Biodiversity is declining globally due to mounting anthropogenic threats. Actions to protect biodiversity against threats can be costly, involving land purchase, invasive species management, and inflicting opportunity costs of lost revenue and livelihoods in conservation areas. Governments and conservation organisations are under increasing pressure to deliver the greatest benefits from conservation funds, and to minimise conflicts between conservation and other human priorities. Most conservation planning approaches are limited in their ability to assist with cost-effective funding allocation decisions. First, approaches often lack quantifiable objectives and appropriate tools. Second, approaches rarely consider economic information, such as spatially explicit data on the costs of conservation actions. In this thesis I address these two limitations, which often co-occur, in spatial conservation planning. Problem definition includes specifying a quantifiable objective, a set of constraints and control variables, and knowledge of the system. A simple conservation objective is to protect target amounts of biodiversity features, such as 15% of the range of each species and vegetation type, over a minimal total reserve area. Here, targets are the constraints and the control variables are the decisions of whether or not to conserve each site. Target-based conservation planning is the dominant spatial prioritisation approach, but has been criticised for failing to protect untargeted portions of biodiversity and for employing targets too low to ensure species persistence. In Chapter 2, I review target-based systematic conservation planning, discovering that many perceived limitations can be overcome with current developments in research and software and better communication, whilst acknowledging the value of alternative approaches. Conservation planning objectives are becoming increasingly complex due to the need to conserve many kinds of features, such as species, habitat types, and ecosystem services. Measures of the spatial congruence between features is often used to determine if one feature is a good surrogate for representing another and whether multiple features can be easily captured in a single plan. In Chapter 3 I review the use of congruence metrics in conservation planning research, explaining the differences between the three most common metrics – spatial correlation, hotspot overlap, incidental representation – and demonstrating why high values in one metric can coincide with low values in another. Most importantly, I show that integrated systematic conservation planning, rather than congruence metrics, is the only way to determine how efficient it will be to protect multiple features in a reserve system. While conservation planning has an implicit goal of cost-efficiency, spatially explicit data on the costs of conservation action are rarely considered. Prioritisation analyses that do not consider conservation costs can lead to the misallocation of funds and high opportunity costs. In Chapter 4 I carry out a global analysis at 1º resolution to identify areas that could protect targets of 10% of every mammal species’ range whilst minimising the opportunity costs of forgone agricultural production. The a priori inclusion of opportunity costs reduced the cost of meeting conservation targets by at least 30%. I then compare cost-effective allocation of funds to actual funding allocation by international conservation agencies in 2006, highlighting globally important, threatened and under-funded regions. While estimates of conservation opportunity costs can increase conservation planning efficiency, there are often various actions under consideration, each with different associated costs. The definition of specific actions, and their respective costs, is rarely considered in conservation planning. In Chapter 5 I develop cost surfaces for two conservation actions in Australia (i) land purchase for reservation estimated by unimproved land values and (ii) stewardship payments to private landholders to conserve biodiversity estimated by forgone agricultural production. I then identify priority areas at a 10 km2 resolution for conserving 15% of the pre-clearing extent of a range of biodiversity features by these actions. I demonstrate that using cost data to reflect specific conservation actions minimises improves financial efficiency by up to two-fold. Cost-effective conservation planning is also hindered by uncertainties in estimates of conservation costs. In Chapter 6 I carry out the first comprehensive sensitivity analysis of conservation priorities to cost value, using the same goal as in Chapter 5, but restricting planning to reservation in Queensland, which is the Australian state with the best quality unimproved land value data. First, I show that sites which are essential or unhelpful for meeting conservation targets maintain a high and low priority status respectively, over a large range of cost data (1-400% of their estimated cost). Medium priority sites are sensitive to estimates of cost, and represent the greatest opportunities to make cost-effective decisions. Next I develop a simple approach for planning with uncertain cost data, where priorities can be updated as real information on the cost of a parcel of land becomes available. This chapter shows that uncertain cost data is useful for conservation planning. Potentially cost-effective areas for conservation actions in Australia are identified in Chapters 5 and 6. My final chapter serves to synthesise and interpret this research. Through comprehensive analyses, I have shown that cost-effective conservation planning requires the definition of appropriate objectives and tools, and the integration of conservation costs. Further, I have demonstrated accessible approaches that integrate these crucial factors, showing at least a doubling of efficiency in conservation investments. There are cost-effective opportunities for conservation actions in Australia and around the world: this research will assist Governments, Non-Government Organisations, and other conservation-minded people in finding them. Further investment is required in obtaining and wisely applying socio-economic data for conservation planning and in evaluating conservation projects to improve our knowledge base.

Biodiversity is declining globally due to mounting anthropogenic threats. Actions to protect biodiversity against threats can be costly, involving land purchase, invasive species management, and inflicting opportunity costs of lost revenue and livelihoods in conservation areas. Governments and conservation organisations are under increasing pressure to deliver the greatest benefits from conservation funds, and to minimise conflicts between conservation and other human priorities. Most conservation planning approaches are limited in their ability to assist with cost-effective funding allocation decisions. First, approaches often lack quantifiable objectives and appropriate tools. Second, approaches rarely consider economic information, such as spatially explicit data on the costs of conservation actions. In this thesis I address these two limitations, which often co-occur, in spatial conservation planning. Problem definition includes specifying a quantifiable objective, a set of constraints and control variables, and knowledge of the system. A simple conservation objective is to protect target amounts of biodiversity features, such as 15% of the range of each species and vegetation type, over a minimal total reserve area. Here, targets are the constraints and the control variables are the decisions of whether or not to conserve each site. Target-based conservation planning is the dominant spatial prioritisation approach, but has been criticised for failing to protect untargeted portions of biodiversity and for employing targets too low to ensure species persistence. In Chapter 2, I review target-based systematic conservation planning, discovering that many perceived limitations can be overcome with current developments in research and software and better communication, whilst acknowledging the value of alternative approaches. Conservation planning objectives are becoming increasingly complex due to the need to conserve many kinds of features, such as species, habitat types, and ecosystem services. Measures of the spatial congruence between features is often used to determine if one feature is a good surrogate for representing another and whether multiple features can be easily captured in a single plan. In Chapter 3 I review the use of congruence metrics in conservation planning research, explaining the differences between the three most common metrics – spatial correlation, hotspot overlap, incidental representation – and demonstrating why high values in one metric can coincide with low values in another. Most importantly, I show that integrated systematic conservation planning, rather than congruence metrics, is the only way to determine how efficient it will be to protect multiple features in a reserve system. While conservation planning has an implicit goal of cost-efficiency, spatially explicit data on the costs of conservation action are rarely considered. Prioritisation analyses that do not consider conservation costs can lead to the misallocation of funds and high opportunity costs. In Chapter 4 I carry out a global analysis at 1º resolution to identify areas that could protect targets of 10% of every mammal species’ range whilst minimising the opportunity costs of forgone agricultural production. The a priori inclusion of opportunity costs reduced the cost of meeting conservation targets by at least 30%. I then compare cost-effective allocation of funds to actual funding allocation by international conservation agencies in 2006, highlighting globally important, threatened and under-funded regions. While estimates of conservation opportunity costs can increase conservation planning efficiency, there are often various actions under consideration, each with different associated costs. The definition of specific actions, and their respective costs, is rarely considered in conservation planning. In Chapter 5 I develop cost surfaces for two conservation actions in Australia (i) land purchase for reservation estimated by unimproved land values and (ii) stewardship payments to private landholders to conserve biodiversity estimated by forgone agricultural production. I then identify priority areas at a 10 km2 resolution for conserving 15% of the pre-clearing extent of a range of biodiversity features by these actions. I demonstrate that using cost data to reflect specific conservation actions minimises improves financial efficiency by up to two-fold. Cost-effective conservation planning is also hindered by uncertainties in estimates of conservation costs. In Chapter 6 I carry out the first comprehensive sensitivity analysis of conservation priorities to cost value, using the same goal as in Chapter 5, but restricting planning to reservation in Queensland, which is the Australian state with the best quality unimproved land value data. First, I show that sites which are essential or unhelpful for meeting conservation targets maintain a high and low priority status respectively, over a large range of cost data (1-400% of their estimated cost). Medium priority sites are sensitive to estimates of cost, and represent the greatest opportunities to make cost-effective decisions. Next I develop a simple approach for planning with uncertain cost data, where priorities can be updated as real information on the cost of a parcel of land becomes available. This chapter shows that uncertain cost data is useful for conservation planning. Potentially cost-effective areas for conservation actions in Australia are identified in Chapters 5 and 6. My final chapter serves to synthesise and interpret this research. Through comprehensive analyses, I have shown that cost-effective conservation planning requires the definition of appropriate objectives and tools, and the integration of conservation costs. Further, I have demonstrated accessible approaches that integrate these crucial factors, showing at least a doubling of efficiency in conservation investments. There are cost-effective opportunities for conservation actions in Australia and around the world: this research will assist Governments, Non-Government Organisations, and other conservation-minded people in finding them. Further investment is required in obtaining and wisely applying socio-economic data for conservation planning and in evaluating conservation projects to improve our knowledge base.

Biodiversity is declining globally due to mounting anthropogenic threats. Actions to protect biodiversity against threats can be costly, involving land purchase, invasive species management, and inflicting opportunity costs of lost revenue and livelihoods in conservation areas. Governments and conservation organisations are under increasing pressure to deliver the greatest benefits from conservation funds, and to minimise conflicts between conservation and other human priorities. Most conservation planning approaches are limited in their ability to assist with cost-effective funding allocation decisions. First, approaches often lack quantifiable objectives and appropriate tools. Second, approaches rarely consider economic information, such as spatially explicit data on the costs of conservation actions. In this thesis I address these two limitations, which often co-occur, in spatial conservation planning. Problem definition includes specifying a quantifiable objective, a set of constraints and control variables, and knowledge of the system. A simple conservation objective is to protect target amounts of biodiversity features, such as 15% of the range of each species and vegetation type, over a minimal total reserve area. Here, targets are the constraints and the control variables are the decisions of whether or not to conserve each site. Target-based conservation planning is the dominant spatial prioritisation approach, but has been criticised for failing to protect untargeted portions of biodiversity and for employing targets too low to ensure species persistence. In Chapter 2, I review target-based systematic conservation planning, discovering that many perceived limitations can be overcome with current developments in research and software and better communication, whilst acknowledging the value of alternative approaches. Conservation planning objectives are becoming increasingly complex due to the need to conserve many kinds of features, such as species, habitat types, and ecosystem services. Measures of the spatial congruence between features is often used to determine if one feature is a good surrogate for representing another and whether multiple features can be easily captured in a single plan. In Chapter 3 I review the use of congruence metrics in conservation planning research, explaining the differences between the three most common metrics – spatial correlation, hotspot overlap, incidental representation – and demonstrating why high values in one metric can coincide with low values in another. Most importantly, I show that integrated systematic conservation planning, rather than congruence metrics, is the only way to determine how efficient it will be to protect multiple features in a reserve system. While conservation planning has an implicit goal of cost-efficiency, spatially explicit data on the costs of conservation action are rarely considered. Prioritisation analyses that do not consider conservation costs can lead to the misallocation of funds and high opportunity costs. In Chapter 4 I carry out a global analysis at 1º resolution to identify areas that could protect targets of 10% of every mammal species’ range whilst minimising the opportunity costs of forgone agricultural production. The a priori inclusion of opportunity costs reduced the cost of meeting conservation targets by at least 30%. I then compare cost-effective allocation of funds to actual funding allocation by international conservation agencies in 2006, highlighting globally important, threatened and under-funded regions. While estimates of conservation opportunity costs can increase conservation planning efficiency, there are often various actions under consideration, each with different associated costs. The definition of specific actions, and their respective costs, is rarely considered in conservation planning. In Chapter 5 I develop cost surfaces for two conservation actions in Australia (i) land purchase for reservation estimated by unimproved land values and (ii) stewardship payments to private landholders to conserve biodiversity estimated by forgone agricultural production. I then identify priority areas at a 10 km2 resolution for conserving 15% of the pre-clearing extent of a range of biodiversity features by these actions. I demonstrate that using cost data to reflect specific conservation actions minimises improves financial efficiency by up to two-fold. Cost-effective conservation planning is also hindered by uncertainties in estimates of conservation costs. In Chapter 6 I carry out the first comprehensive sensitivity analysis of conservation priorities to cost value, using the same goal as in Chapter 5, but restricting planning to reservation in Queensland, which is the Australian state with the best quality unimproved land value data. First, I show that sites which are essential or unhelpful for meeting conservation targets maintain a high and low priority status respectively, over a large range of cost data (1-400% of their estimated cost). Medium priority sites are sensitive to estimates of cost, and represent the greatest opportunities to make cost-effective decisions. Next I develop a simple approach for planning with uncertain cost data, where priorities can be updated as real information on the cost of a parcel of land becomes available. This chapter shows that uncertain cost data is useful for conservation planning. Potentially cost-effective areas for conservation actions in Australia are identified in Chapters 5 and 6. My final chapter serves to synthesise and interpret this research. Through comprehensive analyses, I have shown that cost-effective conservation planning requires the definition of appropriate objectives and tools, and the integration of conservation costs. Further, I have demonstrated accessible approaches that integrate these crucial factors, showing at least a doubling of efficiency in conservation investments. There are cost-effective opportunities for conservation actions in Australia and around the world: this research will assist Governments, Non-Government Organisations, and other conservation-minded people in finding them. Further investment is required in obtaining and wisely applying socio-economic data for conservation planning and in evaluating conservation projects to improve our knowledge base.

In times of tightening national budgets as a result of structural adjustment requirements, the need to make choices in Zimbabwe's publicly funded research is heightened. Adoption of quantitative priority setting methods help improve the objectivity of decision-making while fostering consistency of research priorities with the attainment of research system objectives This study develops and applies a quantitative methodology for agricultural research priority setting for Zimbabwe's Department of Research and Specialist Services (DR&SS) under multiple objectives. Such a methodology must incorporate the structural characteristics of Zimbabwe's agricultural sector: the existence of different farmer types, five different agro-ecological regions and multiple objectives. A three part procedure was used in this study to prioritize agricultural research in Zimbabwe. The first part involved identifying the research objectives, defining the list of commodity and non-commodity programs to be prioritized, defining the agro-ecological zones and collecting technology related data and published information. Researchers, extension workers, and farmer representatives were interviewed using a questionnaire to obtain technology-related data. The second part involved economic analysis to measure the contributions of agricultural research to total economic benefits and their distribution by farmer type and agro-ecological region. Net present values (NPV) of economic surplus gains by research program were used to summarize the total economic efficiency gains projected over fifteen years. Once the benefits have been estimated, the third part of the procedure involved using mathematical programming (MP) to project the optimal allocation of research resources among the various commodities under alternative weights on objectives. A ranking of the expected NPVs indicated that agricultural research priorities are different between smallholder farmers and large scale commercial farmers, with maize cotton, groundnuts, sunflower, goats, pulses and millets being of high priority for smallholder farmers, while maize, beef, cotton, coffee, wheat, dairy, stonefruit, soybeans and roses were top priority for large scale commercial farmers. Research discipline priorities for smallholder farmers include agronomy, plant breeding and chemistry and soils while for large-scale commercial farmers the priorities are plant breeding, agronomy, and plant protection. Optimal allocation of research resources given two objectives (efficiency and equity) were assessed in a series of runs with the mathematical programming model. The tradeoff costs associated with putting an extra weight of different sizes on the equity objective, given the current total budget constraint were relatively modest implying that DR&SS can allocate resources to research on smallholder farming without great loss in efficiency. / Ph. D.

Yes / Obesity research priority setting, if conducted to a high standard, can help promote policy-relevant and efficient research. Therefore, there is a need to identify existing research priority setting studies conducted in the topic area of obesity and to determine the extent to which they followed good practice principles for research priority setting. Studies examining research priority setting in obesity were identified through searching the MEDLINE, PBSC, CINAHL, PsycINFO databases and the grey literature. The nine common themes of good practice in research priority setting were used as a methodological framework to evaluate the processes of the included studies. These were context, use of a comprehensive approach, inclusiveness, information gathering, planning for implementation, criteria, methods for deciding on priorities, evaluation and transparency. Thirteen articles reporting research prioritisation exercises conducted in different areas of obesity research were included. All studies reported engaging with various stakeholders such as policy makers, researchers and healthcare professionals. Public involvement was included in six studies. Methods of research prioritisation commonly included both Delphi and nominal group techniques and surveys. None of the 13 studies fulfilled all nine of the good practice criteria for research priority setting, with the most common limitations including not using a comprehensive approach and lack of inclusivity and evaluating on their processes. There is a need for research priority setting studies in obesity to involve the public and to evaluate their exercises to ensure they are of high quality. / National Institute for Health Research (NIHR) under its Applied Research Collaboration (ARC) Yorkshire and Humber in the form of Ph.D. funding to HI [NIHR200166], the UK Prevention Research Partnership (UKPRP) in the form of funding to JW and RM [MR/S037527/1], the NIHR Clinical Research Network in the form of funding to JW, and the NIHR ARC Yorkshire and Humber in the form of funding to RM

A growing demand for services and expensive innovative technologies is threatening the sustainability of healthcare systems worldwide. Decision makers in this environment struggle to set priorities appropriately, particularly because they lack consensus about which values should guide their decisions; this is because there is no agreement on best practices in priority setting. Decision makers (or ‘leaders’) who want to evaluate priority setting have little guidance to let them know if their efforts were successful t. While approaches exist that are grounded in different disciplines, there is no way to know whether these approaches lead to successful priority setting. The purpose of this thesis is to present a conceptual framework and an evaluation tool for successful priority setting. The conceptual framework is the result of the synthesis of three empirical studies into a framework of ten separate but interconnected elements germane to successful priority setting: stakeholder understanding, shifted priorities/reallocation of resources, decision making quality, stakeholder acceptance and satisfaction, positive externalities, stakeholder engagement, use of explicit process, information management, consideration of values and context, and revision or appeals mechanism. The elements specify both quantitative and qualitative dimensions of priority setting and relate to both process and outcome aspects. The evaluation tool is made up of three parts: a survey, interviews, and document analysis, and specifies both quantitative and qualitative dimensions and relates to both procedural and substantive dimensions of priority setting. The framework and the tool were piloted in a meso-level urban hospital. The pilot test confirmed the usability of the tool as well as face and content validity (i.e., the tool measured relevant features of success identified in the conceptual framework). The tool can be used by leaders to evaluate and improve priority setting.

In Ontario, access to publicly funded home care services is managed by Community Care Access Centres (CCACs). CCAC case managers are responsible for assessing all potential clients and prioritizing the allocation of services. The objectives of this thesis were to: 1) describe the types of decisions made by CCAC organizations and by individual case managers concerning the allocation of nursing, personal support and homemaking services to long-term adult clients with no mental health issues; and 2) to describe and assess the factors and values that influence these decisions. We conducted two case studies in which qualitative data were collected through 39 semi-structured interviews and a review of relevant documents from an urban and a rural area CCAC. A modified thematic analysis was used to identify themes related to the types of priority setting decisions and the associated factors and values. An internet-based survey was then designed based on these results and answered by 177 case managers from 8 of the 14 CCACs. The survey contained discrete choice experiments to examine the relative importance of client attributes and values to prioritization choices related to personal support and homemaking services, as well as questions that examined case managers’ attitudes towards priority setting. We found that both the rural and the urban CCACs utilized similar forms of priority setting and that case managers made the majority of these decisions during their daily interactions with clients. Numerous client, CCAC, and external factors related to the values of safety, independence and client-focused care were considered by case managers during needs assessment and service plan development. The relative importance of the selected client attributes in defining need for personal support and homemaking services was tested and found to be significantly affected by the location of the case manager (rural or urban area), years of experience in home care, and recent experience providing informal care. Case managers allocated services in the spirit of equal service for equal need and in consideration of operational efficiency. We also identified a number of case manager-related, client-related and external factors that interfered with the achievement of horizontal equity.

Priority setting for expensive biopharmaceuticals is one of the most important challenges for publicly funded health systems. One of the drivers of rising healthcare expenditures is pharmaceuticals (i.e., drugs). Moreover, people are living longer and their expectation of, and demand for, health care, drugs, and services are continually increasing. The overall aim of this research was to describe and evaluate reimbursement decisions for six expensive biopharmaceuticals across five countries in order to ascertain if the processes were legitimate and fair. I conducted qualitative case studies of six expensive biopharmaceuticals in order to describe and evaluate the priority setting activities of eight committees across five countries, including Canada, England and Wales, Australia, Israel and the United States. Data sources included: 1) 32 documents and 2) 56 interviews with informants. The recommendations process of each committee partially met the four conditions of ‘accountability for reasonableness’. My main finding is that, while a number of values were considered by committees when making reimbursement decisions, committees tended to focus on values of evidence, effectiveness and efficiency, but not the full range of relevant values. Thus, these contexts did not fully meet the conditions of legitimacy and fairness. I have provided an in-depth description of the eight committees’ priority setting activities regarding the study drugs, as well as committee members’, patients’ and industry representatives’ views regarding the process. I developed practical guidance for leaders for improving reimbursement decisions for expensive biopharmaceuticals, the implementation of which would enhance the fairness and legitimacy of priority setting. This study has demonstrated that in order to create a fair and legitimate drug reimbursement process, we need to ensure the incorporation of a wide range of values, and the involvement of multiple stakeholder groups within the deliberative and appeals/revisions processes.

Research Question: This research adapted, tested, and evaluated a methodology to set priorities for systematic reviews topics within the Cochrane Collaboration that is sustainable and incorporates the social determinants of health and health equity into the analysis. Background: In 2008 a study was conducted to review, evaluate and compare the methods for prioritization used across the Cochrane Collaboration. Two key findings from that study were: 1) the methods were not sustainable and 2) health equity represented a gap in the process. To address these key findings, the objective of this research was to produce and test a method that is sustainable and incorporates the social determinants of health and health equity into the decision making process. As part of this research, the methods were evaluated to determine the level of success. Methodology: With assistance from experts in the field, a comparative analysis of existing priority setting methods was conducted. The Global Evidence Mapping (GEM) method was selected to be adapted to meet our research objectives. The adapted method was tested with assistance of the Cochrane Musculoskeletal Group in identifying priorities for Osteoarthritis. The results of the process and the outcomes were evaluated by applying the “Framework for Successful Priority Setting”. Results: This research found that the priority setting method developed is sustainable. Also, the methods succeeded in incorporating the social determinants of health and health equity into the analysis. A key strength of the study was the ability to incorporate the patients’ perspective in setting priorities for review topics. The lack of involvement of disadvantaged groups of the population was identified as a key limitation. Recommendations were put forward to incorporate the strengths of the study into future priority setting exercises within Cochrane and to address the limitations.

Research Question: This research adapted, tested, and evaluated a methodology to set priorities for systematic reviews topics within the Cochrane Collaboration that is sustainable and incorporates the social determinants of health and health equity into the analysis. Background: In 2008 a study was conducted to review, evaluate and compare the methods for prioritization used across the Cochrane Collaboration. Two key findings from that study were: 1) the methods were not sustainable and 2) health equity represented a gap in the process. To address these key findings, the objective of this research was to produce and test a method that is sustainable and incorporates the social determinants of health and health equity into the decision making process. As part of this research, the methods were evaluated to determine the level of success. Methodology: With assistance from experts in the field, a comparative analysis of existing priority setting methods was conducted. The Global Evidence Mapping (GEM) method was selected to be adapted to meet our research objectives. The adapted method was tested with assistance of the Cochrane Musculoskeletal Group in identifying priorities for Osteoarthritis. The results of the process and the outcomes were evaluated by applying the “Framework for Successful Priority Setting”. Results: This research found that the priority setting method developed is sustainable. Also, the methods succeeded in incorporating the social determinants of health and health equity into the analysis. A key strength of the study was the ability to incorporate the patients’ perspective in setting priorities for review topics. The lack of involvement of disadvantaged groups of the population was identified as a key limitation. Recommendations were put forward to incorporate the strengths of the study into future priority setting exercises within Cochrane and to address the limitations.