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.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions

In this paper we develop set of novel Markov Chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. The novel diffusion bridge proposal derived from the variational approximation allows the use of a flexible blocking strategy that further improves mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample applications the algorithm is accurate except in the presence of large observation errors and low to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient. © 2011 Springer-Verlag.

Scabies outbreak in an intensive care unit with 1,659 exposed individuals--key factors for controlling the outbreak

OBJECTIVE: To investigate a large outbreak of scabies in an intensive care unit of a university hospital and an affiliated rehabilitation center, and to establish effective control measures to prevent further transmission. DESIGN: Outbreak investigation. SETTING: The intensive care unit of a 750-bed university hospital and an affiliated 92-bed rehabilitation center. METHODS: All exposed individuals were screened by a senior staff dermatologist. Scabies was diagnosed on the basis of (1) identification of mites by skin scraping, (2) identification of mites by dermoscopy, or (3) clinical examination of patients without history of prior treatment for typical burrows. During a follow-up period of 6 months, the attack rate was calculated as the number of symptomatic individuals divided by the total number of exposed individuals. INTERVENTIONS: All exposed healthcare workers (HCWs) and their household members underwent preemptive treatment. Initially, the most effective registered drug in Switzerland (ie, topical lindane) was prescribed, but this prescription was switched to topical permethrin or systemic ivermectin as a result of the progression of the outbreak. Individuals with any signs or symptoms of scabies underwent dermatological examination. RESULTS: Within 7 months, 19 cases of scabies were diagnosed, 6 in children with a mean age of 3.1 years after exposure to the index patient with HIV and crusted scabies. A total of 1,640 exposed individuals underwent preemptive treatment. The highest attack rate of 26%-32% was observed among HCWs involved in the care of the index patient. A too-restricted definition of individuals at risk, noncompliance with treatment, and the limited effectiveness of lindane likely led to treatment failure, relapse, and reinfestation within families. CONCLUSIONS: Crusted scabies resulted in high attack rates among HCWs and household contacts. Timely institution of hygienic precautions with close monitoring and widespread, simultaneous scabicide treatment of all exposed individuals are essential for control of an outbreak.

Cost effectiveness of antimicrobial catheters in the intensive care unit : Addressing uncertainty in the decision

Introduction: Some types of antimicrobial-coated central venous catheters (A-CVC) have been shown to be cost-effective in preventing catheter-related bloodstream infection (CR-BSI). However, not all types have been evaluated, and there are concerns over the quality and usefulness of these earlier studies. There is uncertainty amongst clinicians over which, if any, antimicrobial-coated central venous catheters to use. We re-evaluated the cost-effectiveness of all commercially available antimicrobialcoated central venous catheters for prevention of catheter-related bloodstream infection in adult intensive care unit (ICU) patients. Methods: We used a Markov decision model to compare the cost-effectiveness of antimicrobial-coated central venous catheters relative to uncoated catheters. Four catheter types were evaluated; minocycline and rifampicin (MR)-coated catheters; silver, platinum and carbon (SPC)-impregnated catheters; and two chlorhexidine and silver sulfadiazine-coated catheters, one coated on the external surface (CH/SSD (ext)) and the other coated on both surfaces (CH/SSD (int/ext)). The incremental cost per qualityadjusted life-year gained and the expected net monetary benefits were estimated for each. Uncertainty arising from data estimates, data quality and heterogeneity was explored in sensitivity analyses. Results: The baseline analysis, with no consideration of uncertainty, indicated all four types of antimicrobial-coated central venous catheters were cost-saving relative to uncoated catheters. Minocycline and rifampicin-coated catheters prevented 15 infections per 1,000 catheters and generated the greatest health benefits, 1.6 quality-adjusted life-years, and cost-savings, AUD $130,289. After considering uncertainty in the current evidence, the minocycline and rifampicin-coated catheters returned the highest incremental monetary net benefits of $948 per catheter; but there was a 62% probability of error in this conclusion. Although the minocycline and rifampicin-coated catheters had the highest monetary net benefits across multiple scenarios, the decision was always associated with high uncertainty. Conclusions: Current evidence suggests that the cost-effectiveness of using antimicrobial-coated central venous catheters within the ICU is highly uncertain. Policies to prevent catheter-related bloodstream infection amongst ICU patients should consider the cost-effectiveness of competing interventions in the light of this uncertainty. Decision makers would do well to consider the current gaps in knowledge and the complexity of producing good quality evidence in this area.

Nurse staffing levels and the incidence of mortality and morbidity in the adult intensive care unit : a literature review

BACKGROUND: Studies have shown that nurse staffing levels, among many other factors in the hospital setting, contribute to adverse patient outcomes. Concerns about patient safety and quality of care have resulted in numerous studies being conducted to examine the relationship between nurse staffing levels and the incidence of adverse patient events in both general wards and intensive care units. AIM: The aim of this paper is to review literature published in the previous 10 years which examines the relationship between nurse staffing levels and the incidence of mortality and morbidity in adult intensive care unit patients. METHODS: A literature search from 2002 to 2011 using the MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, and Australian digital thesis databases was undertaken. The keywords used were: intensive care; critical care; staffing; nurse staffing; understaffing; nurse-patient ratios; adverse outcomes; mortality; ventilator-associated pneumonia; ventilator-acquired pneumonia; infection; length of stay; pressure ulcer/injury; unplanned extubation; medication error; readmission; myocardial infarction; and renal failure. A total of 19 articles were included in the review. Outcomes of interest are patient mortality and morbidity, particularly infection and pressure ulcers. RESULTS: Most of the studies were observational in nature with variables obtained retrospectively from large hospital databases. Nurse staffing measures and patient outcomes varied widely across the studies. While an overall statistical association between increased nurse staffing levels and decreased adverse patient outcomes was not found in this review, most studies concluded that a trend exists between increased nurse staffing levels and decreased adverse events. CONCLUSION: While an overall statistical association between increased nurse staffing levels and decreased adverse patient outcomes was not found in this review, most studies demonstrated a trend between increased nurse staffing levels and decreased adverse patient outcomes in the intensive care unit which is consistent with previous literature. While further more robust research methodologies need to be tested in order to more confidently demonstrate this association and decrease the influence of the many other confounders to patient outcomes; this would be difficult to achieve in this field of research.

Saudi Arabian adult intensive care unit pressure ulcer incidence and risk factors: A prospective cohort study

The purpose of this study was to identify pressure ulcer (PU) incidence and risk factors that are associated with PU development in patients in two adult intensive care units (ICU) in Saudi Arabia. A prospective cohort study design was used. A total of 84 participants were screened second daily basis until discharge or death, over a consecutive 30-day period, out of which 33 participants with new PUs were identified giving a cumulative hospital-acquired PU incidence of 39·3% (33/84 participants). The incidence of medical devices-related PUs was 8·3% (7/84). Age, length of stay in the ICU, history of cardiovascular disease and kidney disease, infrequent repositioning, time of operation, emergency admission, mechanical ventilation and lower Braden Scale scores independently predicted the development of a PU. According to binary logistic regression analyses, age, longer stay in ICU and infrequent repositioning were significant predictors of all stages of PUs, while the length of stay in the ICU and infrequent repositioning were associated with the development of stages II-IV PUs. In conclusion, PU incidence rate was higher than that reported in other international studies. This indicates that urgent attention is required for PU prevention strategies in this setting.

Aspirin therapy in patients with acute respiratory distress syndrome (ARDS) is associated with reduced intensive care unit mortality: a prospective analysis

INTRODUCTION: Acute respiratory distress syndrome (ARDS) is a common clinical syndrome with high mortality and long-term morbidity. To date there is no effective pharmacological therapy. Aspirin therapy has recently been shown to reduce the risk of developing ARDS, but the effect of aspirin on established ARDS is unknown.

METHODS: In a single large regional medical and surgical ICU between December 2010 and July 2012, all patients with ARDS were prospectively identified and demographic, clinical, and laboratory variables were recorded retrospectively. Aspirin usage, both pre-hospital and during intensive care unit (ICU) stay, was included. The primary outcome was ICU mortality. We used univariate and multivariate logistic regression analyses to assess the impact of these variables on ICU mortality.

RESULTS: In total, 202 patients with ARDS were included; 56 (28%) of these received aspirin either pre-hospital, in the ICU, or both. Using multivariate logistic regression analysis, aspirin therapy, given either before or during hospital stay, was associated with a reduction in ICU mortality (odds ratio (OR) 0.38 (0.15 to 0.96) P = 0.04). Additional factors that predicted ICU mortality for patients with ARDS were vasopressor use (OR 2.09 (1.05 to 4.18) P = 0.04) and APACHE II score (OR 1.07 (1.02 to 1.13) P = 0.01). There was no effect upon ICU length of stay or hospital mortality.

CONCLUSION: Aspirin therapy was associated with a reduced risk of ICU mortality. These data are the first to demonstrate a potential protective role for aspirin in patients with ARDS. Clinical trials to evaluate the role of aspirin as a pharmacological intervention for ARDS are needed.

Tackling the problem of blood culture contamination in the intensive care unit using an educational intervention

Blood culture contamination (BCC) has been associated with unnecessary antibiotic use, additional laboratory tests and increased length of hospital stay thus incurring significant extra hospital costs. We set out to assess the impact of a staff educational intervention programme on decreasing intensive care unit (ICU) BCC rates to <3% (American Society for Microbiology standard). BCC rates during the pre-intervention period (January 2006-May 2011) were compared with the intervention period (June 2011-December 2012) using run chart and regression analysis. Monthly ICU BCC rates during the intervention period were reduced to a mean of 3·7%, compared to 9·5% during the baseline period (P < 0·001) with an estimated potential annual cost savings of about £250 100. The approach used was simple in design, flexible in delivery and efficient in outcomes, and may encourage its translation into clinical practice in different healthcare settings.

Five-year evolution of drug prescribing in a university adult intensive care unit

Introduction: Drug prescription is difficult in ICUs as prescribers are many, drugs expensive and decisions complex. In our ICU, specialist clinicians (SC) are entitled to prescribe a list of specific drugs, negotiated with intensive care physicians (ICP). The objective of this investigation was to assess the 5-year evolution of quantity and costs of drug prescription in our adult ICU and identify the relative costs generated by ICP or SC. Methods: Quantities and costs of drugs delivered on a quarterly basis to the adult ICU of our hospital between 2004 and 2008 were extracted from the pharmacy database by ATC code, an international five-level classification system. Within each ATC first level, drugs with either high level of consumption, high costs or large variations in quantities and costs were singled out and split by type of prescriber, ICP or SC. Cost figures used were drug purchase prices by the hospital pharmacy. Results: Over the 5-year period, both quantities and costs of drugs increased, following a nonsteady, nonparallel pattern. Four ATC codes accounted for 80% of both quantities and costs, with ATC code B (blood and haematopoietic organs) amounting to 63% in quantities and 41% in costs, followed by ATC code J (systemic anti-infective, 20% of the costs), ATC code N (nervous system, 11% of the costs) and ATC code C (cardiovascular system, 8% of the costs). Prescription by SC amounted to 1% in drug quantities, but 19% in drug costs. The rate of increase in quantities and costs was seven times larger for ICP than for SC (Figure 1 overleaf ). Some peak values in costs and quantities were related to a very limited number of patients. Conclusions: A 5-year increase in quantities and costs of drug prescription in an ICU is a matter of concern. Rather unexpectedly, total costs and cost increases were generated mainly by ICP. A careful follow-up is necessary to try influencing this evolution through an institutional policy co-opted by all professional categories involved in the process.

Case-case-control study of risk factors for nasopharyngeal colonization with methicillin-resistant Staphylococcus aureus in a medical-surgical intensive care unit

Nasopharyngeal colonization with methicillin-resistant Staphylococcus aureus (MRSA) often precedes the development of nosocomial infections. In order to identify risk factors for MRSA colonization, we conducted a case-case-control study, enrolling 122 patients admitted to a medical-surgical intensive care unit (ICU). All patients had been screened for nasopharyngeal colonization with S. aureus upon admission and weekly thereafter. Two case-control studies were performed, using as cases patients who acquired colonization with MRSA and methicillin-susceptible S. aureus (MSSA), respectively. For both studies, patients in whom colonization was not detected during ICU stay were selected as control subjects. Several potential risk factors were assessed in univariate and multivariable (logistic regression) analysis. MRSA and MSSA were recovered from nasopharyngeal samples from 27 and 10 patients, respectively. Independent risk factors for MRSA colonization were: length-of-stay in the ICU (Odds Ratio [OR]=1.12, 95%Confidence Interval[CI]=1.06-1.19, p<0.001) and use of ciprofloxacin (OR=5.05, 95%CI=1.38-21.90, p=0.015). The use of levofloxacin had a protective effect (OR=0.08, 95%CI=0.01-0.55, p=0.01). Colonization with MSSA was positively associated with central nervous system disease (OR=7.45, 95%CI=1.33-41.74, p=0.02) and negatively associated with age (OR=0.94, 95%CI=0.90-0.99, p=0.01). In conclusion, our study suggests a role for both cross-transmission and selective pressure of antimicrobials in the spread of MRSA.

Erythrocyte selenium concentration predicts intensive care unit and hospital mortality in patients with septic shock: a prospective observational study

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