Full-scale Implementation Research Articles

Usability of an automated medication dispensation device and adherence dashboard: A study protocol.

Non-adherence to prescribed medication regimens can lead to suboptimal control of chronic health conditions and increased hospitalizations. Older adults may find it particularly challenging to self-manage medications due to physical and cognitive limitations, resulting in medication non-adherence. While automated medication dispensing technologies may offer a solution for medication self-management among older adults, these technologies must demonstrate usability before effectiveness can be investigated and products made available for widespread use. This study will aim to measure usability, workload, and unassisted task completion rates of an automated medication dispenser and medication adherence dashboard on the Medipense portal with older adults and their clinicians, respectively. This study is designed as a convergent parallel mixed-methods observational study with older adults and their clinicians. Usability will be examined with the use of the System Usability Scale (SUS) while NASA Load Index (NASA-TLX) will be utilized to assess the workload of both the device and the adherence monitoring platform. Cognitive walkthrough will be utilized prior to usability testing to identify series of steps required to use the automated dispenser and adherence dashboard. The study will assess the unassisted task completion rates to successfully operate the device. Semi-structured interviews with both types of participants will provide qualitative data with which to comprehensively gauge the automated dispenser user experience. The results of this study will allow us to examine usability of both the automated medication dispensing system and the adherence monitoring dashboard from older adult and health-care provider perspectives. The results of this study will highlight and address the challenges with usability that older adults and health-care providers may face with this device and dashboard. The results of this study will be used to optimize the usability of both the automated medication dispenser and the adherence dashboard. In clinical practice, usability of technology is important to establish prior to full-scale implementation. Products that are not user friendly, add to workload, impact workflow, or are difficult to navigate by both clinicians and population in general may not be adopted. Usability permits an evaluation of the products, to identify problems that must be addressed prior to implementation and to ensure products are useful in clinical practice.

Microbial community evolution in a lab-scale reactor operated to obtain biomass for biochemical methane potential assays

Biochemical methane potential (BMP) test is an important tool to evaluate the methane production biodegradability and toxicity of different wastes or wastewaters. This is a key parameter for assessing design and feasibility issues in the full-scale implementation of anaerobic digestion processes. A standardized and storable inoculum is the key to obtain reproducible results. In Uruguay, a local enterprise dedicated to design and install anaerobic digesters operated a lab-scale bioreactor as a source of biomass for BMP tests, using a protocol previously described. This reactor was controlled and fed with a mixture of varied organic compounds (lipids, cellulolytic wastes, proteins). Biomass was reintroduced into the reactor after BMP assays to maintain a constant volume and biomass concentration. The aim of this work was to evaluate how the microbial community evolved during this operation and the effect of storing biomass in the refrigerator. The composition of the microbial communities was analyzed by 16S rRNA amplicon sequencing using primers for Bacteria and Archaea. The methanogenic activity was determined, and the methanogens were quantified by mcrA qPCR. One sample was stored for a 5-month period in the refrigerator (4 °C); the activity and the microbial community composition were analyzed before and after storage. Results showed that applying the reported methodology, a reliable methanogenic sludge with an acceptable SMA was obtained even though the reactor suffered biomass alterations along the evaluated period. Refrigerating the acclimatized biomass for 5 months did not affect its activity nor its microbial composition according to the 16S rRNA gene sequence analysis, even though changes in the mcrA abundance were observed.Key points• The applied methodology was successful to obtain biomass suitable to perform BMP assays.• The microbial community was resilient to external biomass addition.• Biomass storage at 4 °C for 5 months did not alter the methanogenic activity.Graphical

Analysis of the Construction of Core Literacy of Students in Vocational Undergraduate Education

Vocational undergraduate education has evolved from its initial stages to a full-scale implementation, achieving historic milestones along the way. However, its appeal still lags significantly behind that of general education. The development of students’ core competencies in vocational undergraduate education faces several challenges, including the need for improvements in top-level design, a stronger focus on connotation development, and an upgraded linkage mechanism. To address these issues, it is suggested to refine the top-level design, enhance internal motivation, and build a robust vocational education ecosystem.

Thermal seawater desalination for irrigation purposes in a water-stressed region: Emerging value tensions in full-scale implementation

Water scarcity in arid regions has driven the spread of desalination. These systems contribute to water access but come at an intensive energy cost, and lead to brine discharge and associated environmental impacts. This work aims to investigate emerging societal issues and tensions when developing and implementing a thermal desalination system to produce irrigation water in the South of Spain. This has been done in a demonstration system for solar desalination able to recover water and salts from desalination brine. For this purpose, a context-sensitive design exercise has been implemented. First, tensions between social values expressed by diverse stakeholders have been identified. Then, a set of technical scenarios for the full-scale implementation of the system were designed and evaluated, comparing them to conventional membrane desalination. The analysis indicates high economic and energy costs to avoid the environmental impacts of increasing water production.

Applying the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability Framework Across Implementation Stages to Identify Key Strategies to Facilitate Clinical Decision Support System Integration Within a Large Metropolitan Health Service: Interview and Focus Group Study.

Computerized clinical decision support systems (CDSSs) enhance patient care through real-time, evidence-based guidance for health care professionals. Despite this, the effective implementation of these systems for health services presents multifaceted challenges, leading to inappropriate use and abandonment over the course of time. Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework, this qualitative study examined CDSS adoption in a metropolitan health service, identifying determinants across implementation stages to optimize CDSS integration into health care practice. This study aims to identify the theory-informed (NASSS) determinants, which included multiple CDSS interventions across a 2-year period, both at the health-service level and at the individual hospital setting, that either facilitate or hinder the application of CDSSs within a metropolitan health service. In addition, this study aimed to map these determinants onto specific stages of the implementation process, thereby developing a system-level understanding of CDSS application across implementation stages. Participants involved in various stages of the implementation process were recruited (N=30). Participants took part in interviews and focus groups. We used a hybrid inductive-deductive qualitative content analysis and a framework mapping approach to categorize findings into barriers, enablers, or neutral determinants aligned to NASSS framework domains. These determinants were also mapped to implementation stages using the Active Implementation Framework stages approach. Participants comprised clinical adopters (14/30, 47%), organizational champions (5/30, 16%), and those with roles in organizational clinical informatics (5/30, 16%). Most determinants were mapped to the organization level, technology, and adopter subdomains. However, the study findings also demonstrated a relative lack of long-term implementation planning. Consequently, determinants were not uniformly distributed across the stages of implementation, with 61.1% (77/126) identified in the exploration stage, 30.9% (39/126) in the full implementation stage, and 4.7% (6/126) in the installation stages. Stakeholders engaged in more preimplementation and full-scale implementation activities, with fewer cycles of monitoring and iteration activities identified. These findings addressed a substantial knowledge gap in the literature using systems thinking principles to identify the interdependent dynamics of CDSS implementation. A lack of sustained implementation strategies (ie, training and longer-term, adopter-level championing) weakened the sociotechnical network between developers and adopters, leading to communication barriers. More rigorous implementation planning, encompassing all 4 implementation stages, may, in a way, help in addressing the barriers identified and enhancing enablers.

Стохастично моделиране при маслодайните култури в България в условията на Зелената сделка

This study is designated to elaborate and propose a model for estimation of outcomes and effects at the level of production of oilseed crops in Bulgaria. The projections are manifested through scenarios based on the stochastic error, which is yielded as a difference between real and modelling results on the projected variables. It is deemed to provide a good basis for modelling of scenarios driven by specific parameters from the Green Deal of EU. The applied stochastic model gives a very good basis to elaborate and simulate further sensitive scenarios generated by the factors and variables of the Green Deal. It is thought to carried out through incorporation of the variables covering the world price of oilseeds and the use of nitrogen mineral fertilizers. The applied and evolved model for projecting the development and future outlook of the production of oilseed crops in Bulgaria provides a system of model equations, which is created as a interdependencies between different variables. This model is considered to achieve and reveal specific quantitative results, facilitating the scenario comparisons. The presented model results are made as an estimation of the stochastic error, standing for the difference between the model over the real historical data in the period of 15 years, between 2007 – 2021. It is assumed that production and market risks in the oilseeds sector will increase crucially if the full-scale implementation of the intended restrictions and bans connected to Green Deal measures are adopted. Those restrictions are seen in purported reduction in the use of plant protection chemicals and fertilizers application. Production risks are mainly highlighted in the cut of production yield, market volatility of the oilseed commodity and the affected efficiency due to cost increment. Market risks will mainly be related to securing a market stability and appropriate cost level of the production. The results from the model show that up to the time of this study work covering the historical real data up to 2021, specific signals and turbulences in the production, supply and market performance of the sector are not yet noticed and the supposed stagnation effects from the Green Deal measures are not displayed. Therefore, putting aside the expected strong impact of the Green Deal on the sector by 2030, the production and consumption of oilseeds is projected to remain strong and to gravitate in the high levels achieved in the best years reached recently, indicating that the sector is on the upward trend and the constraints and bans of the Green Deal may have a greater affect eventually in future.

Perspectives of Nursing Home Staff in Advance Care Planning Conversations: Experiences from the APPROACHES Project

ObjectivesAdvance care planning (ACP) is considered a best practice in the nursing home setting; however, there is a lack of consistency in the training of nursing home staff and implementation of structured ACP programs. A qualitative study interviewing ACP specialists in nursing homes was conducted to understand the experience of staff engaged in Aligning Patient Preferences – a Role offering Alzheimer's patients, Caregivers, and Healthcare providers Education and Support (APPROACHES), an embedded pragmatic clinical trial to improve ACP. DesignQualitative interviews regarding ACP specialists’ experiences and perceived intervention impact. Setting and ParticipantsStaff of intervention-assigned nursing home facilities who completed a minimum of 10 ACP conversations with residents during APPROACHES program implementation. MethodsFourteen staff were interviewed. Interviews were transcribed and coded by the research team. ResultsThere were 21 codes identified that were then distilled into the following 5 themes: (1) experiences with the ACP specialist program, (2) engaging in ACP conversations, (3) considerations related to dementia, (4) benefits and challenges of ACP, and (5) involvement of multiple people in the ACP process. Participant responses suggested variability in experiences with the ACP specialist program and highlighted many aspects relevant to engaging in conversations with families and residents, particularly those living with dementia. Benefits of ACP, including relationship building and increased preparedness for changes in health status, were balanced with challenges related to sensitive conversation topics and logistical difficulties in scheduling ACP discussions. ACP specialists discussed the multiple roles that others played in the ACP process. Conclusions and ImplicationsFindings from this analysis provide insights into tailoring APPROACHES and other ACP programs for full-scale implementation in the nursing home setting. Nursing home staff experiences tailoring the program to fit their environments were reflective of the pragmatic nature of the ACP specialist program.

Comprehensive Investigation of the Thermal Performance of an Electrically Heated Double-Glazed Window: A Theoretical and Experimental Approach

The thermal performance of windows is an important area of research to reduce the energy consumption of buildings and improve indoor comfort. The application of innovative glazing technologies can improve the energy performance of windows and transparent facades, resulting in significant energy savings. This paper presents research results on the energy performance of electrically heated windows. A comprehensive CFD and experimental analysis of the heat transfer processes in a window space depending on the size, power, and location of an electric heater was performed. The convective gas flows in the gas gaps and in the boundary layer were also analysed, and it is shown that a window with an electric heater can reduce the energy consumption of a room by 10–12%. This study is a pilot study to assess the feasibility and cost-effectiveness of electric local heating of a window or facade to minimise heat loss before full-scale implementation. The results of numerical modelling and experimental studies confirm the potential of the new technologies.

Valorizing Lycii fructus waste residue into polysaccharide-rich extracts: Extraction methodologies, physicochemical characterization, in vitro activities and economic feasibility

The high polysaccharide content of Lycii fructus agri-food waste should be reclaimed for value liberation from both environmental and economic perspectives. In this study, waste from L. fructus pigment products was valorized on a bench scale by upcycling into active polysaccharide-rich extracts. The methodological feasibility of polysaccharide recovery from L. fructus waste was evaluated using sequential extraction techniques. Three fractions LFP-30, LFP-100, and LFP-121, were obtained under stepwise increases in temperature and pressure. Highly heterogeneous xyloglucan (XG)-pectin macromolecules composed of linear homogalacturonan (HG) and alternating intra-RG-I-linkers, with topological neutral branches and XG participation, were predominant among the L. fructus polysaccharides (LFPs). Antioxidant activities in LFPs were unaffected by waste resources and severe extraction methodology conditions. Additionally, the direct investment potential of polysaccharide recovery was evaluated for full-scale implementation. This study demonstrated the necessity and feasibility of extracting bioactive polysaccharides with potential applications from L. fructus waste, and provided a sustainable strategy for transforming L. fructus waste disposal problems into value-added products using cost-effective methodologies.

Enhancing ozonation technology: A case study on full-scale airlift reactor upgrades in the existing wastewater treatment plant's ozonation tank using CFD

Traditional pneumatic bubble column reactors (PBCRs) in wastewater treatment often have limitations in ozone distribution and disinfection efficacy. This study introduces an optimized Airlift Reactor (ALR) design, enhanced with Computational Fluid Dynamics (CFD), to improve ozone contact time and uniform distribution. Tailored for the SONATRACH GP1/Z Complex in Bethioua, Algeria, the ALR addresses the treatment needs of the facility's WWTP Phase-1, handling domestic wastewater. The study is unique for its full-scale implementation of the ALR, as previous research focused on lab-scale cases. Advanced CFD simulations optimized the ALR design, focusing on baffle configurations to enhance ozone disinfection. The upgraded One Side Baffled Airlift (OS-BALR) variant achieved a Total Coliform inactivation rate of 94.52 %, compared to 74 % with the traditional design. The OS-BALR also demonstrated a lower ozone mass transfer coefficient (KLa) of 0.0048 s−1, improving treatment efficiency and reducing energy consumption. While the Baffled Bubble Column (BBC) reactor showed a higher KLa of 0.0055 s−1 and a microbial removal efficacy of 96.12 %, it is more energy-intensive. This study advances wastewater treatment by bridging innovation with industrial application, contributing to sustainable wastewater management practices globally.

Numerical analysis of hydrogen storage in lined rock cavern under high pressure and its implications to hydrogen embrittlement

Underground hydrogen storage could provide buffer capacity to store the excess energy from renewable resources. A lined rock cavern (LRC) is one of the hydrogen geologic storage site options. It offers great flexibility because it does not rely on the existence of salt caverns, aquifer formations or depleted hydrocarbon reservoir fields. However, many important aspects have to be investigated before its full-scale implementation, among them (1) the effect of spatial variation of rock mass properties and (2) hydrogen embrittlement on the steel lining. We present a numerical study on these two aspects by simulating field tests at a pilot LRC project. For the effect of rock heterogeneity, we assign a spatial variation of elastic properties based on the Gaussian covariance model. The results show a good agreement with the field measurements. The spatial correlation length of rock mass elastic properties only has a minor impact on the cavern surface deformation. Regarding hydrogen embrittlement, our simulations predict a significant hydrogen diffusion in the low alloy steel (S355) lining after ∼2 months of operation. The fracture simulations show little fracture propagation even after 10 years of contact with hydrogen gas. However, the product loss may be too high for the low alloy steel (S355). We would recommend the use of stainless steel to inhibit the hydrogen diffusion. We show that advanced numerical models are powerful tools to ensure the safety of hydrogen storage in LRCs.

Carbon capture and storage at Malaysia power plants: Evaluation of its feasibility and requisite enablers

Rapidly growing GHG emissions are significantly altering the world climate, necessitating a global decarbonization efforts to avert irreversible catastrophic failure of the world ecosystem. Malaysia is pledging to achieve carbon neutrality by 2050 and has subsequently identified Carbon Capture and Storage (CCS) as one of the solutions for carbon removal from its energy sector by 2050. However, the implementation of CCS presents formidable challenges, encompassing both technical and commercial complexities, especially for a nation like Malaysia, which has limited experience in large-scale CCS deployment. This study evaluates the feasibility of CCS implementation in Malaysia's fossil fuel power plants by conducting a comprehensive techno-economic assessment, taking into considerations the prevailing energy landscape of the country. This assessment is very crucial to demonstrate the feasibility of this plan within the timeframe, considering the limited research have been done to assess a national-scale implementation, as well as to provide the important insights for future policy implication to promote CCS adoption. The CCS scenarios are assessed through an analytical approach, and comparative analyses are conducted between alternative paths. The result shows that a large-scale implementation of CCS at Malaysia's fossil fuel power plant to achieve net-zero emission by 2050 are feasible given a strong enforcement on emission policy and establishment of CCS legal framework. CCS can potentially reduce 60% of Malaysia's energy sector total emissions, and a solar-supported CCS helps to reduce it further. Levelized Cost of Electricity analysis reveals that the implementation of CCS leads to only a minimal increase between pre- and post-CCS LCOE when carbon price is considered. A SWOT-PESTLE analysis was also conducted to identify gaps in regulatory framework, financial and social aspects. It can be concluded that CCS is a techno-economically viable solution, however Malaysia's readiness for CCS implementation is still at a very novice stage, and aggressive actions are needed to enable a successful full-scale implementation.

Insight into electricity production performance from dried waste activated sludge in dual chamber microbial fuel cells: Influencing factors, neural network modelling and microbial community analysis

Directly deriving electrical energy from waste activated sludge (WAS) by using microbial fuel cell (MFC) is one of the most promising alternatives to resource utilization of WAS. However, obtaining high MFC performance is still a great challenge for the full-scale implementation of MFC. Therefore, this study aimed to quantify and model the effect of different operating parameters on the performance of MFC fed with dried WAS as anode substrate. The results indicated that MFC exhibited a fast start-up time of 3 days at the inoculated anaerobic sludge: dry WAS mass ratio of 1:5. Moreover, the output voltage and power density of MFC were highly dependent of anolyte pH and temperature, WAS concentration, which was well simulated and predicted by the BPANN model. It was revealed that MFC fed with dry WAS exhibited good performance at 55ºC, pH 9.0 and WAS concentration of 16 g/L, while the stable output voltage and power density were 0.705 V and 5.248 W/m3, respectively. The anolyte temperature significantly affected microbial communities of the anode biofilm. At the phylum level, Synergistota and Proteobacteria dominated the anode biofilm at 35ºC, while Firmicutes was absolutely enriched in the anode biofilm at 55ºC. At the genus level, the predominant Advenella is detected in the anode biofilm at 35ºC, whereas the preponderant MBA03 is identified in the anode biofilm at 35ºC. The findings herein may provide a route for efficiently driving power energy from WAS, which can facilitate the fulfillment of full-scale MFC for the resource utilization of WAS.

Developing a strategic plan for efficient management of industrial waste in the machinery sector at United Tractors Company

United Tractors Company prioritizes sustainable waste management practices. This study investigated their current system, aiming to identify opportunities for improvement in efficiency and environmental impact. The research focused on how effectively United Tractors manages their waste streams, from minimizing generation at the source to responsibly processing and disposing of unavoidable waste. The analysis revealed a successful integrated waste management system at United Tractors, encompassing practices like composting, recycling, and proper treatment of hazardous materials. This approach demonstrates their commitment to minimizing their environmental footprint. The study went beyond current practices, identifying promising advancements in waste processing technologies like gasification and bioethanol production. These techniques offer exciting possibilities for further reducing waste and potentially even generating valuable resources from waste materials. The effectiveness of United Tractors' system can be attributed to their comprehensive approach. The study conducted a detailed waste collection study to understand the composition and volume of waste generated across various departments. This data-driven approach allowed for a thorough cost analysis and an evaluation of the operational efficiency within the waste management system. Importantly, the study highlighted the potential benefits of incorporating advanced waste processing techniques for even greater sustainability in the future. While further feasibility studies are needed before full-scale implementation, these findings pave the way for United Tractors to develop and implement even more sustainable waste management practices in the coming years

Effect of hydrothermal pretreatment on leachate fed Scenedesmus sp. biomass solubilization and biogas production

The aim of the present study was to assess the effect of hydrothermal pretreatment on the solubilization and anaerobic digestion (AD) of Scenedesmus sp. biomass. At first, the microalgae was cultivated in 5% fresh leachate (FL) to recover nutrients such as nitrogen and phosphorus. Scenedesmus sp. grown in 5% FL obtained 100%, 77% and 97% removal efficiency of ammonium nitrogen (NH4+ - N), total Kjeldahl nitrogen (TKN) and phosphate phosphorous (PO43− -P), respectively. In the following step, the hydrothermal pretreatment of Scenedesmus sp. biomass was carried out at 120, 150 and 170 °C and retention time of 0, 30 and 60 min to evaluate its solubilization and biogas production through AD in batch test. Soluble chemical oxygen demand (sCOD) increased by 260% compared to untreated microalgae at 170 °C for 60 min. In comparison to untreated microalgae, the highest increase in biogas (70%) and methane yield (100%) was observed for 150 °C and 60 min pretreated microalgae as a consequence of hydrothermal pretreatment. Hydrothermal pretreatment has shown effectiveness in enhancing biomass solubilization and increasing biogas yield. Nevertheless, further research at the pilot scale is necessary to thoroughly evaluate the potential and feasibility of hydrothermal pretreatment for full-scale implementation.

Questioning Japan's English-Only and Other Language Teaching Communicative Directives

In 2014 the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) published its “English Education Reform Plan corresponding to Globalization” so as to “promote the establishment of an educational environment” conducive to enhancing English education in Japan. This plan, which explicitly covers pre-tertiary education levels and was to be incrementally promoted prior to full scale implementation beginning in fiscal year 2020 with Japan’s hosting of the Tokyo Olympics, states that English education classes are to be conducted in English from the lower secondary school level. This directive to match the students’ target language (TL) with the language of instruction evinces MEXT’s belief that English mediated instruction (EMI) directly impacts TL learning outcomes (e.g., by students consequently displaying competency in TL skills), with those results considered to be key first to students’ university-level English language learning endeavors and then to Japan’s increased internationalization and globalization efforts. To external observers, such an English-only stance appears fully apropos, valid, and justifiable. However, MEXT’s directives must be questioned, not only because of the general untenability of first language (L1) exclusion in TL learning situations, but also because of the difficulties encountered by both educational institutions and their instructors as they attempt to follow MEXT’s directives, particularly after the unforeseen move to remote teaching and learning due to the COVID-19 pandemic. This brief article discusses MEXT’s reform plan, examples of COVID-19’s impact on EMI in communicative teaching contexts, and the myriad benefits to be had by allowing L1 inclusion in TL instruction.

Predicting Attack Paths from Application Security Vulnerabilities Using a Multi-Layer Perceptron

This paper is in the series of continuing research and proposes an approach to predicting possible attack paths from application security vulnerability-based attack trees. The attack trees are formed by stringing together weaknesses discovered in an application code and a group of applications within a domain. The Common Weakness Enumeration (CWE) and Common Vulnerabilities and Exposures (CVE) linked together as a string of vulnerabilities in the attack trees can be visualized as pathways for attacks. These pathways become potential attacks that can spread vertically and horizontally leading to a multi-path attack that can involve multiple software applications. With more data, and huge number of vulnerabilities, it will become impossible to identify all attack paths unless a full-scale implementation of an autonomous processing mechanism is in place. Machine Learning (ML) and Deep Learning (DL) techniques have been adopted in the cybersecurity space for decades, however all the studies have been around networks, endpoints, and device monitoring. This paper focuses on application security and building on earlier work cited, the use of a vulnerability map that uses attack vectors in a Deep Learning (DL) method implementing a Multi-Layer Perceptron (MLP) forms the basis for developing a predictive model that relates a set of linked vulnerabilities to an attack path. The results are encouraging, and this approach will help in identifying successful or failed attack paths involving multiple applications, isolated or grouped, and will help focus on the right applications and the vulnerabilities associated as priority for remediation.

Predicting healthcare expenditure based on Adjusted Morbidity Groups to implement a needs-based capitation financing system

BackgroundDue to population aging, healthcare expenditure is projected to increase substantially in developed countries like Spain. However, prior research indicates that health status, not merely age, is a key driver of healthcare costs. This study analyzed data from over 1.25 million residents of Spain's Murcia region to develop a capitation-based healthcare financing model incorporating health status via Adjusted Morbidity Groups (AMGs). The goal was to simulate an equitable area-based healthcare budget allocation reflecting population needs.MethodsUsing 2017 data on residents' age, sex, AMG designation, and individual healthcare costs, generalized linear models were built to predict healthcare expenditure based on health status indicators. Multiple link functions and distribution families were tested, with model selection guided by information criteria, residual analysis, and goodness-of-fit statistics. The selected model was used to estimate adjusted populations and simulate capitated budgets for the 9 healthcare districts in Murcia.ResultsThe gamma distribution with logarithmic link function provided the best model fit. Comparisons of predicted and actual average costs revealed underfunded and overfunded areas within Murcia. If implemented, the capitation model would decrease funding for most districts (up to 15.5%) while increasing it for two high-need areas, emphasizing allocation based on health status and standardized utilization rather than historical spending alone.ConclusionsAMG-based capitated budgeting could improve equity in healthcare financing across regions in Spain. By explicitly incorporating multimorbidity burden into allocation formulas, resources can be reallocated towards areas with poorer overall population health. Further policy analysis and adjustment is needed before full-scale implementation of such need-based global budgets.

Scenario-based assessment of fecal pathogen sources affecting bathing water quality: novel treatment options to reduce norovirus and Campylobacter infection risks.

Wastewater discharge and runoff waters are significant sources of human and animal fecal microbes in surface waters. Human-derived fecal contamination of water is generally estimated to pose a greater risk to human health than animal fecal contamination, but animals may serve as reservoirs of zoonotic pathogens. In this study, quantitative microbial risk assessment (QMRA) tools were used to evaluate the hygienic impact of sewage effluents and runoff water from municipalities and animal farms on surface and bathing waters. The human-specific microbial source tracking (MST) marker HF183 was used to evaluate the dilution of fecal pathogens originating from the sewage effluent discharge to the downstream watershed. As novel risk management options, the efficiency of UV-LED disinfection and wetland treatment as well as biochar filtration was tested on-site for the contamination sources. According to the dilution pattern of the MST marker HF183, microbes from wastewater were diluted (2.3-3.7 log10) in the receiving waters. The scenario-based QMRA revealed, that the health risks posed by exposure to human-specific norovirus GII and zoonotic Campylobacter jejuni during the bathing events were evaluated. The risk for gastroenteritis was found to be elevated during wastewater contamination events, where especially norovirus GII infection risk increased (1-15 cases per day among 50 bathers) compared with the business as usual (BAU) situation (1 case per day). The noted C. jejuni infection risk was associated with animal farm contamination (1 case per day, versus 0.2-0.6 cases during BAU). Tertiary treatment of wastewater with wetland treatment and UV-LED disinfection effectively reduced the waterborne gastroenteritis risks associated with bathing. Based on the experiences from this study, a QMRA-based approach for health risk evaluations at bathing sites can be useful and is recommended for bathing site risk assessments in the future. In case of low pathogen numbers at the exposure sites, the MST marker HF183 could be used as a pathogen dilution coefficient for the watershed under evaluation. The full-scale implementation of novel tertiary treatment options at wastewater treatment plants (WWTPs) as well as on-site runoff water treatment options should be considered for infection risk management at locations where scenario-based QMRA implies elevated infection risks.

563 Team Science to Assess Effectiveness and Impact in Public Healthcare Delivery System Contracting

OBJECTIVES/GOALS: Healthcare organizations and payers are moving from accountability to effectiveness frameworks. Static vendor contracts for full-scale implementation limit organizations' ability to evaluate impact before scale-up, or to iteratively improve. Our team science innovation employs science and learning methods as systems engage vendors. METHODS/STUDY POPULATION: Our team science innovation is a method to assess and model impact of interventions at scale in healthcare delivery systems. We are integrating expertise in learning processes of an academic medical center (UCLA CTSI) with the organizational knowledge and methodological expertise of the nation’s largest Medicaid managed care plan (LA Care Health Plan), which has over 2 million members. The LA Care Advanced Analytics Lab has unique capability in machine learning, while enables deep learning of variation. Our innovative product is a template to quickly mobilize evaluation and learning for a diverse population in a varied and distributed delivery system. The template design enables rapid learning for the full-scale policy implementation often imposed by government, and in the short timeframes involved. RESULTS/ANTICIPATED RESULTS: LA Care and the UCLA CTSI partnered to provide subject matter expertise and design effective pilots for interventions such as transitional care services, complex care management, and physician home visit strategies, accounting for confounding factors affecting the intervention and outcome. So far, collaborative modeling and design has produced a successful pilot of a physician home visit program intended to reduce avoidable emergency department visits. This pilot quickly revealed several major changes that would need to be incorporated for the contracted vendor to produce results if operated at scale, further informed by machine learning, in sufficient time to inform the contracting process. There are multiple evolving applications, including housing/homelessness. DISCUSSION/SIGNIFICANCE: Integrating the large data and analytics of a large healthcare organization with learning methods from the CTSI -- including learning from variation and designs for studying impact during scale-up -- fosters academic-community team science that could significantly improve the value of our largest delivery systems, public and commercial.