Severe postpartum haemorrhage after vaginal delivery: a statistical process control chart to report seven years of continuous quality improvement

Author(s):  
Corinne Dupont ◽  
Pauline Occelli ◽  
Catherine Deneux- Tharaux ◽  
Sandrine Touzet ◽  
Antoine Duclos ◽  
...  
Author(s):  
T.E. Moongo ◽  
S. Michael

SYNOPSIS Electrowinning consumes a substantial amount of electrical energy, and owing to the ever-increasing unit cost of electrical power there is a need to improve current efficiency in the process. This research was carried out to design a continuous quality improvement framework for improving electrowinning current efficiency by applying statistical process control (SPC) on an online industrial copper electrowinning operation. A sequential mixed research methodology was applied and a statistical software package utilized for analysing data. It was concluded that metallurgical short-circuits (hotspots) had the most significant effect on current efficiency. Bringing hotspots under statistical control resulted in a 5.40% improvement in current efficiency, which is equivalent to approximately 74 t of 99.999% pure grade A copper cathode production over a period of 1.5 months. Keywords: quality, continuous improvement, continuous quality improvement, statistical process control, and current efficiency.


2021 ◽  
Vol 31 (5) ◽  
pp. 539-547
Author(s):  
Heather A. Wolfe ◽  
April Taylor ◽  
Rajeev Subramanyam

2019 ◽  
Vol 27 (1) ◽  
pp. 221-226
Author(s):  
Siyuan F. Yang ◽  
Wei-Ting K. Chien

2015 ◽  
Vol 35 (6) ◽  
pp. 1079-1092 ◽  
Author(s):  
Murilo A. Voltarelli ◽  
Rouverson P. da Silva ◽  
Cristiano Zerbato ◽  
Carla S. S. Paixão ◽  
Tiago de O. Tavares

ABSTRACT Statistical process control in mechanized farming is a new way to assess operation quality. In this sense, we aimed to compare three statistical process control tools applied to losses in sugarcane mechanical harvesting to determine the best control chart template for this quality indicator. Losses were daily monitored in farms located within Triângulo Mineiro region, in Minas Gerais state, Brazil. They were carried over a period of 70 days in the 2014 harvest. At the end of the evaluation period, 194 samples were collected in total for each type of loss. The control charts used were individual values chart, moving average and exponentially weighted moving average. The quality indicators assessed during sugarcane harvest were the following loss types: full grinding wheel, stumps, fixed piece, whole cane, chips, loose piece and total losses. The control chart of individual values is the best option for monitoring losses in sugarcane mechanical harvesting, as it is of easier result interpretation, in comparison to the others.


2018 ◽  
Vol 27 (8) ◽  
pp. 633-642 ◽  
Author(s):  
Rikke von Benzon Hollesen ◽  
Rie Laurine Rosenthal Johansen ◽  
Christina Rørbye ◽  
Louise Munk ◽  
Pierre Barker ◽  
...  

BackgroundA safe delivery is part of a good start in life, and a continuous focus on preventing harm during delivery is crucial, even in settings with a good safety record. In January 2013, the labour unit at Copenhagen University Hospital, Hvidovre, undertook a quality improvement (QI) project to prevent asphyxia and reduced the percentage of newborns with asphyxia by 48%.MethodsThe change theory consisted of two primary elements: (1) the clinical content, including three clinical bundles of evidence-based care, a ‘delivery bundle’, an ‘oxytocin bundle’ and a ‘vacuum extraction bundle’; (2) an implementation theory, including improving skills in interpretation of cardiotocography, use of QI methods and participation in a national learning network. The Model for Improvement and Deming’s system of profound knowledge were used as a methodological framework. Data on compliance with the care bundles and the number of deliveries between newborns with asphyxia (Apgar <7 after 5 min or pH <7) were analysed using statistical process control.ResultsCompliance with all three clinical care bundles improved to 95% or more, and the percentages of newborns with pH <7 and Apgar <7 after 5 min were reduced by 48% and 31%, respectively. In general, the QI approach strengthened multidisciplinary teamwork, systematised workflow and structured communication around the deliveries. Changes included making a standard memo in the medical record, the use of a bedside whiteboard, bedside handovers, shared decisions with a peer when using an oxytocin infusion and the use of a checklist before vacuum extractions.ConclusionThis QI project illustrates how aspects of patient safety, such as the prevention of asphyxia, can be improved using QI methods to more reliably implement best practice, even in high-performing systems.


2009 ◽  
Vol 33 (3) ◽  
pp. 408 ◽  
Author(s):  
Tamara G Chetter

QUALITY IMPROVEMENT is increasingly important for health care organisations both nation-wide and internationally. There is greater recognition of both the variances in patient care and the gaps between evidence-based research and current practice. At the same time, demand, not only for the quantity of services, but for higher quality services, continues to grow. Realising this, most major hospitals across Australia are initiating the redesign of hospital processes in order to maximise the timeliness and quality of patient care. But changing a process does not always result in an improvement.1,2 For this reason, a key component of any quality improvement effort is the robust measurement, analysis, and interpretation of appropriate clinical outcomes and processes, to ensure beneficial changes occur.


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