Study protocol for evaluating the implementation and effectiveness of an emergency department longitudinal patient monitoring system using a mixed-methods approach

Background: Early detection of patient deterioration is a key element of patient safety as it allows timely clinical intervention and potential rescue, thus reducing the risks of serious patient safety incidents. Longitudinal patient monitoring systems have been widely recommended for use to detect clinical deterioration. However, there is conflicting evidence on whether they improve patient outcomes. This may in part be related to variation in the rigour with which they are implemented and evaluated. This study aims to evaluate the implementation and effectiveness of a longitudinal patient monitoring system designed for adult patients in the unique environment of the Emergency Department (ED). Methods: A novel participatory action research (PAR) approach is taken where socio-technical systems (STS) theory and analysis informs the implementation through the improvement methodology of ‘Plan Do Study Act’ (PDSA) cycles. We hypothesise that conducting an STS analysis of the ED before beginning the PDSA cycles will provide for a much richer understanding of the current situation and possible challenges to implementing the ED-specific longitudinal patient monitoring system. This methodology will enable both a process and an outcome evaluation of implementing the ED-specific longitudinal patient monitoring system. Process evaluations can help distinguish between interventions that have inherent faults and those that are badly executed. Discussion: Over 1.2 million patients attend EDs annually in Ireland; the successful implementation of an ED-specific longitudinal patient monitoring system has the potential to affect the care of a significant number of such patients. To the best of our knowledge, this is the first study combining PAR, STS and multiple PDSA cycles to evaluate the implementation of an ED-specific longitudinal patient monitoring system and to determine (through process and outcome evaluation) whether this system can significantly improve patient outcomes by early detection and appropriate intervention for patients at risk of clinical deterioration

A matched-pair cluster design study protocol to evaluate implementation of the Canadian C-spine rule in hospital emergency departments: Phase III

BACKGROUND: Physicians in Canadian emergency departments (EDs) annually treat 185,000 alert and stable trauma victims who are at risk for cervical spine (C-spine) injury. However, only 0.9% of these patients have suffered a cervical spine fracture. Current use of radiography is not efficient. The Canadian C-Spine Rule is designed to allow physicians to be more selective and accurate in ordering C-spine radiography, and to rapidly clear the C-spine without the need for radiography in many patients. The goal of this phase III study is to evaluate the effectiveness of an active strategy to implement the Canadian C-Spine Rule into physician practice. Specific objectives are to: 1) determine clinical impact, 2) determine sustainability, 3) evaluate performance, and 4) conduct an economic evaluation. METHODS: We propose a matched-pair cluster design study that compares outcomes during three consecutive 12-months "before," "after," and "decay" periods at six pairs of "intervention" and "control" sites. These 12 hospital ED sites will be stratified as "teaching" or "community" hospitals, matched according to baseline C-spine radiography ordering rates, and then allocated within each pair to either intervention or control groups. During the "after" period at the intervention sites, simple and inexpensive strategies will be employed to actively implement the Canadian C-Spine Rule. The following outcomes will be assessed: 1) measures of clinical impact, 2) performance of the Canadian C-Spine Rule, and 3) economic measures. During the 12-month "decay" period, implementation strategies will continue, allowing us to evaluate the sustainability of the effect. We estimate a sample size of 4,800 patients in each period in order to have adequate power to evaluate the main outcomes. DISCUSSION: Phase I successfully derived the Canadian C-Spine Rule and phase II confirmed the accuracy and safety of the rule, hence, the potential for physicians to improve care. What remains unknown is the actual change in clinical behaviors that can be affected by implementation of the Canadian C-Spine Rule, and whether implementation can be achieved with simple and inexpensive measures. We believe that the Canadian C-Spine Rule has the potential to significantly reduce health care costs and improve the efficiency of patient flow in busy Canadian EDs

Linkage of whole genome sequencing with administrative health, and electronic medical record data for the study of autism spectrum disorder: Feasibility, Opportunities and Challenges

Introduction Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) that presents with a high degree of heterogeneity (e.g., co-occurrence of other NDDs and other co-morbid conditions), contributing to differential health system needs. Genetics are known to play an important role in ASD and may be associated with different disease trajectories. Objectives and Approach In this proof of principle project, our objective is to link >2,200 children with a confirmed diagnosis of a NDD from the Province of Ontario Neurodevelopmental (POND) Study to administrative health data and electronic medical record (EMR) data in order to identify subgroups of ASD with unique health system trajectories. POND includes detailed phenotype and whole genome sequencing (WGS) data. Identified subgroups will be characterized based on clinical phenotype and genetics. To meet this goal, consideration of WGS-specific privacy and data issues is needed to implement processes which are above and beyond traditional requirements for analyzing individual-level administrative health data. Results Linkage of WGS data with administrative health data is an emerging area of research. As such it has presented a number of initial challenges for our study of ASD. Privacy concerns surrounding the use of WGS data and rare-variant analysis are of particular importance. Practical issues required the need for analysts with expertise in administrative data, EMR data and genetic analyses, and specialized software and sufficient processing power to analyze WGS data. Transdisciplinary discussions of the scope and significance of research questions addressed through this linkage were crucial. The identification of genetic determinants of phenotypes and trajectories in ASD could support targeted early interventions; EMR linkage may inform algorithms to identify ASD in broader populations. These approaches could improve both patient outcome and family experience. Conclusion/Implications As the cost of genetic sequencing decreases, WGS data will become part of the routine clinical management of patients. Linkage of WGS, EMR and administrative data has tremendous potential that has largely not been realized; including population-level ASD research to improve our ability to predict long-term outcomes associated with ASD

OpenET : filling a critical data gap in water management for the western United States.

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET

Major Radiodiagnostic Imaging in Pregnancy and the Risk of Childhood Malignancy: A Population-Based Cohort Study in Ontario

In a record-linkage study, Joel Ray and colleagues examine the association between diagnostic imaging during pregnancy and later childhood cancers

Development and validation of a data dictionary for a feasibility analysis of emergency department key performance indicators

Objectives: The primary study objective was to describe the development of a data dictionary for a feasibility analysis of 11 emergency department (ED) key performance indicators (KPIs). The secondary objective was to internally validate the data dictionary by measuring the inter-observer agreement between data abstractors at participating study sites. Methods: A list of data variables based on the minimum data set elements relevant to the KPIs was developed by a panel of emergency medicine (EM) specialists and from the EM literature. A summit involving the relevant stakeholders, including ED frontline staff, a health economist, an ED clinical data manager and a health care informatician, was convened. For the feasibility analysis project, each data abstractor was furnished with a copy of the data dictionary and attended a one-hour training session prior to commencing data abstraction. Data was independently abstracted for each KPI by two abstractors at each of 12 participating EDs. Inter-rater agreement between abstractors was calculated using Cohen's kappa and results were reported using the Landis and Koch criteria. Results: A data dictionary was developed by creating clear definitions and establishing abstraction instructions for each variable. A total of 43 data variables were included in the study data dictionary: 4 on patient demographics; 19 time variables; 5 outcome variables; 8 ED service and staffing units and 7 medical definitions. A clear definition and a set of data abstraction instructions including data sources were developed for each variable to aid data abstraction during the feasibility analysis. Overall 9,276 ED patient records were used for data abstraction to internally validate the data dictionary. The median Cohen kappa score ranged between 0.56 to 0.81. Conclusion: There is a continued need to standardize definitions of KPIs for the purpose of comparing ED performance and for research purposes. This is a necessary first step in the implementation of valid and reliable ED performance measures. This study successfully developed an internally valid data dictionary that can be used for day-to-day ED operations and for research purposes

Improved outcomes with early collaborative care of ambulatory heart failure patients discharged from the emergency department

Background: The type of outpatient physician care after an emergency department visit for heart failure may affect patients' outcomes. Methods and Results: Using the National Ambulatory Care Reporting System, we examined the care and outcomes of heart failure patients who visited and were discharged from the emergency department in Ontario, Canada (April 2004 to March 2007). Early collaborative care by a cardiologist and primary care (PC) physician within 30 days after discharge was compared with PC alone. Care for 10 599 patients (age, 74.9±11.9 years; 50.2% male) was provided by PC alone (n=6596), cardiologist alone (n=535), or concurrently by both cardiologist and PC (n=1478); 1990 did not visit a physician. Collaborative care patients were more likely to undergo assessment of left ventricular function (57.4% versus 28.7%), noninvasive stress testing (20.1% versus 7.8%), and cardiac catheterization (11.6% versus 2.7%) compared with PC. Drug prescriptions (patients ≥65 years of age) demonstrated higher use of angiotensin-converting enzyme inhibitors (58.8% versus 54.6%), angiotensin receptor blockers (22.7% versus 18.1%), β-adrenoceptor antagonists (63.4% versus 48.0%), loop diuretics (84.2% versus 79.6%), metolazone (4.8% versus 3.4%), and spironolactone (19.8% versus 12.7%) within 100 days after emergency department discharge for collaborative care compared with PC. In a propensity-matched model, mortality was lower with PC compared with no physician visit (hazard ratio, 0.75; 95% confidence interval, 0.64 to 0.87; P<0.001). Collaborative care reduced mortality compared with PC (hazard ratio, 0.79; 95% confidence interval, 0.63 to 1.00; P=0.045). Sole cardiology care conferred a trend to increased mortality (hazard ratio, 1.41 versus collaborative care; 95% confidence interval, 0.98 to 2.03; P=0.067). Conclusions: Early collaborative heart failure care was associated with increased use of drug therapies and cardiovascular diagnostic tests and better outcomes compared with PC alone

Analysis of the MISR LAI/FPAR product for spatial and temporal coverage, accuracy and consistency

The Multi-angle Imaging SpectroRadiometer (MISR) instrument provides global imagery at nine discrete viewing angles and four visible/nearinfrared spectral bands. MISR standard products include green leaf area index (LAI) of vegetation and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). This paper describes the research basis for transitioning the MISR LAI/FPAR products from provisional to validation status. The efforts included not only comparisons to field data but also analyses of relationships, consistency and complementarity between various MISR products derived by independent algorithms. For example, we show how the energy absorbed by the ground below vegetation can be estimated from two independent MISR products, FPAR and BHRPAR (bi-hemispheric reflectance at PAR wavelengths). Further, we show that this information can be used to derive at least three measures of canopy structure — Beer&apos;s law extinction coefficient, mean leaf inclination and the gap fraction or vegetation ground cover. The spatial and temporal coverage of the LAI/FPAR product is mainly limited by cloud contamination. However, when a successful aerosol retrieval is performed, typically 95 % of pixels have surface reflectance retrievals suitable as input to the LAI/FPAR algorithm. The algorithm provides LAI/FPAR retrievals in 50–80 % of these pixels with suitable input. The early versions of the algorithm overestimated LAI values in grasses and broadleaf crops. The MISR LAI product from the recalibrated algorithm (version 3.3) is assessed by comparison with field data collected in a 3×3 km agricultural area (grasses and cereal crops) near Avignon, France. LAI retrievals in other biomes are compared to MODIS LAI product of known accuracy. The MISR LAI product shows structural and phenological variability in agreement with data. Our results suggest that the product is accurate to within 0.66 LAI in herbaceous vegetation an