Impact of date stamping on patient safety measurement in patients undergoing CABG: Experience with the AHRQ Patient Safety Indicators

<p>Abstract</p> <p>Background</p> <p>The Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) provide information on hospital risk-adjusted rates for potentially preventable adverse events. Although designed to work with routine administrative data, it is unknown whether the PSIs can accurately distinguish between complications and pre-existing conditions. The objective of this study is to examine whether the AHRQ PSIs accurately measure hospital complication rates, using the data with present-on-admission (POA) codes to distinguish between complications and pre-existing conditions</p> <p>Methods</p> <p>Retrospective cohort study of patients undergoing isolated CABG surgery in California conducted using the 1998–2000 California State Inpatient Database. We calculated the positive predictive value of selected AHRQ PSIs using information from the POA as the gold standard, and the intra-class correlation coefficient to assess the level of agreement between the hospital risk-adjusted PSI rates with and without the information contained in the POA modifier.</p> <p>Results</p> <p>The false positive error rate, defined as one minus the positive predictive value, was greater than or equal to 20% for four of the eight PSIs examined: decubitus ulcer, failure-to-rescue, postoperative physiologic and metabolic derangement, and postoperative pulmonary embolism or deep venous thrombosis. Pairwise comparison of the hospital risk-adjusted PSI rates, with and without POA information, demonstrated almost perfect agreement for five of the eight PSI's. For decubitus ulcer, failure-to-rescue, and postoperative pulmonary embolism or DVT, the intraclass-correlation coefficient ranged between 0.63 to 0.79.</p> <p>Conclusion</p> <p>For some of the AHRQ Patient Safety Indicators, there are significant differences in the risk-adjusted rates of adverse events depending on whether the POA indicator is used to distinguish between pre-existing conditions and complications. The use of the POA indicator will increase the accuracy of the AHRQ PSIs as measures of adverse outcomes.</p

Coexistence of opposite opinions in a network with communities

The Majority Rule is applied to a topology that consists of two coupled random networks, thereby mimicking the modular structure observed in social networks. We calculate analytically the asymptotic behaviour of the model and derive a phase diagram that depends on the frequency of random opinion flips and on the inter-connectivity between the two communities. It is shown that three regimes may take place: a disordered regime, where no collective phenomena takes place; a symmetric regime, where the nodes in both communities reach the same average opinion; an asymmetric regime, where the nodes in each community reach an opposite average opinion. The transition from the asymmetric regime to the symmetric regime is shown to be discontinuous.Comment: 14 pages, 4 figure

Error probability performance of a short-reach multicore fiber optical interconnect transmission system

A standalone module for rectangular array multicore fiber (MCF)-based optical interconnect (OI) is realized that includes inherent intercore crosstalk and provides space division multiplexed coupling/decoupling of optical power. The module is integrated in a short-reach communication system to provide bit error probability (BEP). Next, a closed-form equation for BEP applicable to MCF OI with intercore crosstalk is derived. For characteristic parameters of the module, results obtained by two approaches agree within 1% for 40 Gbps per channel and predict an error-free transmission of aggregated data rate of 2.5 Tbps through the MCF OI under consideration

Coherent Moving States in Highway Traffic (Originally: Moving Like a Solid Block)

Recent advances in multiagent simulations have made possible the study of realistic traffic patterns and allow to test theories based on driver behaviour. Such simulations also display various empirical features of traffic flows, and are used to design traffic controls that maximise the throughput of vehicles in heavily transited highways. In addition to its intrinsic economic value, vehicular traffic is of interest because it may throw light on some social phenomena where diverse individuals competitively try to maximise their own utilities under certain constraints. In this paper, we present simulation results that point to the existence of cooperative, coherent states arising from competitive interactions that lead to a new phenomenon in heterogeneous highway traffic. As the density of vehicles increases, their interactions cause a transition into a highly correlated state in which all vehicles practically move with the same speed, analogous to the motion of a solid block. This state is associated with a reduced lane changing rate and a safe, high and stable flow. It disappears as the vehicle density exceeds a critical value. The effect is observed in recent evaluations of Dutch traffic data.Comment: Submitted on April 21, 1998. For related work see http://www.theo2.physik.uni-stuttgart.de/helbing.html and http://www.parc.xerox.com/dynamics

Perspectives of primary health care staff on the implementation of a sexual health quality improvement program: A qualitative study in remote aboriginal communities in Australia

Background: Young people living in remote Australian Aboriginal communities experience high rates of sexually transmissible infections (STIs). STRIVE (STIs in Remote communities, ImproVed and Enhanced primary care) was a cluster randomised control trial of a sexual health continuous quality improvement (CQI) program. As part of the trial, qualitative research was conducted to explore staff perceptions of the CQI components, their normalisation and integration into routine practice, and the factors which influenced these processes. Methods: In-depth semi-structured interviews were conducted with 41 clinical staff at 22 remote community clinics during 2011-2013. Normalisation process theory was used to frame the analysis of interview data and to provide insights into enablers and barriers to the integration and normalisation of the CQI program and its six specific components. Results: Of the CQI components, participants reported that the clinical data reports had the highest degree of integration and normalisation. Action plan setting, the Systems Assessment Tool, and the STRIVE coordinator role, were perceived as adding value to the program, but were less readily integrated or normalised. The remaining two components (dedicated funding for health promotion and service incentive payments) were seen as least relevant. Our analysis also highlighted factors which enabled greater integration of the CQI components. These included familiarity with CQI tools, increased accountability of health centre staff and the translation of the CQI program into guideline-driven care. The analysis also identified barriers, including high staff turnover, limited time involved in the program and competing clinical demands and programs. Conclusions: Across all of the CQI components, the clinical data reports had the highest degree of integration and normalisation. The action plans, systems assessment tool and the STRIVE coordinator role all complemented the data reports and allowed these components to be translated directly into clinical activity. To ensure their uptake, CQI programs must acknowledge local clinical guidelines, be compatible with translation into clinical activity and have managerial support. Sexual health CQI needs to align with other CQI activities, engage staff and promote accountability through the provision of clinic specific data and regular face-to-face meetings. Trial registration: Australian and New Zealand Clinical Trials Registry ACTRN12610000358044. Registered 6/05/2010. Prospectively Registered

The association between nurse staffing and hospital outcomes in injured patients

The enormous fiscal pressures facing trauma centers may lead trauma centers to reduce nurse staffing and to make increased use of less expensive and less skilled personnel. The impact of nurse staffing and skill mix on trauma outcomes has not been previously reported. The goal of this study was to examine whether nurse staffing levels and nursing skill mix are associated with trauma patient outcomes. We used data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample to perform a cross-sectional study of 70,142 patients admitted to 77 Level I and Level II centers. Logistic regression models were used to examine the association between nurse staffing measures and (1) mortality, (2) healthcare associated infections (HAI), and (3) failure-to-rescue. We controlled for patient risk factors (age, gender, injury severity, mechanism of injury, comorbidities) and hospital structural characteristics (trauma center status - Level I versus Level II, hospital size, ownership, teaching status, technology level, and geographic region). A 1% increase in the ratio of licensed practical nurse (LPN) to total nursing time was associated with a 4% increase in the odds of mortality (adj OR 1.04; 95% CI: 1.02-1.06; p = 0.001) and a 6% increase in the odds of sepsis (adj OR 1.06: 1.03-1.10; p < 0.001). Hospitals in the highest quartile of LPN staffing had 3 excess deaths (95% CI: 1.2, 5.1) and 5 more episodes of sepsis (95% CI: 2.3, 7.6) per 1000 patients compared to hospitals in the lower quartile of LPN staffing. Higher hospital LPN staffing levels are independently associated with slightly higher rates of mortality and sepsis in trauma patients admitted to Level I or Level II trauma centers

Optimal Self-Organization

We present computational and analytical results indicating that systems of driven entities with repulsive interactions tend to reach an optimal state associated with minimal interaction and minimal dissipation. Using concepts from non-equilibrium thermodynamics and game theoretical ideas, we generalize this finding to an even wider class of self-organizing systems which have the ability to reach a state of maximal overall ``success''. This principle is expected to be relevant for driven systems in physics like sheared granular media, but it is also applicable to biological, social, and economic systems, for which only a limited number of quantitative principles are available yet.Comment: This is the detailled revised version of a preprint on ``Self-Organised Optimality'' (cond-mat/9903319). For related work see http://www.theo2.physik.uni-stuttgart.de/helbing.html and http://angel.elte.hu/~vicsek

Traffic Instabilities in Self-Organized Pedestrian Crowds

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.Comment: Article published in PLoS Computational biology. Freely available here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100244

Case-mix and the use of control charts in monitoring mortality rates after coronary artery bypass

BACKGROUND: There is debate about the role of crude mortality rates and case-mix adjusted mortality rates in monitoring the outcomes of treatment. In the context of quality improvement a key purpose of monitoring is to identify special cause variation as this type of variation should be investigated to identify possible causes. This paper investigates agreement between the identification of special cause variation in risk adjusted and observed hospital specific mortality rates after coronary artery bypass grafting in New York hospitals. METHODS: Coronary artery bypass grafting mortality rates between 1994 and 2003 were obtained from the New York State Department of Health's cardiovascular reports for 41 hospitals. Cross-sectional control charts of crude (observed) and risk adjusted mortality rates were produced for each year. Special cause variation was defined as a data point beyond the 99.9% probability limits: hospitals showing special cause variation were identified for each year. Longitudinal control charts of crude (observed) and risk adjusted mortality rates were produced for each hospital with data for all ten years (n = 27). Special cause variation was defined as a data point beyond 99.9% probability limits, two out of three consecutive data points beyond 95% probability limits (two standard deviations from the mean) or a run of five consecutive points on one side of the mean. Years showing special cause variation in mortality were identified for each hospital. Cohen's Kappa was calculated for agreement between special causes identified in crude and risk-adjusted control charts. RESULTS: In cross sectional analysis the Cohen's Kappa was 0.54 (95% confidence interval: 0.28 to 0.78), indicating moderate agreement between the crude and risk-adjusted control charts with sensitivity 0.4 (95% confidence interval 0.17–0.69) and specificity 0.98 (95% confidence interval: 0.95–0.99). In longitudinal analysis, the Cohen's Kappa was 0.61 (95% confidence interval: 0.39 to 0.83) indicating good agreement between the tests with sensitivity 0.63 (95% confidence interval: 0.39–0.82) and specificity 0.98 (95% confidence interval: 0.96 to 0.99). CONCLUSION: There is moderate-good agreement between signals of special cause variation between observed and risk-adjusted mortality. Analysis of observed hospital specific CABG mortality over time and with other hospitals appears to be useful in identifying special causes of variation. Case-mix adjustment may not be essential for longitudinal monitoring of outcomes using control charts

Modeling and verifying a broad array of network properties

Motivated by widely observed examples in nature, society and software, where groups of already related nodes arrive together and attach to an existing network, we consider network growth via sequential attachment of linked node groups, or graphlets. We analyze the simplest case, attachment of the three node V-graphlet, where, with probability alpha, we attach a peripheral node of the graphlet, and with probability (1-alpha), we attach the central node. Our analytical results and simulations show that tuning alpha produces a wide range in degree distribution and degree assortativity, achieving assortativity values that capture a diverse set of many real-world systems. We introduce a fifteen-dimensional attribute vector derived from seven well-known network properties, which enables comprehensive comparison between any two networks. Principal Component Analysis (PCA) of this attribute vector space shows a significantly larger coverage potential of real-world network properties by a simple extension of the above model when compared against a classic model of network growth.Comment: To appear in Europhysics Letter