Planning Efforts Research Articles

Interactive Effects of Built Environment and Parking Policy on Car Use: Examining Differences Between Work and Non-Work Trips

Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence.

Evergreen Migration for North Carolina Community College Libraries

The migration of North Carolina Community College Libraries to the Evergreen platform is the culmination of planning, training, and implementation efforts of librarians throughout the state over the last four and a half years. This article provides a brief overview of the process and outlines benefits for the 50 participating institutions, before concluding with suggestions for other libraries that are considering a similar migration.

Urban Open Space Utilization for Subsistence Agriculture: A Study of Esikhaleni Township

This research investigates the motivations driving the utilization of urban open spaces for subsistence agriculture and assesses its impact on the livelihoods of residents in Esikhaleni Township. Employing a mixed-methods approach, the study conducts structured interviews with local farmers and in-depth interviews with municipal officials from the uMhlathuze Municipality. The findings highlight food insecurity, the necessity for accessible fresh produce, agricultural passion, and rising food costs as primary drivers compelling Esikhaleni residents towards open space farming. Moreover, the research underscores the significant contribution of open space agriculture to the livelihoods of Esikhaleni residents, including improved access to fresh food, reduced food expenditures, and supplementary income generation through produce sales. The study concludes by recommending the integration of urban agriculture into urban planning efforts to safeguard land for agricultural purposes, thereby enabling residents of Esikhaleni Township to engage in sustainable agricultural practices.

Stronger increase of methane emissions from coastal wetlands by non‐native Spartina alterniflora than non‐native Phragmites australis

Societal Impact StatementThe invasive species S. alterniflora and P. australis are fast growing coastal wetland plants sequestering large amounts of carbon in the soil and protect coastlines against erosion and storm surges. In this global analysis, we found that Spartina and Phragmites increase methane but not nitrous oxide emissions, with Phragmites having a lesser effect. The impact of the invasive species on emissions differed greatly among different types of native plant groups, providing valuable information to managers and policymakers during coastal wetland planning and restoration efforts. Further, our estimated net emissions per wetland plant group facilitate regional and national blue carbon estimates.Summary Globally, Spartina alterniflora and Phragmites australis are among the most pervasive invasive plants in coastal wetland ecosystems. Both species sequester large amounts of atmospheric carbon dioxide (CO2) and biogenic carbon in soils but also support production and emission of methane (CH4). In this study, we investigated the magnitude of their net greenhouse gas (GHG) release from invaded and non‐invaded habitats. We conducted a meta‐analysis of GHG fluxes associated with these two species and related soil carbon content and plant biomass in invaded coastal wetlands. Our results show that both invasive species increase CH4 fluxes compared to uninvaded coastal wetlands, but they do not significantly affect CO2 and N2O fluxes. The magnitude of emissions from Spartina and Phragmites differs among native habitats. GHG fluxes, soil carbon and plant biomass of Spartina‐invaded habitats were highest compared to uninvaded mudflats and succulent forb‐dominated wetlands, while being lower compared to uninvaded mangroves (except for CH4). This meta‐analysis highlights the important role of individual plant traits as drivers of change by invasive species on plant‐mediated carbon cycles.

Disaster vulnerability in road networks: a data-driven approach through analyzing network topology and movement activity

The rise in natural disasters and climate-induced events, such as wildfires, hurricanes, and flooding, has significantly affected urban life. These events can disrupt daily activity and flows of individuals and goods on road and transit networks. To enhance urban resilience against disasters, it’s crucial to study and understand road network vulnerability, utilizing data-driven insights to inform planning and preparedness efforts. The aim of this paper is to develop a data-driven exploratory approach to assess vulnerability in road networks in response to a disruption. To accomplish this, we compare the centrality of road segments before, during, and after disaster, considering the network topological structure and movement activity as it is observed through large tracking data of cellphone traces on the network. The novelty of our approach lies in inferring the impact from movement data, instead of manually removing links from the network. The results obtained from this study suggest that incorporating movement data into the assessment of network functionality provides a more realistic estimation of the road network vulnerability in response to a disruption, compared to solely using network topology.

Model sensitivity in predicting extreme precipitation events in urban areas: A case study over Beijing

Understanding and forecasting the spatial and temporal distributions of extreme precipitation over urban areas is crucial for effective planning and mitigation efforts. However, this task remains challenging as accurate forecasting depends on properly representing urban surfacees and their interactions with the planetary boundary layer (PBL). We examined the hindcast of an extreme precipitation event over Beijing on 21–22 July 2012. The primary focus was assessing its sensitivity to two widely used PBL parameterizations (MYJ and YSU), two urban parameterizations (SLUCM and BEP_BEM), and two different land-use and land-cover (LULC) datasets.Sensitivity experiments were initialized at different times to explore the model dependence on initial conditions. The analyses were conducted over three selected regions: the entire model domain covering the Beijing metropolitan area, an upwind region of Beijing, and the entire urban area of Beijing. The results show that the MYJ PBL scheme performs better than the YSU PBL scheme in capturing near-surface air temperature as well as the location and timing of the heaviest precipitation. The variability in simulated precipitation among the chosen PBL schemes is lower compared to that among different time of initializations. The LULC impacted the spatial distribution of precipitation but its effect on the amount of precipitation was minimal. Overall, using a combination of the MYJ PBL scheme, SLUCM urban parameterization, and locally-enhanced Beijing LULC, and initializing the model simulations at 0000 UTC July 20, 2012, demonstrated superior performance in capturing precipitation levels, despite some spatial discrepancies in the precipitation distribution. The performance of BEP_BEM urban parameterization is similar to SLUCM across various factors such as average rain rate, maximum rain rate, and rain volume. These findings offer valuable insights towards better simulations of extreme precipitation and flooding in rapidly urbanizing areas such as Beijing.

Association between postoperative complications and hospital length of stay: a large-scale observational study of 4,495,582 patients in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) registry

BackgroundPrecise estimates of risk-adjusted increases in postoperative length of stay (LOS) associated with postoperative complications across a range of complications and operations are not available in the existing literature.MethodsAssociations between preoperative characteristics, postoperative complications and postoperative LOS were tested using medians, interquartile ranges, and nonparametric rank sum tests in a retrospective cohort study using the 2005–2018 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) dataset. A negative binomial model was used with postoperative LOS as the dependent variable and preoperative characteristics and postoperative complications as independent variables. The model was applied to estimate each patient’s postoperative LOS with and without each postoperative complication to measure the association between each complication and risk-adjusted change in postoperative LOS.ResultsA total of 4,495,582 patients were included. After risk-adjustment, occurrence of each postoperative complication was associated with significantly increased postoperative LOS (between + 3.9 and + 20.1 days, p < 0.0001). The longest risk-adjusted postoperative LOS increases were associated with prolonged ventilator use (+ 20.1 days), wound disruption (+ 19.4 days), and acute renal failure (+ 17.1 days).ConclusionOccurrence of any postoperative complication was associated with increased risk-adjusted postoperative LOS. Degree of increase varied by complication. These data could be useful for patient counseling, allocation of resources, discharge planning, and quality improvement efforts.

An Overview of Transdisciplinary and Bottom-up Approach for Urban Resilience: The Case of Turkey

While top-down strategies have traditionally dominated urban planning in Turkey, recent shifts towards participatory practices and project-based policies have aimed to involve citizens in decision-making processes. Nevertheless, in the case of Turkey, these participatory models are inadequate for effectively addressing resilience. This article therefore discusses the role of participatory processes in creating resilient cities, as well as how to strengthen transdisciplinary (TR) and bottom-up approaches to urban participation in Turkish urban contexts. The article presents a theoretical framework that connects TR and bottom-up approaches based on existing literature, practices, and planning policy examples. It argues that TR approaches complement bottom-up approaches to urban governance by enhancing urban and social resilience, strengthening local communities, and reducing urban inequalities. Urban planning efforts that promote collaboration, incorporate multiple perspectives, and involve local communities in decision-making processes can address complex urban issues while also fostering long-term sustainability and resilience. This approach not only instills a sense of ownership and empowerment among urban residents but also leverages knowledge and skills to generate more effective and sustainable solutions. By creating a framework that promotes long-term education and citizenship awareness, urban governance can sustain urban resilience in a more viable manner over the long term in Turkey.

Enhancing bird habitat networks in metropolitan areas: Resilience assessment and improvement strategies – A case study from Shanghai

Constructing bird habitat networks (BHNs) is crucial for maintaining the health and service equilibrium of urban ecosystems, especially in large metropolitan areas where the pressure of urbanization is intense. However, most existing BHNs fail to account for the dynamic changes and unique requirements of local species, leading to homogenized construction outcomes and ecological corridor objectives. This study employs a comprehensive approach to identify bird habitat patches using multiple high-quality sources, then utilize circuit theory and complex network theory to construct and assess the resilience of BHN. Our key findings showed: (1)93 bird habitat sources were identified, predominantly situated in the continuous green spaces of southern and southeastern Shanghai, whereas habitat sources in the city center and other densely built-up areas are more dispersed, highlighting them as prime targets for future ecological restoration efforts. (2) The distribution of bird habitat corridors exhibits significant spatial heterogeneity, with primary corridors predominantly spanning the southwestern and eastern parts of the study area, while secondary corridors are more abundant in the western and northern parts, forming a denser network, whereas the central area shows fewer and more isolated corridors. (3) The decline in structural and functional resilience was notably more rapid under targeted attacks than under random attacks, underscoring the need to prioritize crucial bird habitat sources on the city's periphery, especially near highly urbanized areas, in urban planning and biodiversity conservation efforts to sustain ecological balance and biodiversity. These insights provide a crucial scientific basis for urban planners, emphasizing the integration of biodiversity conservation into urban development strategies by optimizing ecological sources and corridors to balance development with ecological preservation.

Geomorphology and sediment mobility on sand banks: A study of Dogfish Bank, Hecate Strait, Northeast Pacific Ocean

AbstractMovement of sediment along shallow continental shelves is a natural process with wide‐ranging environmental and economic implications, making it of high importance to marine spatial planning efforts in the offshore. Development of marine renewable energy, for instance, requires detailed understanding of the morphodynamics of mobile bedforms to select foundation types and ensure safe installation of infrastructure in shallow shelf environments. This study evaluates geomorphology and sediment mobility of Dogfish Bank (&lt; 20 mbsl) in the Hecate Strait offshore British Columbia, Canada, using hydroacoustic and airborne bathymetric data combined with seismic profiles and grain‐size information. These data reveal current‐swept features ranging from sediment‐depleted lag to sediment‐abundant sand ridges and dunes, with sand ribbons and furrows in‐between. Seismic reflection data show up to 15 m of surficial sand concentrated beneath north‐aligned sand ridges that dominate the bathymetry of northwest Hecate Strait. Sand ribbons (typically understood sediment‐limited features in shallow marine environments) are notably maintained over seabed with comparable sand thickness to adjacent dunes (i.e. sediment‐abundant features), suggesting local spatial variability in hydrodynamics and sediment characteristics (principally grain size) influence expression of mobile bedforms. Repeat mapping between 2008 and 2019 shows dunes and ribbons both migrate northwards, with largest seafloor changes along northeast‐facing lee sides of dunes, matching closely with published models of sediment mobility which suggest northward bedform migration is largely driven by storms. Median total migration distance is 164 m (northward) for dunes (time‐averaged rate of 14.9 m/year). Sand ribbons show less migration (median northward distance of 73 m) and migrate in a depth‐dependent manner. Because sand ribbons are typically flow‐parallel features, their lateral migration likely results from varying current directions and flow acceleration over shallower seabed. Sand ribbon migration should therefore a consideration in studies examining seabed change, particularly when they are formed over unconsolidated sediment.

Enhancing Adaptive Capacity by Engaging and Empowering Frontline Workers: A Case Study From a Water Utility

AbstractWater utility crews, including those who perform system maintenance and operations at drinking water, wastewater, and stormwater utilities, are experiencing the impacts of changing rainfall characteristics first‐hand. These frontline crews have relevant, experiential knowledge about changing climate‐related risks and adaptation needs that, to date, are not included in utilities' strategic climate planning or implementation efforts, resulting in critical knowledge systems and action gaps. In this co‐production case study with Seattle Public Utilities (SPU), a municipal public water utility in Washington State, we use surveys and interviews to document barriers and opportunities for frontline crew engagement to enhance SPU's climate adaptation strategies to extreme rainfall. We find that 66% of crew workers perceive changes to rainfall intensity over the past decade and 59% report responding more to rainfall‐related issues. These frontline crews are coping with changes in extreme precipitation by increasing preventative maintenance, working overtime during major storm events, and doing more pre‐storm planning and preparation. Crews identified several aspects limiting their ability to respond to and prepare for extreme rainfall. To enhance their adaptive capacity, crews documented needs for infrastructure improvement, workforce facilities improvement, increased access to appropriate personal protective equipment, improved communication and coordination across the utility, and enhanced workforce capacity, including increased staff numbers. Findings suggest that for more effective, equitable, and responsive climate adaptation, water utilities should explicitly solicit and include crews' knowledge and lived experiences in adaptation planning while prioritizing strategies that enhance frontline crews' capacity and working conditions as a form of reciprocal action.

Non-linear relationship between built environment and active travel: A hybrid model considering spatial heterogeneity

Exploring the mechanisms between the built environment and active travel is crucial for promoting green transportation and fostering the sustainable development of cities. Existing literature focuses on the correlation between the built environment and active travel in urban centers, with limited studies on suburban environments, ignoring the implications of spatial heterogeneity. This paper conducts a comprehensive spatio-temporal analysis of suburban residents’ active travel behavior and explores the nonlinear relationship between suburban built environment and active travel. A novel hybrid modeling framework that combines eXtreme Gradient Boosting and Multi-scale Geographic Weighted Regression is introduced to forecast suburban active travel demand with the consideration of the nonlinearity and spatial heterogeneity in parameter estimates. Shapley additive explanation is used to elucidate the non-linear relationship between built environment variables and active travel. The results indicate that the proposed hybrid model performs the best with high predictive power and interpretability. The density of tourist attractions, transportation facilities, and household properties emerges as the three most influential factors affecting residents’ active travel behavior. Social-economic attributes contribute 15.70% to the prediction, while three categories of built environment variables (accessibility, transportation facilities, and land use) contribute 7.31%, 5.13%, and 71.87%, respectively. The hybrid model appears to be effective in identifying the nonlinear relationship and threshold effects between built environment variables and active travel. Besides, the model provides actionable insights into designing sustainable and efficient suburban environments, supporting targeted planning and policy-making efforts.

The present and future of preoperative planning

Preoperative planning for shoulder arthroplasty has become widely used for primary cases and now also in revision situations. From the initial, two-dimensional manual planning efforts on CT scans, planning has evolved to now using three-dimensional planning software programs. A number of different programs exist with various methods underpinning their chosen landmarks and segmentation methods. Preoperative planning has allowed for development of execution tools to translate the preoperative plan to intra-operative reality. This article considers the particular relevance of preoperative arthroplasty planning to the shoulder joint, the current status of preoperative planning, the reasons to engage with preoperative planning, the execution tools available as an extension of preoperative planning, and the future of intra-operative execution technologies associated with planning. Preoperative planning is the foundation of prospective advances in these so-called enabling technologies and the future of preoperative planning will be shaped by a desire to continue to optimize execution techniques in shoulder arthroplasty, with the ultimate goal of using these techniques to achieve improved patient outcomes.

Python-Based Urban Land Suitability Evaluation for Effective Urban Planning

Abstract: One of the global environmental problems is that the population is growing rapidly around the world. unfortunately, land is a limited resource. Land suitability analysis merges as the most efficient and commonly used method that represents an effective informative tool to support policymakers and planners in developing optimal master plans, maintaining sustainability, and ensuring social equity among residents. Python's free and open-source ecosystem of geospatial libraries like Geo Pandas makes it a cost-effective alternative to proprietary GIS software for this purpose. Furthermore, Python excels at automation, allowing you to write scripts that save time and ensure consistency for repetitive tasks in land suitability analysis. At first, users can choose the project type based on the classification of land use and input raster and vector data. After that, each layer is reclassified, and a weighted overlay is applied at the end. A raster would be the final land suitability output file. Urban planning benefits greatly from Python's capabilities. Land suitability models can assess the viability of development projects by considering factors like flood risk, slope stability, and proximity to infrastructure. The applications extend far beyond these initial examples. Python's land suitability models are instrumental in environmental management as well. Habitat suitability modeling, for instance, considers factors like vegetation cover, water availability, and connectivity to existing habitats to identify areas suitable for specific wildlife species. This information is crucial for conservation planning and restoration efforts. This paper is designed to explain the beneficial aspects of a Python-based approach to land suitability modelling and how it operates.

Digitally derived trail terrain metrics

ABSTRACT Trails are essential transportation infrastructure supporting access to protected natural areas and providing recreation to hikers, runners, cyclists, equestrians, motorists, and many more worldwide. The slope of trails and their surrounding terrain influences physical trail sustainability and difficulty of travel. This research examines methods for using high-resolution digital elevation models to measure terrain steepness near trails and along trails or potential trail routes by comparing geographic information system (GIS) derived measurements to field measurements from the Appalachian Trail. The analysis validates the use of digitally derived trail terrain metrics and provides guidance to improve their utility in future trail planning and assessment efforts.

UTILIZING GOOGLE EARTH FOR ENVIRONMENTAL PLANNING: EXTRACTION OF POINT SOURCE LOCATIONS AT THE UPSTREAM OF SUNGAI SKUDAI CATCHMENT, JOHOR MALAYSIA

This study explores the application of geospatial technologies, specifically focusing on Google Earth (GE), to extract and mapping point source pollution in the upstream of Sungai Skudai Catchment (SRC). A thorough analysis of the locations of restaurants, launderettes, car washes, and workshops was made practical by the combination of Geographic Information Systems (GIS) tools with satellite images, which offers important data for environmental planning and water quality management. The research area, located in Johor, Malaysia, offers an example of the difficulties driven by rapid urban growth. This study provides comprehensive directions for extracting point sources, with a focus on verifying data via field surveys and Google searches. The upstream region was found to have 373 restaurants, 62 launderettes, 73 car washes, and 80 workshops. The dataset was further improved by the validation process, which determined any inconsistencies and added additional data. This study highlights the importance of field verification for improving point source pollution data accuracy. It also provides a base for comprehensive strategies for pollution management, land-use planning, and preservation efforts in rapidly changing environments, such as the Sungai Skudai Catchment.

Navigating dual hazards: Managing hurricane evacuation and sheltering operations Amidst COVID-19

Hurricane Laura made landfall in August of 2020 as a Category 4 storm, heavily affecting the coastlines of Texas and Louisiana. At the same time, both areas were coping with a surge in COVID-19 cases absent a vaccine. For this study, we explored how emergency management stakeholders navigated evacuation, sheltering, and re-entry planning and operations during a dual hazard threat where hurricane risk reduction measures contradicted COVID-19 risk reduction measures. We conducted 35 semi-structured interviews with emergency management stakeholders in Texas and Louisiana in the spring of 2021. Participants were recruited using a purposive sampling strategy designed to identify agency representatives and other officials involved with planning for hurricane season and with the Hurricane Laura response effort. We used thematic analysis to code and analyze the data. Findings suggest that while the process for planning for hurricanes had to shift to an online approach, the plan for addressing hurricane season was largely unchanged from the perspective of most participants until days before impact, when the decision was made to move to noncongregate sheltering. This led to adaptive and creative improvisation on the part of participants managing the evacuation and sheltering operations. Likewise, we found that caring for and communicating with evacuees in a noncongregate setting presented unanticipated challenges that required improvisation to address. Given the continued threat posed by COVID-19 and other respiratory illnesses, this study provides insights that emergency management stakeholders could apply to current and future planning and response efforts for hazards that require evacuation and sheltering.

Spatial Patterns of Cumulative Hotspots and Their Relationships with Topographical Factors and Land Use in Kanchanaburi Province, Thailand

The clustering of hotspots represents fires occurring at specific locations across various time intervals, and is an increasingly important interdisciplinary research phenomenon. This article investigates the spatial distribution of cumulative hotspots and their relationships with topographical factors and land use in Kanchanaburi province. Data from the Suomi NPP VIIRS system spanning from 2012 to 2021 were utilized for the analysis of Getis-Ord (Gi*) spatial autocorrelation using Fire Radiative Power values. The analysis included the correlation with topographic data such as elevation, slope, aspect, and overlay with land use data. The results reveal that significant hotspots are concentrated in the districts of Si Sawat, Thong Pha Phum, Sai Yok, Sangkhla Buri, and Mueang Kanchanaburi. The majority of hotspots were statistically insignificant (85%), with hotspots (10%) and cold spots (5%) predominantly occurring in forested and agricultural areas. Hotspots were particularly prevalent in the northern and northeastern regions. Therefore, the utilization of Suomi NPP VIIRS data in conjunction with spatial statistics can identify the occurrence of hotspots and cold spots, aiding in planning and policy-making efforts to mitigate hotspot occurrences.

A Survivor-Centered Framework for Domestic Violence Brief Crisis Intervention: A Stakeholder-Informed Approach

Program evaluation and assessment are critical for understanding the impact of domestic violence services and interventions and for making necessary refinements and revisions to programs. Demonstrating the impact of domestic violence programs (e.g., hotlines and shelters) poses challenges due to the complexities associated with abuse experiences. The use of an assessment framework will help categorize users’ multiple needs, clarify specific components of intervention approaches, and ensure that services meet clients’ needs. This article provides a comprehensive overview of a theoretical and stakeholder-informed approach used to develop an assessment framework for the National Domestic Violence Hotline (The Hotline). The research resulted in a framework which underscores the importance of survivor empowerment and support as key survivor outcomes. This article presents detailed information about the SAF-T project including methods and processes used to develop the survivor-centered framework and provides guidance for those interested in developing similar theoretical and stakeholder-informed frameworks for program planning, measuring performance, and evaluation efforts.

A Hybrid Markov-SPC Approach to Assess Cost Differences in Urgent Care Utilization Using Patient-Reported Data in Inflammatory Bowel Disease.

Cost is a key outcome in quality and value, but it is often difficult to estimate reliably and efficiently for use in real-time improvement efforts. We describe a method using patient-reported outcomes (PROs), Markov modeling, and statistical process control (SPC) analytics in a real-time cost-estimation prototype designed to assess cost differences between usual care and improvement conditions in a national multicenter improvement collaborative-the IBD Qorus Learning Health System (LHS). The IBD Qorus Learning Health System (LHS) collects PRO data, including emergency department utilization and hospitalizations from patients prior to their clinical visits. This data is aggregated monthly at center and collaborative levels, visualized using Statistical Process Control (SPC) analytics, and used to inform improvement efforts. A Markov model was developed by Almario et al to estimate annualized per patient cost differences between usual care (baseline) and improvement (intervention) time periods and then replicated at monthly intervals. We then applied moving average SPC analyses to visualize monthly iterative cost estimations and assess the variation and statistical reliability of these estimates over time. We have developed a real-time Markov-informed SPC visualization prototype which uses PRO data to analyze and monitor monthly annualized per patient cost savings estimations over time for the IBD Qorus LHS. Validation of this prototype using claims data is currently underway. This new approach using PRO data and hybrid Markov-SPC analysis can analyze and visualize near real-time estimates of cost differences over time. Pending successful validation against a claims data standard, this approach could more comprehensively inform improvement, advocacy, and strategic planning efforts.