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.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Occupational Access and Wage Discrimination

This article presents a study on the quantification of the level of occupational access and wage discrimination in Great Britain. The traditional approach to quantifying the level of sex discrimination is to distinguish gender differences in productive characteristics from the unequal treatment of characteristics according to gender. The role of inter- versus intra-occupational effects in determining the magnitude of wage differences between men and women was examined. The econometric results provided estimates of the wage differential in six broad occupational classifications together with an aggregate picture of how important the occupational distribution of females is in explaining their lower average wage. In summary, the results of the study suggest that the vast majority of the male and female wage differential arises from intra-occupation effects. The results provide evidence to suggest that occupational segregation is not a major contributor to the observed male/female wage differential.

CO2 emissions from the combustion of native Australian trees

Carbon dioxide (CO2), as a primary product of combustion, is a known factor affecting climate change and global warming. In Australia, CO2 emissions from biomass burning are a significant contributor to total carbon in the atmosphere and therefore, it is important to quantify the CO2 emission factors from biomass burning in order to estimate their magnitude and impact on the Australian atmosphere. This paper presents the quantification of CO2 emission factors for five common tree species found in South East Queensland forests, as well as several grasses taken from savannah lands in the Northern Territory of Australia, under controlled ‘fast burning’ and ‘slow burning’ laboratory conditions. The results showed that CO2 emission factors varied according to the type of vegetation and burning conditions, with emission factors for fast burning being 2574 ± 254 g/kg for wood, 394 ± 40 g/kg for branches and leaves, and 2181 ± 120 g/kg for grass. Under slow burning conditions, the CO2 emission factors were 218 ± 20 g/kg for wood, 392± 80 g/kg for branches and leaves, and 2027 ± 809 g/kg for grass.

Optimal image sample size for corneal nerve morphometry

Purpose Arbitrary numbers of corneal confocal microscopy images have been used for analysis of corneal subbasal nerve parameters under the implicit assumption that these are a representative sample of the central corneal nerve plexus. The purpose of this study is to present a technique for quantifying the number of random central corneal images required to achieve an acceptable level of accuracy in the measurement of corneal nerve fiber length and branch density. Methods Every possible combination of 2 to 16 images (where 16 was deemed the true mean) of the central corneal subbasal nerve plexus, not overlapping by more than 20%, were assessed for nerve fiber length and branch density in 20 subjects with type 2 diabetes and varying degrees of functional nerve deficit. Mean ratios were calculated to allow comparisons between and within subjects. Results In assessing nerve branch density, eight randomly chosen images not overlapping by more than 20% produced an average that was within 30% of the true mean 95% of the time. A similar sampling strategy of five images was 13% within the true mean 80% of the time for corneal nerve fiber length. Conclusions The “sample combination analysis” presented here can be used to determine the sample size required for a desired level of accuracy of quantification of corneal subbasal nerve parameters. This technique may have applications in other biological sampling studies.

Airborne concentration of Volatile Organic Compounds in school environment in Brisbane

Traffic emissions are considered as a major source of pollutants, particularly ultrafine particles, in the urban environment. There is an increased concern about airborne particles not only because of their environmental effects but also due to their potential adverse health effects on humans. There have been a number of studies related to the number concentration and size distribution of these particles but studies on the chemical composition of aerosols, especially in the school environment, are very limited. Mejia et. al (2011) reviewed studies on the exposure to and impact of air pollutants on school children and found that there were only a handful of studies on this topic. Therefore, the main focus of this research is on an analysis of the chemical composition of airborne particles, as well as source apportionment and the quantification of ambient concentrations of organic pollutants in the vicinity of schools, as a part of “Ultrafine Particles from Traffic Emissions on Children’s Health” (UPTECH) project. The aim of the present study was to find out the concentrations of different Volatile Organic Compounds (VOCs) in both outdoor and indoor locations from six different schools in Brisbane.

Preliminary results on the chemical composition of outdoor airborne particles at urban schools and possible implications for the air quality in classrooms

Vehicle emissions are a significant source of fine particles (Dp < 2.5 µm) in an urban environment. These fine particles have been shown to have detrimental health effects, with children thought to be more susceptible. Vehicle emissions are mainly carbonaceous in nature, and carbonaceous aerosols can be defined as either elemental carbon (EC) or organic carbon (OC). EC is a soot-like material emitted from primary sources while OC fraction is a complex mixture of hundreds of organic compounds from either primary or secondary sources (Cao et al., 2006). Therefore the ratio of OC/EC can aid in the identification of source. The purpose of this paper is to use the concentration of OC and EC in fine particles to determine the levels of vehicle emissions in schools. It is expected that this will improve the understanding of the potential exposure of children in a school environment to vehicle emissions.

Spatial variation of particle number concentration in school microscale environment

There is significant toxicological evidence of the effects of ultrafine particles (<100nm) on human health (WHO 2005). Studies show that the number concentration of particles has been associated with adverse human health effects (Englert 2004). This work is part of a major study called ‘Ultrafine Particles form Traffic Emissions and Children’s Health’ (UPTECH), which seeks to determine the effect of the exposure to traffic related ultrafine particles on children’s health in schools (http://www.ilaqh.qut.edu.au/Misc/UPT ECH%20Home.htm). Quantification of spatial variation of particle number concentration (PNC) in a microscale environment and identification of the main affecting parameters and their contribution levels are the main aims of this analysis.

Using expedited 10g protein counter (EP-10) for meal planning

Precise protein quantification and recommendation is essential in clinical dietetics, particularly in the management of individuals with chronic kidney disease, malnutrition, burns, wounds, pressure ulcers, and those in active sports. The Expedited 10g Protein Counter (EP-10) was developed to simplify the quantification of dietary protein for assessment and recommendation of protein intake.1 Instead of using separate protein exchanges for different food groups to quantify the dietary protein intake of an individual, every exchange in the EP-10 accounts for an exchange each of 3g non-protein-rich food and 7g protein-rich food (Table 1). The EP-10 was recently validated and published in the Journal of Renal Nutrition recently.1 This study demonstrated that using the EP-10 for dietary protein intake quantification had clinically acceptable validity and reliability when compared with the conventional 7g protein exchange while requiring less time.2 In clinical practice, the use of efficient, accurate and practical methods to facilitate assessment and treatment plans is important. The EP-10 can be easily implemented in the nutrition assessment and recommendation for a patient in the clinical setting. This patient education tool was adapted from materials printed in the Journal of Renal Nutrition.1 The tool may be used as presented or adapted to assist patients to achieve their recommended daily protein intake.

Nutritional intervention incorporating expedited 10g protein counter (EP-10) to improve the albumin and transferrin of chronic hemodialysis patients

Objective: The expedited 10g protein counter (EP-10) is a quick and valid clinical tool for dietary protein quantification. This study aims to assess the clinical effectiveness of the EP-10 in improving serum albumin and transferrin in chronic hemodialysis patients. Methods: Forty-five patients with low serum albumin (< 38 g /L) were enrolled in this study. Parameters measured included dry weight, height, dietary intake, and levels of serum albumin, transferrin, potassium, phosphate and kinetic modeling (Kt/v). The nutritional intervention incorporated the EP-10 in two ways (1)lto quantify protein intake of patients and (2)ito educate patients to meet their protein requirements. Mean values of the nutritional parameters before and after intervention were compared using paired t-test. Results: Three months after nutritional intervention, mean albumin levels increased significantly from 32.2+4.8g/L to 37.0+3.2g/L (p<0.001). Thirty-eight (84%) patients showed an increase in albumin levels while two (4%) maintained their levels. Of the thirty-six (80%) patients with low transferrin levels (<200 mg/dL), 28 (78%) had an increase and two maintained their levels post-intervention. Mean transferrin levels increased significantly from 169.4+39.9mg/dL to 180.9+38.1mg/dL (p< 0.05). Conclusion: Nutritional intervention incorporating the EP-10 method is able to make significant improvements to albumin and transferrin levels of chronic hemodialysis patients.

Investigating the deployment of project management : a new perspective based on the concept of certification

Purpose – The purpose of this paper is to provide a summary description of the doctoral thesis investigating the field of project management (PM) deployment. Researchers will be informed of the current contributions within this topic and of the possible further investigations and researches. The decision makers and practitioners will be aware of a set of tools addressing the PM deployment with new perspectives. Design/methodology/approach – Research undertaken with the thesis is based on quantitative methods using time series statistics (time distance analysis) and comparative and correlation analysis aimed to better define and understand the PM deployment within and between countries or groups. Findings – The results suggest a project management deployment index (PMDI) to objectively measure the PM deployment based on the concept of certification. A proposed framework to empirically benchmark the PM deployment between countries by integrating the PMDI time series with the two dimensional comparative analysis of Sicherl. The correlation analysis within Hoftsede cultural framework shows the impact of the national culture dimensions on the PM deployment. The forecasting model shows a general continual growth trend of the PM deployment, with continual increase in the time distance between the countries. Research limitations/implications – The PM researchers are offered an empirical quantification on which they can construct further investigations and understanding of this phenomenon. The number of possible units that can be studied offers wide possibilities to replicate the thesis work. New researches can be undertaken to investigate further the contribution of other social or economical indicators, or to refine and enrich the definition of the PMDI indicator. Practical implications – These results have important implications on the PM deployment approaches. The PMDI measurements and time series comparisons facilitate considerably the measurement and benchmarking between the units (e.g. countries) and against targets, while the readiness setting of the studied unit (in terms of development and cultural levels) impacts the PM deployment within this country. Originality/value – This paper provides a summary of cutting-edge research work in the studied field of PM deployment and a link to the published works that researchers can use to help them understand the thesis research as well as how it can be extended.

Evaluation of the cost-effectiveness of strategies claiming to reduce the risk of surgical site infections following primary total hip arthroplasty

Background Total hip arthroplasty (THA) is a commonly performed procedure and numbers are increasing with ageing populations. One of the most serious complications in THA are surgical site infections (SSIs), caused by pathogens entering the wound during the procedure. SSIs are associated with a substantial burden for health services, increased mortality and reduced functional outcomes in patients. Numerous approaches to preventing these infections exist but there is no gold standard in practice and the cost-effectiveness of alternate strategies is largely unknown. Objectives The aim of this project was to evaluate the cost-effectiveness of strategies claiming to reduce deep surgical site infections following total hip arthroplasty in Australia. The objectives were: 1. Identification of competing strategies or combinations of strategies that are clinically relevant to the control of SSI related to hip arthroplasty 2. Evidence synthesis and pooling of results to assess the volume and quality of evidence claiming to reduce the risk of SSI following total hip arthroplasty 3. Construction of an economic decision model incorporating cost and health outcomes for each of the identified strategies 4. Quantification of the effect of uncertainty in the model 5. Assessment of the value of perfect information among model parameters to inform future data collection Methods The literature relating to SSI in THA was reviewed, in particular to establish definitions of these concepts, understand mechanisms of aetiology and microbiology, risk factors, diagnosis and consequences as well as to give an overview of existing infection prevention measures. Published economic evaluations on this topic were also reviewed and limitations for Australian decision-makers identified. A Markov state-transition model was developed for the Australian context and subsequently validated by clinicians. The model was designed to capture key events related to deep SSI occurring within the first 12 months following primary THA. Relevant infection prevention measures were selected by reviewing clinical guideline recommendations combined with expert elicitation. Strategies selected for evaluation were the routine use of pre-operative antibiotic prophylaxis (AP) versus no use of antibiotic prophylaxis (No AP) or in combination with antibiotic-impregnated cement (AP & ABC) or laminar air operating rooms (AP & LOR). The best available evidence for clinical effect size and utility parameters was harvested from the medical literature using reproducible methods. Queensland hospital data were extracted to inform patients’ transitions between model health states and related costs captured in assigned treatment codes. Costs related to infection prevention were derived from reliable hospital records and expert opinion. Uncertainty of model input parameters was explored in probabilistic sensitivity analyses and scenario analyses and the value of perfect information was estimated. Results The cost-effectiveness analysis was performed from a health services perspective using a hypothetical cohort of 30,000 THA patients aged 65 years. The baseline rate of deep SSI was 0.96% within one year of a primary THA. The routine use of antibiotic prophylaxis (AP) was highly cost-effective and resulted in cost savings of over $1.6m whilst generating an extra 163 QALYs (without consideration of uncertainty). Deterministic and probabilistic analysis (considering uncertainty) identified antibiotic prophylaxis combined with antibiotic-impregnated cement (AP & ABC) to be the most cost-effective strategy. Using AP & ABC generated the highest net monetary benefit (NMB) and an incremental $3.1m NMB compared to only using antibiotic prophylaxis. There was a very low error probability that this strategy might not have the largest NMB (<5%). Not using antibiotic prophylaxis (No AP) or using both antibiotic prophylaxis combined with laminar air operating rooms (AP & LOR) resulted in worse health outcomes and higher costs. Sensitivity analyses showed that the model was sensitive to the initial cohort starting age and the additional costs of ABC but the best strategy did not change, even for extreme values. The cost-effectiveness improved for a higher proportion of cemented primary THAs and higher baseline rates of deep SSI. The value of perfect information indicated that no additional research is required to support the model conclusions. Conclusions Preventing deep SSI with antibiotic prophylaxis and antibiotic-impregnated cement has shown to improve health outcomes among hospitalised patients, save lives and enhance resource allocation. By implementing a more beneficial infection control strategy, scarce health care resources can be used more efficiently to the benefit of all members of society. The results of this project provide Australian policy makers with key information about how to efficiently manage risks of infection in THA.

Comparative study of depth-dependent characteristics of equine and human osteochondral tissue from the medial and lateral femoral condyles

Articular cartilage defects are common after joint injuries. When left untreated, the biomechanical protective function of cartilage is gradually lost, making the joint more susceptible to further damage, causing progressive loss of joint function and eventually osteoarthritis (OA). In the process of translating promising tissue-engineering cartilage repair approaches from bench to bedside, pre-clinical animal models including mice, rabbits, goats, and horses, are widely used. The equine species is becoming an increasingly popular model for the in vivo evaluation of regenerative orthopaedic approaches. As there is also an increasing body of evidence suggesting that successful lasting tissue reconstruction requires an implant that mimics natural tissue organization, it is imperative that depth-dependent characteristics of equine osteochondral tissue are known, to assess to what extent they resemble those in humans. Therefore, osteochondral cores (4-8 mm) were obtained from the medial and lateral femoral condyles of equine and human donors. Cores were processed for histology and for biochemical quantification of DNA, glycosaminoglycan (GAG) and collagen content. Equine and human osteochondral tissues possess similar geometrical (thickness) and organizational (GAG, collagen and DNA distribution with depth) features. These comparable trends further underscore the validity of the equine model for the evaluation of regenerative approaches for articular cartilage.

Double blind : women as creative practice-led researchers

While the productive relationship between praxis and feminist research has been well established, the situation is more complicated for female artist/researchers in the fraught field of creative practice-led research. Firstly, their research is being conducted in the context of ongoing debate, as Andrea Phillips has summarized, over whether practice-led research has been embraced in order to potentially produce emancipatory knowledge, or whether it is simply the rationalization and quantification of creative processes. Secondly, there is a pervasive paradox whereby, rather than feeling empowered by the process of critical and reflective self-analysis, many women are inhibited by enduring insecurities about the value of their work and/or their ownership of it. The reasons for this appear to be twofold: they are disheartened by the ongoing disproportion of successful women artists, and they are intimidated by the fundamentally masculine discourse surrounding research in the university. Many of these anxieties appear to have been exacerbated by the research quality assessment process, the Excellence in Research for Australia Initiative (ERA). This collaborative paper draws on the authors' experiences as both artist-researchers and educators to contextualize this paradox and also discuss what forms of praxis intervention may be useful in the preparation for, and supervision of, creative practice-led research by women.

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010 : a systematic analysis for the Global Burden of Disease Study 2010

Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.