based on the ranking of input variables, regression analysis was performed and corresponding mathematical dependences were obtained with alternate inclusion of factors in a decreasing degree of their influence on the output variable to establish functional dependencies between the experimental data on desalination plant operation. The regression dependence for the experimental data of specific conductivity on the selected state parameters was obtained. The coefficient of determination is equal to 0.7245. The regression dependence describing the change of the hydrogen index has also been obtained. The coefficient of determination is equal to 0.7231. The proposed models explain 72% of the variation in the dependent variable. The correlation ratio is 0.82, which determines the close relationship between the values. Regression models adequately describe the operational data of the nuclear power plant and can be used as part of the control system of the filter unit.

Between-centre differences in care for in-hospital cardiac arrest: a prospective cohort study

BackgroundSurvival after in-hospital cardiac arrest is poor, but current literature shows substantial heterogeneity in reported survival rates. This study aims to evaluate care for patients suffering in-hospital cardiac arrest (IHCA) in the Netherlands by assessing between-hospital heterogeneity in outcomes and to explain this heterogeneity stemming from differences in case-mix or differences in quality of care.MethodsA prospective multicentre study was conducted comprising 14 centres. All IHCA patients were included. The adjusted variation in structure and process indicators of quality of care and outcomes (in-hospital mortality and cerebral performance category [CPC] scale) was assessed with mixed effects regression with centre as random intercept. Variation was quantified using the median odds ratio (MOR), representing the expected odds ratio for poor outcome between two randomly picked centres.ResultsAfter excluding centres with less than 10 inclusions (2 centres), 701 patients were included of whom, 218 (32%) survived to hospital discharge. The unadjusted and case-mix adjusted MOR for mortality was 1.19 and 1.05, respectively. The unadjusted and adjusted MOR for CPC score was 1.24 and 1.19, respectively. In hospitals where personnel received cardiopulmonary resuscitation (CPR) training twice per year, 183 (64.7%) versus 290 (71.4%) patients died or were in a vegetative state, and 59 (20.8%) versus 68 (16.7%) patients showed full recovery (p < 0.001).ConclusionIn the Netherlands, survival after IHCA is relatively high and between-centre differences in outcomes are small. The existing differences in survival are mainly attributable to differences in case-mix. Variation in neurological outcome is less attributable to case-mix.

Assessment of potential process quality indicators for systemic treatment of breast cancer in Belgium: a population-based study

BackgroundQuality indicators (QIs) for the management of breast cancer (BC) have been published in Europe and internationally. In Belgium, a task force was established to select measurable process indicators of systemic treatment for BC, focusing on appropriateness of delivered care. The objective of this study was to evaluate the results of the selected QIs, both nationally and among individual centres.Patients and MethodsFemale Belgian residents with unilateral primary invasive BC diagnosed between 2010 and 2014 were selected from the Belgian Cancer Registry database. The national number enabled linkage with the national reimbursement database, which contains information on all reimbursed medical procedures. A total of 12 process indicators were measured on the population and hospital level. Intercentre variability was assessed by median results and interquartile ranges.ResultsA total of 48 872 patients were included in the study. QIs concerning specific BC subtypes only applied to patients diagnosed in 2014 (n = 9855). Clinical stage (cStage) I patients (n = 17 116) were staged with positron emission tomography/computed tomography. Among patients who were pT1aN0 human epidermal growth factor receptor 2 (HER2) positive (n = 47), 25.5% (n = 12) received adjuvant trastuzumab. Among patients with de novo metastatic luminal A/B-like HER2-negative BC (n = 295), 17.3% (n = 51) received upfront chemotherapy. (Neo)adjuvant chemotherapy was administered in 52.4% (n = 12 592) of operated women with cStage I-III, in 37.0% (n = 1270) of operated women with cStage I-III luminal A/B-like HER2-negative BC, and in 19.1% of operated women with cStage I luminal A/B-like HER2-negative BC. In the population of operated patients with cStage I-III, of those younger than 70 years that started adjuvant endocrine therapy (n = 3591), 81.7% (n = 2932) continued treatment for ≥4.5 years. Among patients in cStage I-III older than 70 years (n = 8544), 19.0% (n = 1622) received (neo)adjuvant chemotherapy, whereas among patients with cStage I-III luminal A/B-like HER2-negative BC (n = 1388), 13.0% (n = 181) received (neo)adjuvant chemotherapy. In patients with cStage I-II luminal A/B-like HER2-negative BC older than 70 years (n = 1477), 11.6% (n = 171) were not operated and received upfront endocrine treatment.ConclusionWell-considered QIs using population-based data can evaluate quality of care and expose disparities among treatment centres. Their use in daily practice should be implemented in all centres treating BC.

Impact of the algal-bacterial community structure, physio-types and biological and environmental interactions on the performance of a high rate algal pond treating biogas and wastewater

This study investigated the algal and prokaryotic community structure in an outdoors pilot High Rate Algal Pond (HRAP) that was simultaneously used for the treatment of high-strength wastewater and biogas upgrading. The algal and prokaryotic diversity was analyzed and correlated with biological and environmental parameters, and process quality indicators. The results obtained showed that the dominance of a versatile and resistant algae, such as Chlorella vulgaris, which is tolerant to high NH4+ and CO2 concentrations, concomitant to a specific prokaryotic population allowed for the obtention of biomethane with 95.2 ± 0.7% CH4, 1.4 ± 0.1% CO2 and no H2S. The bacterial community, fostered by the algal population, the light hours, and photoperiod had an important role on both biogas upgrading, through O2 and H2S elimination, and wastewater treatment. While the algal population was involved in the elimination of the ammonium of the wastewater through assimilation, the bacterial population was the main factor responsible for organic carbon, nitrate and phosphate removal, as well as nitrification. The low oxygen concentrations at night promoted bacterial denitrification, increasing the nitrite concentration in the treated wastewater. Through these findings, this research encourages photosynthetic biogas upgrading combined with wastewater treatment in HRAPs using an inoculum composed of a dominant microalgae, and an enriched prokaryotic population of aerobic chemo-organoheterotrophs, aerobic nitrifiers, and sulfur bacteria. Unlike the bacterial consortium in this study, this designed consortium can avoid the accumulation of nitrite in the cultivation broth and reduce the content of oxygen in the produced biomethane.

Understanding the Role and Value of Process Quality Indicators in Older Vascular Surgery Inpatients

Despite the development of geriatrics surgery process quality indicators (QIs), few studies have reported on these QIs in routine surgical practice. Even less is known about the links between these QIs and clinical outcomes, and patient characteristics. We aimed to measure geriatrics surgery process QIs, and investigate the association between process QIs and outcomes, and QIs and patient characteristics, in hospitalized older vascular surgery patients. This was a prospective cohort study of 150 consecutive patients aged ≥ 65 years admitted to a tertiary vascular surgery unit. Occurrence of geriatrics surgery process QIs as part of routine vascular surgery care was measured. Associations between QIs and high-risk patient characteristics, and QIs and clinical outcomes were assessed using clustered heatmaps. QI occurrence rate varied substantially from 2% to 93%. Some QIs, such as cognition and delirium screening, documented treatment preferences, and geriatrician consultation were infrequent and clustered with high-risk patient characteristcs. There were two major process-outcome clusters: (a) multidisciplinary consultations, communication and screening-based process QIs with multiple adverse outcomes, and (b) documentation and prescribing-related QIs with fewer adverse outcomes. Clustering patterns of process QIs with clinical outcomes are complex, and there is a differential occurrence of QIs by patient characteristics. Prospective intervention studies that report on implemented QIs, outcomes and patient characteristics are needed to better understand the causal pathways between process QIs and outcomes, and to help prioritize targets for quality improvement in the care of older surgical patients.

Steam boiler transfer function through fuel supply - steam pressure at boiler outlet

The article provides an analytical relationship (mathematical model) between the steam pressure at the exit of the steam boiler and the fuel supplied to the boiler. The mathematical model was determined on the basis of the characteristics obtained experimentally through the channel "fuel - steam pressure in the boiler". The experimental data were processed by the method of M.P. Simo and E.P. Stephanie. The dynamics of the change in steam pressure in a steam boiler is simulated in the Matlab (Simulink) simulation environment. The resulting model will be used to develop an automatic control system for the vaporization process. In particular, when establishing the region of stable operation of the regulator, when choosing the optimal values of the tuning parameters of the regulator that satisfy the given quality indicators of technological processes.

Research of the control system for liquids level maintenance in tanks

The problems of controlling the operating modes of pumping units with a frequency-controlled drive based on an asynchronous short-circuited motor are considered. The specific features of the requirements for the control process quality indicators of liquid level stabilization control system for the reservoirs are discussed. Mathematical models of functionally necessary parts of the system are obtained in the form of transfer functions: a frequency-controlled drive with scalar control, a generalized control object, and a feedback sensor. The linearized model of the controlled object taking into consideration a nonlinear dependence of the the torque at the motor shaft on rotational speed is obtained in the form of a transfer function of the aperiodic unit. A block diagram of a closed loop liquid level control system has been developed. It is shown that the use of standard settings for the system under consideration, focused on maximum performance achievement, can leads to unacceptable values of control action speed variations and hence to generation of hydraulic shocks that decreases a wear of kinematic parts of the unit. A method for the synthesis of the controller is proposed, which takes into account the limitations on the quality indicators of the transient process of a speed variation of the pump unit when control system counteracts main disturbances. The synthesis of controller is carried out for an example of a specific installation and the results of modeling transients of a control system and perturbing effects are discussed.

Improving The Safety Stability Of Algorithms For Recurrent State Estimation Based On The Methods Of Conditionally Gaussian Filtering.

In the world, research is underway to create a universal approach to assessing the state of stochastic control objects, focused on solving problems of adaptive control of dynamic objects. In this regard, an important task is to improve and modify methods and algorithms for adaptive estimation of the state of stochastic control objects based on the methods of conditionally Gaussian filtering in conditions of various kinds of disturbances and noises. [1] Currently, the Republic pays great attention to the areas of automation and control, including the creation of advanced control systems that provide energy and resource savings in the automation and management of various technological processes and industries. The Strategy for the Further Development of the Republic of Uzbekistan for 2017–2021 sets out the tasks ... to reduce the energy intensity and resource intensity of the economy, to widely introduce energy-saving technologies into production, and to increase labor productivity in the sectors of the economy. In this aspect, the creation of effective algorithms for adaptive estimation of the state of stochastic control objects based on the methods of conditionally Gaussian filtering, which contribute to improving the accuracy and quality indicators of control processes, is very important.

Total Value of Ownership and Overall Equipment Effectiveness analysis to evaluate the impact of automation on time and costs of therapeutic drug monitoring

Total Value of Ownership (TVO) and Overall Equipment Effectiveness (OEE) analysis are novel tools capable of monitoring and analyzing industrial processes by assessing the efficiency of the entire instrumental equipment and calculating instrument capacity utilization. Such integrated analysis, measuring quality indicators of the testing process, could also provide new perspectives and methodologies for the workflow organization of clinical laboratories. In this study, TVO and OEE were employed for the evaluation of two different configurations of a therapeutic drug monitoring sector, comparing the results obtained for immunosuppressant (ISD) and anti-epileptic drugs (AED) analysis as well as checking their quantitative performance in terms of limit of quantification, accuracy and precision. TVO analysis was performed for ISDs, including the Total Direct Labor Time, Total Cycle Time and Turnaround Time as well as cost of testing. Instruments’ performance and workload were assessed using OEE indicator, studying Availability, Performance and Quality factors. Total Cycle Time for a batch was 3.55 h, decreasing of 1.5 h in the new setting where personnel are engaged for 0.98 h, 25% of total testing time. The calculated cost per sample was 6.60 euro. Availability values were significantly higher for automated sample-handling system and ISDs analysis by LC-MS. Higher Performance values were obtained for LC-MS system for AED and other TDM. Quality values were >0.94 for all instruments. TVO and OEE proved to be applicable to clinical laboratory environment, quantifying benefits and costs of newly developed semi-automated therapeutic drug monitoring sector. This novel approach based on an integrated analysis may help activity planning and quality improvement and could be used in the future for benchmarking progress as a product/process comparison tool in other laboratory fields.

A perturbation signal based data-driven Gaussian process regression model for in-process part quality prediction in robotic countersinking operations

• Machining operations often require a post-process quality inspection step. • Robotic machining introduces further sources of errors in the manufacturing process. • In-process sensor data is used to infer key process quality indicators. • A GPR-based process model provides predictions with uncertainty quantification. • The machined part quality is robustly predicted from in-process information. A typical manufacturing process consists of a machining (material removal) process followed by an inspection system for the quality checks. Usually these checks are performed at the end of the process and they may also involve removing the part to a dedicated inspection area. This paper presents an innovative perturbation signal based data generation and machine learning approach to build a robust process model with uncertainty quantification. The model is to map the in-process signal features collected during machining with the post-process quality results obtained upon inspection of the finished product. In particular, a probabilistic framework based on Gaussian Process Regression (GPR) is applied to build the process model that accurately and reliably predicts key process quality indicators. Raw data provided by multiple sensors including accelerometers, power transducers and acoustic emissions is first collected and then processed to extract a large number of signal features from both time and frequency domains. A strategy for the selection of most relevant features is also explored in this work in order to reduce the input space dimension and achieve faster training times. The proposed GPR model was tested on a multi-robot countersinking application for monitoring of the machined countersink depths in composite aircraft components. Experimental results showed that the model can be used as a tool to predict the part quality through in-process sensory information, which in turn, helps to reduce the total inspection time by identifying the parts that would require further investigation.

Approach to modeling protozoa grazing on the basis of the current state of knowledge

Protozoa are significant components of activated sludge which purify the effluent of free swimming bacteria as well as trigger floc formation. In addition, their presence is often used as an indicator of process quality. In classical models, the impact of protozoa on biomass is implicitly included in the bacteria decay rates, which in most cases gives a sufficient level of detail. However, modeling of certain processes, such as bioaugmentation, would greatly benefit from a functional model including protozoa grazing explicitly. To further establish the approach for protozoa grazing modeling, the authors have summarized the current state of knowledge in this area, as well as pointed out crucial elements that have to be considered. Aspects of the endogenous oxygen uptake rate (OUR), the preference of protozoa towards particular bacteria groups, and alternative sources of nutrient are presented and discussed. Based on the drawn conclusions, the authors have proposed a modeling concept towards protozoa grazing that will maintain both stability and accordance with generally accepted activated sludge models (ASM). The presented approach includes a division of each bacteria group into dispersed and flocculated bacteria that emerge from newly formed flocculation and deflocculation processes, with a different level of grazing on both components.

A Scoping Review of Process Indicators for Measuring Quality of Care in Glaucoma.

There are no standardized process quality indicators (QIs) in glaucoma care. Although they can be inferred from guidelines and trials, they should be designed and standardized to allow better assessment of the quality of care. QIs are crucial for assessing the performance of any health care system. To allow efficiency, effectiveness, and patient-centeredness, there is a need for prompt acquisition of up-to-date information. Among the available QIs, process indicators have the highest sensitivity to frequent changes and could better reflect the implementation outcomes of novel ideas and technology. This study aimed to map the available information regarding process QIs in glaucoma care, identify the current development stage of these indicators, and systematically synthesize them. We performed a scoping review of 4 electronic bibliographic databases for studies reporting on process QIs in glaucoma. We retrieved 7502 references and created a domain list reflecting the core idea underlying each indicator. We summarized information from 18 documents and listed 20 domains. The most mentioned domains were follow-up, optic nerve head assessment, visual field test, and intraocular pressure. Indicators regarding the quality of life assessment, patient assistance, or presence of written protocols were less frequently mentioned. There are notable variations among process QIs in glaucoma and significant heterogeneity in their descriptions in published studies. Although novel indicators can be inferred from guidelines and trials, they should be designed and standardized for better assessment of performance in health systems to improve their quality.

Differences in nursing home admission between functionally defined populations in Germany and the association with quality of health care

BackgroundPeople prefer to age in place and not move into a nursing home as long as possible. The prevention of cognitive and functional impairments is feasible to support this goal. Health services play a key role in providing support for underlying medical conditions. We examined differentials in nursing home admissions between patient sharing networks in Germany and whether potential variations can be attributed to indicators of health care provision.MethodsWe conducted an ecological study using data of patients of 65 years and above from all 11 AOK statutory health insurance companies in Germany. Nursing home admissions were observed in a cohort of persons becoming initially care-dependent in 2006 (n = 118,213) with a follow-up of up to 10 years. A patient sharing network was constructed and indicators for quality of health care were calculated based on data of up to 6.6 million patients per year. Community detection was applied to gain distinct patient populations. Analyses were conducted descriptively and through regression analyses to identify the variation explained by included quality indicators.ResultsThe difference in the proportion of nursing home admissions between identified clusters shows an interquartile range (IQR) of 12.6% and the average time between onset of care-dependency and admission to a nursing home an IQR of 10,4 quarters. Included quality indicators attributed for 40% of these variations for the proportion of nursing home admissions and 49% for the time until nursing home admission, respectively. Indicators of process quality showed the single highest contribution. Effects of single indicators were inconclusive.ConclusionsHealth services can support persons in their preference to age in place. Research and discussion on adequate health care for care-dependent persons and on conditions, where nursing home admission may be beneficial, is necessary.

Competitive Adaptive Reweighted Sampling Method for Fault Detection

According to Darwin’s theory of evolution, a variable combination with the strongest correlation between selection process variables and quality indicators is developed. This is called competitive adaptive reweighted sampling (CARS). In this article, the absolute value of the partial least squares regression coefficient is used to assess the importance of each variable. Next, we select variables based on the regression coefficients of variables and quality indicators, including forced variable selection based on exponential decreasing function (EDF) and competitive variable selection based on adaptive reweighted sampling (ARS). Finally, we use cross-validation (CV) to select the subset with the lowest root mean square error of CV (RMSECV). The Tennessee-Eastman (TE) process is used to evaluate the performance of the proposed fault detection method. The results show that CARS can find the best combination of certain key variables, improving the fault detection capability of quality indicators.

Model-Agnostic Meta-Learning With Optimal Alternative Scaling Value and Its Application to Industrial Soft Sensing

In soft sensing, relationship variation of process variables and quality indicators may cause the model trained from the training datasets unsuitable for the prediction on the testing datasets. As the model-agnostic meta-learning can utilize the supporting datasets to strengthen the prediction performance of the query samples, it can maintain reliable prediction performance in relationship variation. However, the traditional model-agnostic meta-learning contains inconsistencies between the parameters evaluated in the training stage and those adapted in the predicting stage. The phenomenon is inferred as the dilemma of getting valuable evaluated parameters related to the initial parameters and accurate parameters representing the parameters adapted in the predicting stage. In this article, we propose the stage-related adaption block to use the model-agnostic meta-learning modularly. Finally, the model-agnostic meta-learning method based on the optimal alternative scaling value is proposed and verified in a numerical example and an industrial application.

Визначення закономірностей оцінок показників якості технологічного процесу на безрозмірній шкалі

The purpose of the article is to study the patterns of evaluation of quality indicators of the technological process on a sizeless scale. The quality of production depends on the quality of technological processes, namely - many factors of technological, technical and organizational nature. The technological process is the basis of any production process, is the most important part of it, associated with the processing of raw materials and its transformation into finished products. Product quality is the most important indicator of companies seeking to develop and succeed in competition among other manufacturers. This issue is especially relevant for Ukrainian companies seeking to be competitive in the European and world markets. To manage the quality of the object often have to use statistical methods of evaluation and management, where, as basic information you need to know not the law of distribution of quality in its units, and know the law of distribution of their assessments on a sizeless scale, therefore, research related to determining the patterns of distribution of assessments of quality indicators of the technological process on a sizeless scale. Knowing the law of distribution of unit quality indicators of the object of qualimetry and knowing the dependence with their estimates on a sizeless scale, it is possible to solve practical problems to determine the probability of getting estimates of quality indicators in a given interval. The solution of such problems is relevant in determining the risks of the processes of quality management systems, or determining the reliability of the technological process and other indicators. As a result of the study, the main conditions for the quantity and quality of statistical information were identified. It is shown that the correctness and efficiency of solving practical problems, using statistical methods of quality assessment, is determined by the amount of information about the functioning of the technological process, which can be divided into conservative and operational. Conservative information includes knowledge of the distribution law and finding effective statistical estimates of its parameters, and operational - the sample size.

Regional anaesthesia quality indicators for adult patients undergoing non-cardiac surgery: a systematic review.

Improvement in healthcare delivery depends on the ability to measure outcomes that can direct changes in the system. An overview of quality indicators within the field of regional anaesthesia is lacking. This systematic review aims to synthesise available quality indicators, as per the Donabedian framework, and provide a concise overview of evidence-based quality indicators within regional anaesthesia. A systematic literature search was conducted using the databases MEDLINE, Embase, CINAHL and Cochrane from 2003 to present, and a prespecified search of regional anaesthesia society websites and healthcare quality agencies. The quality indicators relevant to regional anaesthesia were subdivided into peri-operative structure, process and outcome indicators as per the Donabedian framework. The methodological quality of the indicators was determined as per the Oxford Centre for Evidence-Based Medicine's framework. Twenty manuscripts met our inclusion criteria and, in total, 68 unique quality indicators were identified. There were 4 (6%) structure, 12 (18%) process and 52 (76%) outcome indicators. Most of the indicators were related to the safety (57%) and effectiveness (19%) of regional anaesthesia and were general in nature (60%). In addition, most indicators (84%) were based on low levels of evidence. Our study is an important first step towards describing quality indicators for the provision of regional anaesthesia. Future research should focus on the development of structure and process quality indicators and improving the methodological quality and usability of these indicators.