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Mind the gap: Information gaps and bridging options in assessing in-situ conservation achievements
(2008)
The biodiversity crisis has gained political attention on a global level. The “2010 Target” of the Convention on Biological Diversity (CBD) aims to significantly reduce the loss of biodiversity by 2010. In order to achieve this, a network of representative and effectively managed protected areas is to be established. The effectiveness of protected areas thus represents one indicator for progress towards the CBD’s 2010 Target. However, indicators require information. The present study, in a first step, reviews the availability of open access long-term ecological data for assessing protected area effectiveness. This review shows two parallel – though contradictory – phenomena: data overkill and data scarcity. While the number of online databases providing open access data on biodiversity has grown tremendously, no long-term ecological data for a larger set of protected areas can be openly accessed. Reasons for this data scarcity are discussed. Based on this lack of information, in a second step, a method to bridge information gaps through social science research is aspired. An innovative Conservation Success Framework is developed, which defines and relates conservation needs, conservation capacity and conservation actions, its three main components. The basic assumption is that conservation can only be successful where the conservation capacity exists that is required to implement the conservation actions determined by the conservation needs. The framework was used to develop open and closed questionnaires for application in two Mexican biosphere reserves, the Sierra Gorda and the Sierra de Manantlán. As "conservation success" is often immeasurable in protected areas in practice due to unspecific conservation objectives the term is for the case studies substituted by “conservation achievements”, i.e. clearly noticeable effects from conservation actions. Overall, almost 60 interviews were conducted with different stakeholder groups. The gained information is validated through social science research techniques, such as triangulation of perspectives and active and passive observation. Based on this, conservation needs are identified and conservation capacities summarised and discussed for both case study sites. Implemented conservation actions addressing identified conservation needs and conservation capacity constraints are then analysed. In addition, noticeable effects from conservation actions on the state of biodiversity at case study sites, i.e. the conservation achievements, are described. Where locally available, non-open access data (as opposing open access data) are used to verify the findings from the social science research. Identified conservation achievements at both case study sites are evident both from quantitative information (for example forest cover increase according to non-open access data) and qualitative information (for example perceived change in the occurrence of illegal activities according to interviews). In addition, rather “intangible” indicators that can only be revealed through qualitative surveys are identified for both sites. This study thus highlights the crucial importance of integrating different types of data, ecological and socio-economic, as well as quantitative and qualitative ones. The present study concludes with a series of recommendations 1) to local practitioners at the two case study sites, and 2) to the international conservation community. Local practitioners may benefit from the present study because its results provide for each site a) an overview of existing conservation needs and implemented conservation actions; b) an easy way to identify action gaps; c) a baseline to identify progress indicators; and d) an overview of diverse perspectives on the current effectiveness of the biosphere reserves. These benefits are considered of particular importance as they can be influential in the revision of the site’s management plans, which both are now approximately ten years old and will soon be revised. The international conservation community will not be able to make a clear statement in the year 2010 about the effectiveness of protected areas on a global level due to a lack of information and transparency. However, the year 2010 should not be considered an end point for measuring progress in in-situ conservation; instead protected area quality standards must be created, effectiveness evaluations institutionalised and efforts to foster regular reporting must continue. Consequently, a scheme of consolidated actions from local to national and international level is proposed that could help to sustainably bridge existing information gaps and close them on the long run. In the end, progress reporting on the effectiveness of protected areas, and other indicators, can only improve if different governance levels “mind the information gaps” in cooperation, until continued information gathering and sharing hopefully closes these gaps one day.
Objectives: Several clinical disease activity indices (DAIs) have been developed to noninvasively assess mucosal healing in pediatric Crohn’s disease (CD). However, their clinical application can be complex. Therefore, we present a new way to identify the most informative biomarkers for mucosal inflammation from current markers in use and, based on this, how to obtain an easy-to-use DAI for clinical practice. A further aim of our proof-of-concept study is to demonstrate how the performance of such a new DAI can be compared to that of existing DAIs.
Methods: The data of two independent study cohorts, with 167 visits from 109 children and adolescents with CD, were evaluated retrospectively. A variable selection based on a Bayesian ordinal regression model was applied to select clinical or standard laboratory parameters as predictors, using an endoscopic outcome. The predictive performance of the resulting model was compared to that of existing pediatric DAIs.
Results: With our proof-of-concept dataset, the resulting model included C-reactive protein (CRP) and fecal calprotectin (FC) as predictors. In general, our model performed better than the existing DAIs. To show how our Bayesian approach can be applied in practice, we developed a web application for predicting disease activity for a new CD patient or visit.
Conclusions: Our work serves as a proof-of-concept, showing that the statistical methods used here can identify biomarkers relevant for the prediction of a clinical outcome. In our case, a small number of biomarkers is sufficient, which, together with the web interface, facilitates the clinical application. However, the retrospective nature of our study, the rather small amount of data, and the lack of an external validation cohort do not allow us to consider our results as the establishment of a novel DAI for pediatric CD. This needs to be done with the help of a prospective study with more data and an external validation cohort in the future.
Background: Clinical practice guidelines are systematically developed statements intended to optimize patient care. However, a gapless implementation of guideline recommendations requires health care personnel not only to be aware of the recommendations and to support their content but also to recognize every situation in which they are applicable. To not miss situations in which recommendations should be applied, computerized clinical decision support can be provided through a system that allows an automated monitoring of adherence to clinical guideline recommendations in individual patients.
Objective: This study aims to collect and analyze the requirements for a system that allows the monitoring of adherence to evidence-based clinical guideline recommendations in individual patients and, based on these requirements, to design and implement a software prototype that integrates guideline recommendations with individual patient data, and to demonstrate the prototype’s utility in treatment recommendations.
Methods: We performed a work process analysis with experienced intensive care clinicians to develop a conceptual model of how to support guideline adherence monitoring in clinical routine and identified which steps in the model could be supported electronically. We then identified the core requirements of a software system to support recommendation adherence monitoring in a consensus-based requirements analysis within the loosely structured focus group work of key stakeholders (clinicians, guideline developers, health data engineers, and software developers). On the basis of these requirements, we designed and implemented a modular system architecture. To demonstrate its utility, we applied the prototype to monitor adherence to a COVID-19 treatment recommendation using clinical data from a large European university hospital.
Results: We designed a system that integrates guideline recommendations with real-time clinical data to evaluate individual guideline recommendation adherence and developed a functional prototype. The needs analysis with clinical staff resulted in a flowchart describing the work process of how adherence to recommendations should be monitored. Four core requirements were identified: the ability to decide whether a recommendation is applicable and implemented for a specific patient, the ability to integrate clinical data from different data formats and data structures, the ability to display raw patient data, and the use of a Fast Healthcare Interoperability Resources–based format for the representation of clinical practice guidelines to provide an interoperable, standards-based guideline recommendation exchange format.
Conclusions: Our system has advantages in terms of individual patient treatment and quality management in hospitals. However, further studies are needed to measure its impact on patient outcomes and evaluate its resource effectiveness in different clinical settings. We specified a modular software architecture that allows experts from different fields to work independently and focus on their area of expertise. We have released the source code of our system under an open-source license and invite for collaborative further development of the system.