Project description:CONTEXT:Relationships between researchers and decision-makers have demonstrated positive potential to influence research, policy and practice. Over time, interest in better understanding the relationships between the two parties has grown as demonstrated by a plethora of studies globally. However, what remains elusive is the evolution of these vital relationships and what can be learned from them with respect to advancing evidence-informed decision-making. We therefore explored the nuances around the initiation, maintenance and dissolution of academic-government relationships. METHODS:We conducted in-depth interviews with 52 faculty at one school of public health and 24 government decision-makers at city, state, federal and global levels. Interviews were transcribed and coded deductively and inductively using Atlas.Ti. Responses across codes and respondents were extracted into an Excel matrix and compared in order to identify key themes. FINDINGS:Eight key drivers to engagement were identified, namely (1) decision-maker research needs, (2) learning, (3) access to resources, (4) student opportunities, (5) capacity strengthening, (6) strategic positioning, (7) institutional conditionalities, and (8) funder conditionalities. There were several elements that enabled initiation of relationships, including the role of faculty members in the decision-making process, individual attributes and reputation, institutional reputation, social capital, and the role of funders. Maintenance of partnerships was dependent on factors such as synergistic collaboration (i.e. both benefit), mutual trust, contractual issues and funding. Dissolution of relationships resulted from champions changing/leaving positions, engagement in transactional relationships, or limited mutual trust and respect. CONCLUSIONS:As universities and government agencies establish relationships and utilise opportunities to share ideas, envision change together, and leverage their collaborations to use evidence to inform decision-making, a new modus operandi becomes possible. Embracing the individual, institutional, networked and systems dynamics of relationships can lead to new practices, alternate approaches and transformative change. Government agencies, schools of public health and higher education institutions more broadly, should pay deliberate attention to identifying and managing the various drivers, enablers and disablers for relationship initiation and resilience in order to promote more evidence-informed decision-making.

Project description:In densely populated areas, surface waters are affected by many sources of pollution. Besides classical pollutants like nutrients and organic matter that lead to eutrophication, micropollutants from various point- and non-point sources are getting more attention by water quality managers. For cost-effective management an integrated assessment is needed that takes into account all relevant pollutants and all sources of pollution within a catchment. Due to the difficulty of identifying and quantifying sources of pollution and the need for considering long-term changes in boundary conditions, typically substantial uncertainty exists about the consequences of potential management alternatives to improve surface water quality. We therefore need integrated assessment methods that are able to deal with multiple objectives and account for various sources of uncertainty. This paper aims to contribute to integrated, prospective water management by combining a) multi-criteria decision support methods to structure the decision process and quantify preferences, b) integrated water quality modelling to predict consequences of management alternatives accounting for uncertainty, and c) scenario planning to consider uncertainty from potential future climate and socio-economic developments, to evaluate the future cost-effectiveness of water quality management alternatives at the catchment scale. It aims to demonstrate the usefulness of multi-attribute value functions for water quality assessment to i) propagate uncertainties throughout the entire assessment procedure, ii) facilitate the aggregation of multiple objectives while avoiding discretization errors when using categories for sub-objectives, iii) transparently communicate the results. We show how to use such multi-attribute value functions for model-based decision support in water quality management. We showcase the procedure for the Mönchaltorfer Aa catchment on the Swiss Plateau. We evaluate ten different water quality management alternatives, including current practice, that tackle macro- and micropollutants from a wide spectrum of agricultural and urban sources. We evaluate costs and water quality effects of the alternatives under four different socio-economic scenarios for the horizon 2050 under present and future climate projections and visualize their uncertainty. While the performance of alternatives is catchment specific, the methods can be transferred to other places and other management situations. Results confirm the need for cross-sectoral coordination of different management actions and interdisciplinary collaboration to support the development of prospective strategies to improve water quality.

Project description:BACKGROUND:Knowledge of what the pharmaceutical industry emphasizes when assessing trial sites during site selection is sparse. A better understanding of this issue can improve the collaboration on clinical trials and increase knowledge of how to attract and retain industry-sponsored trials. Accordingly, we investigated which site-related qualities multinational biopharmaceutical companies and clinical research organizations (CROs) find most important during site selection. METHODS:An online survey among decision-makers for trial site selection in the Nordic countries employed at multinational biopharmaceutical companies and CROs was conducted. The respondents' experiences with and perceptions of site selection were addressed to evaluate the relative importance of site-related qualities. We included up to four respondents per company, representing different geographic regions. Descriptive statistics were used to summarize findings. RESULTS:Of 49 eligible companies, 20 biopharmaceutical companies and 23 CROs participated. In total, 83 responses were analyzed (estimated response rate 78%). A relative importance of site-related qualities was identified: For example, 88% (binomial 95% confidence interval [CI] ±7%) preferred reaching enrollment goals at trial sites in their region 10% quicker rather than cutting the costs at all sites by 20%. Likewise, 42% (CI ±11%) of the respondents preferred that trial sites were best at having the first patients ready for inclusion right after site initiation visit compared to having good data entry, documentation, and reporting practice (25% [CI ±9%]), easily reachable site personnel and backup (23% [CI ±9%]), fast contractual procedure times (6% [CI ±5%]), a key opinion leader associated with the site (3% [CI ±4%]), and updated equipment and facilities (1% [CI ±2%]). In total, 75% [CI ±9%] agreed that their company would be interested in cooperating with an inexperienced trial site if the site had access to a large patient population and 52% [CI ±11%] had experienced that their company selected an inexperienced trial site in favor of an experienced site due to a higher level of interest and commitment. CONCLUSIONS:This study indicates that recruitment-related factors are pivotal to the pharmaceutical industry when assessing trial sites during site selection. Data quality-related factors seem highly valued especially in early phase trials whereas costs and investigator's publication track record are less important. Experience in conducting clinical trials is not imperative. However, this applies primarily to late phase trials.

Project description:BackgroundTraditionally, the economic value of health technologies is assessed with cost-effectiveness (CE) and budget impact (BI) analyses. However, the evaluation of rare disease therapies often considers novel value criteria. Multi-criteria decision analysis (MCDA) is a promising tool in the assessment of value criteria that typically cannot be captured with traditional approaches.ObjectivesThe objective of this research was to investigate the criteria and scoring functions applied in value frameworks and MCDA tools relevant to the evaluation of rare disease therapies. The aim was to gain a better understanding of the domains and measurement of commonly referenced novel value criteria.MethodsA systematic literature review was performed covering the period from 2013 to 2019. MCDA or value framework articles and structured review papers on orphan-drug-specific MCDA articles were reviewed. Information sources included MEDLINE, Embase, Scopus, and 26 other gray literature sources. A descriptive review of identified criteria and scoring functions was performed, with special focus on "novel" value criteria that are traditionally not considered in CE or BI analyses.ResultsIn total, 15 relevant value frameworks and MCDA tools were identified. These studies included a large number (n = 56) of individual value criteria. The most commonly included novel criteria were unmet medical need, severity of disease, and reduction in uncertainty. The identified scoring functions (measurement methods) for novel criteria were highly heterogeneous and tailored. Standardized scoring functions were not observed. Additionally, the studies did not provide their rationale for choosing a specific scoring function for a criterion.ConclusionsMCDA is a promising tool to include novel value criteria into the health technology assessment of therapies for rare diseases. To support the development of a transparent and justified evaluation process, scoring functions should be further investigated.

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The criteria used by key decision makers in Australia to judge the academic quality of NTROs

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