Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Age of blood and recipient factors determine the severity of transfusion-related acute lung injury (TRALI)

Introduction Critical care patients frequently receive blood transfusions. Some reports show an association between aged or stored blood and increased morbidity and mortality, including the development of transfusion-related acute lung injury (TRALI). However, the existence of conflicting data endorses the need for research to either reject this association, or to confirm it and elucidate the underlying mechanisms. Methods Twenty-eight sheep were randomised into two groups, receiving saline or lipopolysaccharide (LPS). Sheep were further randomised to also receive transfusion of pooled and heat-inactivated supernatant from fresh (Day 1) or stored (Day 42) non-leucoreduced human packed red blood cells (PRBC) or an infusion of saline. TRALI was defined by hypoxaemia during or within two hours of transfusion and histological evidence of pulmonary oedema. Regression modelling compared physiology between groups, and to a previous study, using stored platelet concentrates (PLT). Samples of the transfused blood products also underwent cytokine array and biochemical analyses, and their neutrophil priming ability was measured in vitro. Results TRALI did not develop in sheep that first received saline-infusion. In contrast, 80% of sheep that first received LPS-infusion developed TRALI following transfusion with "stored PRBC." The decreased mean arterial pressure and cardiac output as well as increased central venous pressure and body temperature were more severe for TRALI induced by "stored PRBC" than by "stored PLT." Storage-related accumulation of several factors was demonstrated in both "stored PRBC" and "stored PLT", and was associated with increased in vitro neutrophil priming. Concentrations of several factors were higher in the "stored PRBC" than in the "stored PLT," however, there was no difference to neutrophil priming in vitro. Conclusions In this in vivo ovine model, both recipient and blood product factors contributed to the development of TRALI. Sick (LPS infused) sheep rather than healthy (saline infused) sheep predominantly developed TRALI when transfused with supernatant from stored but not fresh PRBC. "Stored PRBC" induced a more severe injury than "stored PLT" and had a different storage lesion profile, suggesting that these outcomes may be associated with storage lesion factors unique to each blood product type. Therefore, the transfusion of fresh rather than stored PRBC may minimise the risk of TRALI.

Learning how to be responsive to public policy issues affecting SSSI members

Human survival depends on human ingenuity in using resources at hand to sustain human life. The historical record – in wrings and archaeological artefacts – provides evidence of the growth and collapse of political organisations and societies. In the institutions of Western civilisation, some traditions have endured over millennia where the roles of monarchs and public officials have been organised in perpetual succession. These roles were developed as conventions in the British Parliament after 1295 and provided the models of corporate governance in both public and private enterprise that have been continuously refined to the present day. In 2011, the Queensland Parliament legislated to introduce a new and more open system of scrutiny of legislation through a system of portfolio-based parliamentary committees. The committees began to function more actively in July 2012 and have inviting submissions from stakeholders and experts in a structured way to consider the government’s priorities in its legislative programme. The questions now are whether the Surveying and Spatial Sciences can respond expertly to address the terms of reference and meet the timetables of the various parliamentary committees. This paper discusses some of the more important and urgent issues that deserve debate that the profession needs to address in becoming more responsive to matters of public policy.

Dalcetrapib restoring belief in modulating CETP as a beneficial mechanism in cardiovascular disease

Abstract Background: As low HDL cholesterol levels are a risk factor for cardiovascular disease, raising HDL cholesterol substantially by inhibiting or modulating cholesteryl ester transfer protein (CETP) may be useful in coronary artery disease. The first CETP inhibitor that went into clinical trial, torcetrapib, was shown to increase the levels of HDL cholesterol, but it also increased cardiovascular outcomes, probably due to an increase in blood pressure and aldosterone secretion, by an off-target mechanism/s. Objective/methods: Dalcetrapib is a new CETP modulator that increases the levels of HDL cholesterol, but does not increase blood pressure or aldosterone secretion. The objective was to evaluate a paper describing the effects of dalcetrapib on carotid and aortic wall thickness in subjects with, or at high risk, of coronary artery disease; the dal-PLAQUE study. Results: dal-PLAQUE showed that dalcetrapib reduced the progression of atherosclerosis and may also reduce the vascular inflammation associated with this, in subjects with, or with high risk of, coronary heart disease, who were already taking statins. Conclusions: These results suggest that modulating CETP with dalcetrapib may be a beneficial mechanism in cardiovascular disease. The results of the dal-HEART series, which includes dal-PLAQUE 1 and 2, and dal-OUTCOMES, when complete, will provide more definitive information about the benefit, or not, of dalcetrapib in coronary artery disease.