An Integrated Assessment approach to linking biophysical modelling and economic valuation tools

Natural resource management (NRM) typically involves complex decisions that affect a variety of stakeholder values. Efficient NRM, which achieves the greatest net environmental, social and financial benefits, needs to integrate the assessment of environmental impacts with the costs and benefits of investment. Integrated assessment (IA) is one approach that incorporates the several dimensions of catchment NRM, by considering multiple issues and knowledge from various disciplines and stakeholders. Despite the need for IA, there are few studies that integrate biophysical modelling tools with economic valuation. In this paper, we demonstrate how economic non-market valuation tools can be used to support an IA of catchment NRM changes. We develop a Bayesian Network model that integrates: a process-based water quality model; ecological assessments of native riparian vegetation; estimates of management costs; and non-market (intangible) values of changes in riparian vegetation. This modelling approach illustrates how information from different sources can be integrated in one framework to evaluate the environmental and economic impacts of NRM actions. It also shows the uncertainties associated with the estimated welfare effects. By estimating the marginal social costs and benefits, a cost-benefit analysis of alternative management intervention can be gained and provides more economic rationality to NRM decisions.Bayesian networks, bio-economic modelling, catchment management, cost-benefit analysis, environmental values, integrated assessment and modelling, non-market valuation, riparian vegetation, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Operating theatre modelling: integrating social measures

Hospital resource modelling literature is primarily focussed on productivity and efficiency measures. In this paper, our focus is on the alignment of the most valuable revenue factor, the operating room (OR) with the most valuable cost factor, the staff. When aligning these economic and social decisions, respectively, into one sustainable model, simulation results justify the integration of these factors. This research shows that integrating staff decisions and OR decisions results in better solutions for both entities. A discrete event simulation approach is used as a performance test to evaluate an integrated and an iterative model. Experimental analysis show how our integrated approach can benefit the alignment of the planning of the human resources as well as the planning of the capacity of the OR based on both economic related metrics (lead time, overtime, number of patients rejected) and social related metrics (personnel preferences, aversions, roster quality)

Designing Frameworks to Deliver Unknown Information to Support MBIs

This paper reports on a Catchment Modelling Framework (CMF) designed to support an Australian pilot of an auction for multiple environmental outcomes EcoTender. The CMF is used to estimate multiple environmental outcomes including carbon, terrestrial biodiversity, aquatic function (water quality and quantity) and saline land area. This information was previously unavailable for application to environmental markets. This is the first time a market-based policy has been fully integrated from desk to field with a Catchment Modelling Framework for the purchase of multiple outcomes. This framework solves the unknown information problem of linking paddock scale landuse and management to catchment-scale environmental outcomes. The framework provides the Victorian government with a replicable transparent evidence-based approach to the procurement of environment outcomes.Research Methods/ Statistical Methods,

Dynamic integrated water quality modelling: A case study of the Lambro River, northern Italy

In this paper an integrated modelling approach is presented and applied to a 26km stretch of the Lambro River downstream of the Merone Wastewater Treatment Plant in northern Italy. The sub-models used (ASM1 for the treatment plant and RWQM1 for the river) have been implemented in the WEST® simulator. Hydraulics and quality processes of the Lambro River have been modelled with a ‘tanks in series’ approach. The purpose of this study is to model the effect on river water quality of an insufficient treatment capacity of the WWTP. The plant was constantly operating at its maximum hydraulic capacity, leading to a daily bypass of dry weather wastewater, which imposed a marked diurnal cycle on pollutant concentrations in the river. The assessment of the actual WWTP upgrade has confirmed its beneficial effect on the river water quality.Keywords: ASM1, integrated modelling, LAS, model interfaces, RWQM

Evaluation of complex integrated care programmes: the approach in North West London

Background: Several local attempts to introduce integrated care in the English National Health Service have been tried, with limited success. The Northwest London Integrated Care Pilot attempts to improve the quality of care of the elderly and people with diabetes by providing a novel integration process across primary, secondary and social care organisations. It involves predictive risk modelling, care planning, multidisciplinary management of complex cases and an information technology tool to support information sharing. This paper sets out the evaluation approach adopted to measure its effect. Study design: We present a mixed methods evaluation methodology. It includes a quantitative approach measuring changes in service utilization, costs, clinical outcomes and quality of care using routine primary and secondary data sources. It also contains a qualitative component, involving observations, interviews and focus groups with patients and professionals, to understand participant experiences and to understand the pilot within the national policy context. Theory and discussion: This study considers the complexity of evaluating a large, multi-organisational intervention in a changing healthcare economy. We locate the evaluation within the theory of evaluation of complex interventions. We present the specific challenges faced by evaluating an intervention of this sort, and the responses made to mitigate against them. Conclusions: We hope this broad, dynamic and responsive evaluation will allow us to clarify the contribution of the pilot, and provide a potential model for evaluation of other similar interventions. Because of the priority given to the integrated agenda by governments internationally, the need to develop and improve strong evaluation methodologies remains strikingly important

BRINGING CARE QUALITY TO LIFE: TOWARDS QUALITY INDICATOR-DRIVEN PATHWAY MODELLING IN HEALTH CARE NETWORKS

Integrated care is a promising approach to create connectivity, alignment, and collaboration in a network of health care providers, especially for people with long-term and complex conditions. It aims at improving care quality, but a common, standardised quality management approach for such networks is still missing. In this context, care pathways are recognised as important quality management tools. They define key goals of care and organise actions to achieve them. However, their utilisation in terms of quality management is lacking methodological support. The article provides the conceptual foundations as part of a design-oriented research project that aims to develop a method for the utilisation of care pathways for quality management purposes in inte-grated care settings. Therefore, the realm of process quality in integrated care is analysed and structured by means of a classification framework. Moreover, relevant concepts for the integration of quality indicators in care pathways are analysed and represented with a semi-formal domain ontology. These conceptualisations prepare the next steps in the project’s research agenda. These comprise the development and evaluation of an indicator-driven care pathway modelling lan-guage and its application for quality management in integrated care. This approach could make quality of integrated care more transparent and manageable

Challenges in the harmonisation of global integrated assessment models: a comprehensive methodology to reduce model response heterogeneity

Harmonisation sets the ground to a solid inter-comparison of integrated assessment models. A clear and transparent harmonisation process promotes a consistent interpretation of the modelling outcomes divergences and, reducing the model variance, is instrumental to the use of integrated assessment models to support policy decision-making. Despite its crucial role for climate economic policies, the definition of a comprehensive harmonisation methodology for integrated assessment modelling remains an open challenge for the scientific community. This paper proposes a framework for a harmonisation methodology with the definition of indispensable steps and recommendations to overcome stumbling blocks in order to reduce the variance of the outcomes which depends on controllable modelling assumptions. The harmonisation approach of the PARIS REINFORCE project is presented here to layout such a framework. A decomposition analysis of the harmonisation process is shown through 6 integrated assessment models (GCAM, ICES-XPS, MUSE, E3ME, GEMINI-E3, and TIAM). Results prove the potentials of the proposed framework to reduce the model variance and present a powerful diagnostic tool to feedback on the quality of the harmonisation itself

A novel and integrated architecture for identification and cancellation of noise from GSM signal

There are multiple reasons for the evolution as well as the presence of noise over transmitted GSM signal. In spite of various approaches towards noise cancellation techniques, there are less applicable techniques for controlling noise in acoustic GSM signal. Therefore, the proposed manuscript presents an integrated modelling which performs modelling of noise identification that could significantly assist in successful noise cancellation. The proposed system uses three different approach viz. i) stochastic based approach for noise modelling, ii) analytical-based approach where allocated power acts as one of the prominent factors of noise, and iii) wavelet-based approach for effective decomposition of GSM signal for assisting better noise cancellation technique followed by better retention of signal quality. Simulated in MATLAB, the study outcome shows that it offers a cost-effective implementation, A Practical Approach for Noise identification, and Effective Noise Cancellation with Signal quality retention. The proposed system offers approximately 24% of enhancement in noise reduction as compared to any existing digital filters with 1.6 seconds faster in processing speed

Multivariate adaptive regression splines for estimating riverine constituent concentrations

Regression-based methods are commonly used for riverine constituent concentration/flux estimation, which is essential for guiding water quality protection practices and environmental decision making. This paper developed a multivariate adaptive regression splines model for estimating riverine constituent concentrations (MARS-EC). The process, interpretability and flexibility of the MARS-EC modelling approach, was demonstrated for total nitrogen in the Patuxent River, a major river input to Chesapeake Bay. Model accuracy and uncertainty of the MARS-EC approach was further analysed using nitrate plus nitrite datasets from eight tributary rivers to Chesapeake Bay. Results showed that the MARS-EC approach integrated the advantages of both parametric and nonparametric regression methods, and model accuracy was demonstrated to be superior to the traditionally used ESTIMATOR model. MARS-EC is flexible and allows consideration of auxiliary variables; the variables and interactions can be selected automatically. MARS-EC does not constrain concentration-predictor curves to be constant but rather is able to identify shifts in these curves from mathematical expressions and visual graphics. The MARS-EC approach provides an effective and complementary tool along with existing approaches for estimating riverine constituent concentrations

The unified enterprise modelling language – Overview and further Work

ISBN 978-1-1234-7890-2/08International audienceThe Unified Enterprise Modelling Language (UEML) aims to support integrated use of enterprise and IS models expressed in a variety of languages. The achieve this aim, UEML provides a hub through which different languages can be connected, thereby paving the way for connecting the models expressed in those languages. UEML offers a structured approach to describing enterprise and IS modelling constructs, a common ontology to interrelate construct descriptions at the semantic level, a correspondence analysis approach to estimate semantic construct similarity, a quality framework to aid selection of languages, a meta-meta model to organise the UEML and a set of tools to aid its use. This paper presents an overview of UEML and points to paths for further work