Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model

<p>Abstract</p> <p>Background</p> <p>Near-road exposures of traffic-related air pollutants have been receiving increased attention due to evidence linking emissions from high-traffic roadways to adverse health outcomes. To date, most epidemiological and risk analyses have utilized simple but crude exposure indicators, most typically proximity measures, such as the distance between freeways and residences, to represent air quality impacts from traffic. This paper derives and analyzes a simplified microscale simulation model designed to predict short- (hourly) to long-term (annual average) pollutant concentrations near roads. Sensitivity analyses and case studies are used to highlight issues in predicting near-road exposures.</p> <p>Methods</p> <p>Process-based simulation models using a computationally efficient reduced-form response surface structure and a minimum number of inputs integrate the major determinants of air pollution exposures: traffic volume and vehicle emissions, meteorology, and receptor location. We identify the most influential variables and then derive a set of multiplicative submodels that match predictions from "parent" models MOBILE6.2 and CALINE4. The assembled model is applied to two case studies in the Detroit, Michigan area. The first predicts carbon monoxide (CO) concentrations at a monitoring site near a freeway. The second predicts CO and PM_2.5concentrations in a dense receptor grid over a 1 km²area around the intersection of two major roads. We analyze the spatial and temporal patterns of pollutant concentration predictions.</p> <p>Results</p> <p>Predicted CO concentrations showed reasonable agreement with annual average and 24-hour measurements, e.g., 59% of the 24-hr predictions were within a factor of two of observations in the warmer months when CO emissions are more consistent. The highest concentrations of both CO and PM_2.5were predicted to occur near intersections and downwind of major roads during periods of unfavorable meteorology (e.g., low wind speeds) and high emissions (e.g., weekday rush hour). The spatial and temporal variation among predicted concentrations was significant, and resulted in unusual distributional and correlation characteristics, including strong negative correlation for receptors on opposite sides of a road and the highest short-term concentrations on the "upwind" side of the road.</p> <p>Conclusions</p> <p>The case study findings can likely be generalized to many other locations, and they have important implications for epidemiological and other studies. The reduced-form model is intended for exposure assessment, risk assessment, epidemiological, geographical information systems, and other applications.</p

Visual process maps to support implementation efforts: a case example

Abstract Background Process mapping is often used in quality improvement work to examine current processes and workflow and to identify areas to intervene to improve quality. Our objective in this paper is to describe process maps as a visual means of understanding modifiable behaviors and activities, in this case example to ensure that goals of care conversations are part of admitting a veteran in long-term care settings. Methods We completed site visits to 6 VA nursing homes and reviewed their current admission processes. We conducted interviews to document behaviors and activities that occur when a veteran is referred to a long-term care setting, during admission, and during mandatory VA reassessments. We created visualizations of the data using process mapping approaches. Process maps for each site were created to document the admission activities for each VA nursing home and were reviewed by the research team to identify consistencies across sites and to identify potential opportunities for implementing goals of care conversations. Results We identified five consistent behaviors that take place when a veteran is referred and admitted in long-term care. These behaviors are assessing, discussing, decision-making, documenting, and re-assessing. Conclusions Based on the process maps, it seems feasible that the LST note and order template could be completed along with other routine assessment processes. However, this will require more robust multi-disciplinary collaboration among both prescribing and non-prescribing health care providers. Completing the LST template during the current admission process would increase the likelihood that the template is completed in a timely manner, potentially alleviate the perceived time burden, and help with the provision of veteran-centered care.http://deepblue.lib.umich.edu/bitstream/2027.42/174078/1/43058_2020_Article_94.pd

Designing clinical practice feedback reports: three steps illustrated in Veterans Health Affairs long-term care facilities and programs

Abstract Background User-centered design (UCD) methods are well-established techniques for creating useful artifacts, but few studies illustrate their application to clinical feedback reports. When used as an implementation strategy, the content of feedback reports depends on a foundational audit process involving performance measures and data, but these important relationships have not been adequately described. Better guidance on UCD methods for designing feedback reports is needed. Our objective is to describe the feedback report design method for refining the content of prototype reports. Methods We propose a three-step feedback report design method (refinement of measures, data, and display). The three steps follow dependencies such that refinement of measures can require changes to data, which in turn may require changes to the display. We believe this method can be used effectively with a broad range of UCD techniques. Results We illustrate the three-step method as used in implementation of goals of care conversations in long-term care settings in the U.S. Veterans Health Administration. Using iterative usability testing, feedback report content evolved over cycles of the three steps. Following the steps in the proposed method through 12 iterations with 13 participants, we improved the usability of the feedback reports. Conclusions UCD methods can improve feedback report content through an iterative process. When designing feedback reports, refining measures, data, and display may enable report designers to improve the user centeredness of feedback reports.http://deepblue.lib.umich.edu/bitstream/2027.42/173835/1/13012_2019_Article_950.pd

Evaluating implementation strategies to support documentation of veterans’ care preferences

ObjectiveTo evaluate the effectiveness of feedback reports and feedback reports + external facilitation on completion of life-sustaining treatment (LST) note the template and durable medical orders. This quality improvement program supported the national roll-out of the Veterans Health Administration (VA) LST Decisions Initiative (LSTDI), which aims to ensure that seriously-ill veterans have care goals and LST decisions elicited and documented.Data SourcesPrimary data from national databases for VA nursing homes (called Community Living Centers [CLCs]) from 2018 to 2020.Study DesignIn one project, we distributed monthly feedback reports summarizing LST template completion rates to 12 sites as the sole implementation strategy. In the second involving five sites, we distributed similar feedback reports and provided robust external facilitation, which included coaching, education, and learning collaboratives. For each project, principal component analyses matched intervention to comparison sites, and interrupted time series/segmented regression analyses evaluated the differences in LSTDI template completion rates between intervention and comparison sites.Data Collection MethodsData were extracted from national databases in addition to interviews and surveys in a mixed-methods process evaluation.Principal FindingsLSTDI template completion rose from 0% to about 80% throughout the study period in both projects’ intervention and comparison CLCs. There were small but statistically significant differences for feedback reports alone (comparison sites performed better, coefficient estimate 3.48, standard error 0.99 for the difference between groups in change in trend) and feedback reports + external facilitation (intervention sites performed better, coefficient estimate −2.38, standard error 0.72).ConclusionsFeedback reports + external facilitation was associated with a small but statistically significant improvement in outcomes compared with comparison sites. The large increases in completion rates are likely due to the well-planned national roll-out of the LSTDI. This finding suggests that when dissemination and support for widespread implementation are present and system-mandated, significant enhancements in the adoption of evidence-based practices may require more intensive support.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/173095/1/hesr13958_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/173095/2/hesr13958.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/173095/3/hesr13958-sup-0001-Supinfo1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/173095/4/hesr13958-sup-0002-Supinfo2.pd