Chief Executive Officers' Perceptions of Collective Organizational Engagement and Patient Experience in Acute Care Hospitals.

The concept of employee engagement has garnered considerable attention in acute care hospitals because of the many positive benefits that research has found when clinicians are individually engaged. However, limited, if any, research has examined the effects of engaging all hospital employees (including housekeeping, cafeteria, and admissions staff) in a collective manner and how this may impact patient experience, an important measure of hospital performance. Therefore, this quantitative online survey-based study examines the association between 60 chief executive officers' (CEOs') perceptions of the collective organizational engagement (COE) of all hospital employees and patient experience. A summary measure of the US Hospital Consumer Assessment of Healthcare Providers and Systems survey scores was used to assess patient experience at each of the 60 hospitals represented in the study. A multiple linear regression model was tested using structural equation modeling. The findings of the research suggest that CEOs' perceptions of COE explain a significant amount of variability in patient experience at acute care hospitals. Practical implications for CEOs and other hospital leaders are provided that discuss how COE can be used as an organizational capability to influence organizational performance.

Drift dynamics in microbial communities and the effective community size.

The structure and diversity of all open microbial communities are shaped by individual births, deaths, speciation and immigration events; the precise timings of these events are unknowable and unpredictable. This randomness is manifest as ecological drift in the population dynamics, the importance of which has been a source of debate for decades. There are theoretical reasons to suppose that drift would be imperceptible in large microbial communities, but this is at odds with circumstantial evidence that effects can be seen even in huge, complex communities. To resolve this dichotomy we need to observe dynamics in simple systems where key parameters, like migration, birth and death rates can be directly measured. We monitored the dynamics in the abundance of two genetically modified strains of Escherichia coli, with tuneable growth characteristics, that were mixed and continually fed into 10 identical chemostats. We demonstrated that the effects of demographic (non-environmental) stochasticity are very apparent in the dynamics. However, they do not conform to the most parsimonious and commonly applied mathematical models, where each stochastic event is independent. For these simple models to reproduce the observed dynamics we need to invoke an 'effective community size', which is smaller than the census community size.

Probabilistic models to describe the dynamics of migrating microbial communities.

In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete) model simulates absolute numbers of individual cells, whereas the other (continuous) model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported.

Spatial-temporal survey and occupancy-abundance modeling to predict bacterial community dynamics in the drinking water microbiome.

UNLABELLED: Bacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment. Understanding bacterial dynamics in the distribution system is critical to ensuring that safe drinking water is being supplied to customers. We present a 15-month survey of bacterial community dynamics in the drinking water system of Ann Arbor, MI. By sampling the water leaving the treatment plant and at nine points in the distribution system, we show that the bacterial community spatial dynamics of distance decay and dispersivity conform to the layout of the drinking water distribution system. However, the patterns in spatial dynamics were weaker than those for the temporal trends, which exhibited seasonal cycling correlating with temperature and source water use patterns and also demonstrated reproducibility on an annual time scale. The temporal trends were driven by two seasonal bacterial clusters consisting of multiple taxa with different networks of association within the larger drinking water bacterial community. Finally, we show that the Ann Arbor data set robustly conforms to previously described interspecific occupancy abundance models that link the relative abundance of a taxon to the frequency of its detection. Relying on these insights, we propose a predictive framework for microbial management in drinking water systems. Further, we recommend that long-term microbial observatories that collect high-resolution, spatially distributed, multiyear time series of community composition and environmental variables be established to enable the development and testing of the predictive framework. IMPORTANCE: Safe and regulation-compliant drinking water may contain up to millions of microorganisms per liter, representing phylogenetically diverse groups of bacteria, archaea, and eukarya that affect public health, water infrastructure, and the aesthetic quality of water. The ability to predict the dynamics of the drinking water microbiome will ensure that microbial contamination risks can be better managed. Through a spatial-temporal survey of drinking water bacterial communities, we present novel insights into their spatial and temporal community dynamics and recommend steps to link these insights in a predictive framework for microbial management of drinking water systems. Such a predictive framework will not only help to eliminate microbial risks but also help to modify existing water quality monitoring efforts and make them more resource efficient. Further, a predictive framework for microbial management will be critical if we are to fully anticipate the risks and benefits of the beneficial manipulation of the drinking water microbiome.

Terminal pathologies affect rates of decline to different extents and age accelerates the effects of terminal pathology on cognitive decline.

OBJECTIVES: To test whether different terminal pathologies are associated with different rates of age-related decline in fluid and crystallized mental abilities and whether pathology-associated declines are accelerated by age. METHODS: During a 20-year longitudinal study, 6203 participants were quadrennially assessed on the Heim's (Heim, A 1970) The AH4 series of intelligence tests Slough, U.K.: NEP) AH4-1 and AH4-2 tests of fluid intelligence and on the Raven's (Raven, J. C. 1965) The Mill Hill Vocabulary Scale London: H.K. Lewis) Mill Hill A and B tests of recognition and production vocabulary. Dates and proximate causes of death were logged for 2499 participants. Multilevel modelling compared rates of decline after effects of sex, demographics, and practice were taken into consideration. RESULTS: Rates of cognitive decline markedly differed across pathologies, being most rapid for dementias and infections, slower for malignancies, and most prolonged for cardiovascular conditions. Pathologies were associated with faster declines in older individuals. DISCUSSION: After sex, age, and demographics have also been considered, different terminal pathologies are associated with markedly different rates of decline. Age accelerates pathology-related decline. This raises the further question as to whether any, or how much of, age-related cognitive decline is brought about by other causes than an increasing burden of pathologies.

Combined niche and neutral effects in a microbial wastewater treatment community.

It has long been assumed that differences in the relative abundance of taxa in microbial communities reflect differences in environmental conditions. Here we show that in the economically and environmentally important microbial communities in a wastewater treatment plant, the population dynamics are consistent with neutral community assembly, where chance and random immigration play an important and predictable role in shaping the communities. Using dynamic observations, we demonstrate a straightforward calibration of a purely neutral model and a parsimonious method to incorporate environmental influence on the reproduction (or birth) rate of individual taxa. The calibrated model parameters are biologically plausible, with the population turnover and diversity in the heterotrophic community being higher than for the ammonia oxidizing bacteria (AOB) and immigration into AOB community being relatively higher. When environmental factors were incorporated more of the variance in the observations could be explained but immigration and random reproduction and deaths remained the dominant driver in determining the relative abundance of the common taxa. Consequently we suggest that neutral community models should be the foundation of any description of an open biological system.

Cytokines and IGF-I in delirious and non-delirious acutely ill older medical inpatients.

BACKGROUND: therapeutic use of cytokines can induce delirium, and delirium often occurs during infections associated with elevated levels of cytokines. This study examined the association of demographic, clinical and biological factors (IL-1alpha, IL-1beta, IL-1RA, IL-6, TNF-alpha, IFN-gamma, LIF, IGF-I, APOE genotype) with the presence and severity of delirium. METHODS: in an observational prospective longitudinal study, patients aged 70+ were recruited from an elderly medical unit and assessed every 3-4 days (maximum assessments 4). At each time, the scales MMSE, DRS, CAM, APACHEII were administered and blood was withdrawn to estimate the above biological factors. Mixed effects (PQL) and GEE were used to analyse the repeated measurements and investigate the associations at the individual and population average levels. RESULTS: a total of 205 observations on 67 individuals were analysed. Lower levels of IGF-I, and lower levels of circulating IL-1RA, are significantly (P < 0.05) associated with delirium, while the remaining of cytokines, severity of illness and possession of epsilon 4 allele had a non-significant effect. This has been shown by both statistical methods. Similarly lower levels of IGF-I, and high levels of IFN-gamma, are statistically significantly (P < 0.05) associated with higher DRS scores (more severe delirium). CONCLUSIONS: this study finds that (i) low levels of both neuroprotective factors (IGF-I, IL-1RA) are associated with delirium, (ii) high IFN-gamma and low IGF-I have significant effects on delirium severity and (iii) otherwise the pro-inflammatory cytokines studied, APOE genotype and severity of illness do not appear to be associated, in older medically ill patients, with either delirium or severity of it.

Further analyses of the effects of practice, dropout, sex, socio-economic advantage, and recruitment cohort differences during the University of Manchester longitudinal study of cognitive change in old age.

A sample of 4,314 volunteers who, when first recruited, were aged from 41 to 93 years were quadrennially tested from 2 to 4 occasions during the next 4 to 20 years on the Cattell Culture Fair intelligence test, 2 tests of information-processing speed, the Wechsler Adult Intelligence Scale (WAIS) vocabulary test, and 3 memory tests. After significant effects of practice, sex, demographics, socio-economic advantage, and recruitment cohort had been identified and considered, performance on all tests declined with age. These age-related declines accelerated for the Cattell and WAIS, 2 tests of information speed, and 2 of the memory tests. For all tests individuals' trajectories of age-related change diverged with increasing age but, unexpectedly, were not affected by demographic factors. Practice gains from an initial experience of the cognitive tests remained undiminished as the interval before the second experience increased from 4 to 8 + years.

Death, dropout, and longitudinal measurements of cognitive change in old age.

During a 20-year longitudinal study of cognitive change in old age 2,342 of 5,842 participants died and 3,204 dropped out. To study cognitive change as death approaches, we grouped participants by survival, death, dropout, or dropout followed by death. Linear mixed-effects pattern-mixture models compared rates of cognitive change before death and dropout from four quadrennial administrations of tests of fluid intelligence, vocabulary, and verbal learning. After we took into account the significant effects of age, gender, demographics, and recruitment cohorts, we found that approach to death and dropout caused strikingly similar reductions in mean test scores and amounts of practice gains between successive quadrennial testing sessions. Participants who neither dropped out nor died showed significant but slight cognitive declines. These analyses illustrate how neglect of dropout miscalculates effects of death, of worsening health, and of all other factors affecting rates of cognitive change.

Sudden declines in intelligence in old age predict death and dropout from longitudinal studies.

It is well known that approaching death accelerates cognitive decline. The converse issue, that is, the question of whether rapid declines in cognitive ability are risk factors for imminent death, has not been investigated. Every 4 years between 1983 and 2003, we gave 1,414 healthy community residents who were aged between 49 and 93 years the Heim AH4-1 test of fluid intelligence. A modified Andersen-Gill model evaluated AH4-1 scores at entry to the study and changes in scores between successive quadrennial test sessions as risk factors for death and dropout. Deaths, dropouts, age, gender, occupational categories, and recruitment cohorts were also taken into account. Participants with lower AH4-1 scores on entry were significantly more likely to die or to drop out. At all ages and levels of baseline intelligence, the risks of deaths and dropouts further increased if test scores fell by 10%, and again increased if they fell by 20% during 4-year intervals between successive assessments.

Age and ability affect practice gains in longitudinal studies of cognitive change.

During a 20-year longitudinal study, 5,842 participants aged 49 to 93 years significantly improved over two to four successive experiences of the Heim AH4-1 intelligence test (first published in 1970), even with between-test intervals of 4 years and longer. After we considered significant attrition by death and dropout and the effects of gender, socioeconomic advantage, and recruitment cohort, we found that participants with high intelligence test scores showed greater improvement than did those with lower intelligence test scores. Practice gains also reduced with age, even after we took into consideration the individual differences in intelligence test scores. This emphasizes the methodological point that neglect of individual differences in improvement during longitudinal studies underestimates age-related changes in younger and more able participants and the theoretical point that, like all experiences during everyday life, participation in longitudinal studies alters the ability of aging humans to cope with cognitive demands to different extents according to their baseline abilities.

Age-associated losses of brain volume predict longitudinal cognitive declines over 8 to 20 years.

Absolute differences in global brain volume predict differences in cognitive ability among healthy older adults. However, absolute differences confound lifelong differences in brain size with amounts of age-related shrinkage. Measurements of cerebrospinal fluid (CSF) volume were made to estimate age-related shrinkage in 93 healthy volunteers aged 63 to 86 years. Their current levels of brain shrinkage predicted their amounts of decline over the previous 8 to 20 years on repeated assessments during a longitudinal study on the Cattell "Culture Fair" Intelligence Test, on two tests of information processing speed, and marginally on the Wechsler Adult Intelligence Scale (D. Wechsler, 1981), but not on three memory tests. Loss of brain volume is an effective marker both for current cognitive status and for amounts and rates of previous age-related cognitive losses.

Neutral assembly of bacterial communities.

Two recent, independent advances in ecology have generated interest and controversy: the development of neutral community models (NCMs) and the extension of biogeographical relationships into the microbial world. Here these two advances are linked by predicting an observed microbial taxa-volume relationship using an NCM and provide the strongest evidence so far for neutral community assembly in any group of organisms, macro or micro. Previously, NCMs have only ever been fitted using species-abundance distributions of macroorganisms at a single site or at one scale and parameter values have been calibrated on a case-by-case basis. Because NCMs predict a malleable two-parameter taxa-abundance distribution, this is a weak test of neutral community assembly and, hence, of the predictive power of NCMs. Here the two parameters of an NCM are calibrated using the taxa-abundance distribution observed in a small waterborne bacterial community housed in a bark-lined tree-hole in a beech tree. Using these parameters, unchanged, the taxa-abundance distributions and taxa-volume relationship observed in 26 other beech tree communities whose sizes span three orders of magnitude could be predicted. In doing so, a simple quantitative ecological mechanism to explain observations in microbial ecology is simultaneously offered and the predictive power of NCMs is demonstrated.

White matter lesions account for all age-related declines in speed but not in intelligence.

MRI scans measured white matter lesion prevalence (WMLP) in 65 people ages 65-84 years who also took 17 cognitive tests: 3 tests of general fluid intelligence, 3 of vocabulary, 2 of episodic and 3 of working memory, 2 of processing speed, and 4 of frontal and executive function. Entry of age with WMLP into regression equations as predictors of test scores showed that inferences about the functional relationships between markers of brain aging and cognitive impairments are seriously misleading if they are based on simple correlations alone. A new finding that WMLP accounts for all of the age-related variance between individuals in tests of speed and executive ability but for none of the age-related variance in intelligence revises current hypotheses that gross brain changes affect general fluid intelligence and other mental abilities solely through their effects on information-processing speed.

Modeling taxa-abundance distributions in microbial communities using environmental sequence data.

We show that inferring the taxa-abundance distribution of a microbial community from small environmental samples alone is difficult. The difficulty stems from the disparity in scale between the number of genetic sequences that can be characterized and the number of individuals in communities that microbial ecologists aspire to describe. One solution is to calibrate and validate a mathematical model of microbial community assembly using the small samples and use the model to extrapolate to the taxa-abundance distribution for the population that is deemed to constitute a community. We demonstrate this approach by using a simple neutral community assembly model in which random immigrations, births, and deaths determine the relative abundance of taxa in a community. In doing so, we further develop a neutral theory to produce a taxa-abundance distribution for large communities that are typical of microbial communities. In addition, we highlight that the sampling uncertainties conspire to make the immigration rate calibrated on the basis of small samples very much higher than the true immigration rate. This scale dependence of model parameters is not unique to neutral theories; it is a generic problem in ecology that is particularly acute in microbial ecology. We argue that to overcome this, so that microbial ecologists can characterize large microbial communities from small samples, mathematical models that encapsulate sampling effects are required.

What is the extent of prokaryotic diversity?

The extent of microbial diversity is an intrinsically fascinating subject of profound practical importance. The term 'diversity' may allude to the number of taxa or species richness as well as their relative abundance. There is uncertainty about both, primarily because sample sizes are too small. Non-parametric diversity estimators make gross underestimates if used with small sample sizes on unevenly distributed communities. One can make richness estimates over many scales using small samples by assuming a species/taxa-abundance distribution. However, no one knows what the underlying taxa-abundance distributions are for bacterial communities. Latterly, diversity has been estimated by fitting data from gene clone libraries and extrapolating from this to taxa-abundance curves to estimate richness. However, since sample sizes are small, we cannot be sure that such samples are representative of the community from which they were drawn. It is however possible to formulate, and calibrate, models that predict the diversity of local communities and of samples drawn from that local community. The calibration of such models suggests that migration rates are small and decrease as the community gets larger. The preliminary predictions of the model are qualitatively consistent with the patterns seen in clone libraries in 'real life'. The validation of this model is also confounded by small sample sizes. However, if such models were properly validated, they could form invaluable tools for the prediction of microbial diversity and a basis for the systematic exploration of microbial diversity on the planet.

Taxa-area relationships for microbes: the unsampled and the unseen.

The recent observation of a power-law relationship, S proportional A(z), between number of taxa, S, and area, A, for microbial eukaryotes and bacteria suggests that this is one of the few generic relationships in ecology, applicable to plants, animals and microbes. However, the rate of increase in the number of species with area varies from approximately the fourth (z = 0.26) to as little as the 50th root (z = 0.0019) in microbes. This is an enormous range for which no quantitative explanation has been proffered. We show by sampling from synthetic populations that the disparity between sample and community sizes in microbial community surveys means z can be considerably underestimated and accrual of rare taxa with increasing area will not be detectable. Significant microbial taxa-area relationships will only be observed when changes in community structure within samples correlate with area. Thus, the very low z values observed recently cannot be used as the sole evidence in support of any particular community theory of community assembly. More generally, this suggests that our search for patterns and laws in the microbial world will be profoundly influenced and, potentially distorted by the sample sizes that are typical of microbial community surveys.

Quantifying the roles of immigration and chance in shaping prokaryote community structure.

Naturally occurring populations of bacteria and archaea are vital to life on the earth and are of enormous practical significance in medicine, engineering and agriculture. However, the rules governing the formation of such communities are still poorly understood, and there is a need for a usable mathematical description of this process. Typically, microbial community structure is thought to be shaped mainly by deterministic factors such as competition and niche differentiation. Here we show, for a wide range of prokaryotic communities, that the relative abundance and frequency with which different taxa are observed in samples can be explained by a neutral community model (NCM). The NCM, which is a stochastic, birth-death immigration process, does not explicitly represent the deterministic factors and therefore cannot be a complete or literal description of community assembly. However, its success suggests that chance and immigration are important forces in shaping the patterns seen in prokaryotic communities.

Neglect of dropout underestimates effects of death in longitudinal studies.

Investigations of terminal declines in mental abilities have assessed cognitive performance at a single time point and retrospectively compared survivors and decedents at a single later census date. Neglect of outcomes other than death, such as dropout, causes a loss of information on the relative frailty of survivors and deceased persons before the census date and on incidence of mortality and frailty among survivors after the census date. This discards information on differences in health status between younger and older survivors. The Heim AH4-1 intelligence test was given to 4,228 people between the ages of 42 and 92 years, and both deaths and dropouts were logged during three successive census periods during the subsequent 11 years. Within and across census periods, effects of impending death and dropout did not differ, decreasing with time from initial assessment. Thus the effects of terminal decline, or indeed of any other variable affecting cognitive performance, are miscalculated if dropout is ignored.

Estimating bacterial diversity from clone libraries with flat rank abundance distributions.

There are a number of parametric and non-parametric methods for estimating diversity. However all such methods employ either the proportional abundance of the most abundant taxon in a sample or require that a specific taxon is sampled more than once. Consequently, the available methods for estimating diversity cannot be applied to samples consisting entirely of singletons, which might be characteristic of some hyperdiverse communities. Here we present a non-parametric method that estimates the probability that a given number of unique taxa would be sampled from a community with a particular diversity. We have applied this approach to a well known data set of 100 unique clones from a sample of Amazonian soil (Borneman and Triplett (1997) Appl Environ Microbiol 63: 2647-2653) and determine the probability that this observation would be made from an environment of a given diversity. On this basis we can state this observation would be very unlikely (P = 0.006) if the soil diversity was less than 10(3), and quite unlikely (P = 0.6) if the diversity was less than 10(4), and probable (P = 0.95) if the diversity was about 10(5). There are essentially no contestable assumptions in our method. Thus we are able to offer almost unequivocal evidence that the bacterial diversity, of at least soils, is very large and a method that may be used to interpret samples consisting entirely of singletons from other hyperdiverse communities.