Management Strategy Evaluation Research Articles

The Evaluation of Drug Management and Improvement Strategies Using the Hanlon Method in the Pharmacy Installation of the Bahteramas Hospital Southeast Sulawesi

Drug management is a drug management cycle which includes these stages as follows: selection, procurement, distribution and use. Ineffectiveness and inefficiency may negatively impact hospitals both medically and economically. This study aims to evaluate drug management in the selection, procurement, distribution and use of drugs at the Bahteramas Hospital, Southeast Sulawesi,
 with Hanlon method as strategic improvement. This study has done with a descriptive method with data collected retrospectively in 2022 and prospectively, both primary (management record) and secondary (interviews). Results of this study about drug management showed there were 4 indicators that do not comply with standards. Meanwhile, other 10 indicators could comply with the standards. The improvement strategy using the Hanlon method in drug management is to prioritize repairing problems sequentially starting from the average percentage of drug waiting time, suitability of the national formulary and hospital formulary, as well as the percentage of dead stock.

Range-wide contrast in management outcomes for transboundary Northeast Pacific sablefish

Sablefish ( Anoplopoma fimbria) of the Northeast Pacific support a highly mobile, valuable fishery resource currently managed as three separate populations. Recent work has shown sablefish to be genetically mixed; have high movement rates; and have synchronous biomass trends, including recent declines. A management strategy evaluation was developed with stakeholders and scientists from three regions to investigate whether spatially structured management paradigms might result in better conservation and economic outcomes. The management strategy evaluation includes a transboundary operating model to represent spatial population dynamics including movement and a delay–difference estimation method with varying spatial complexities and potential stratifications, and harvest control rules. Mismatches in the spatial scale of management and the underlying biological units pose a crucial risk of localized depletion in the southern U.S. West Coast. This study presents one of the first transboundary, spatially-explicit management strategy evaluations conditioned to actual data. These results underscore the importance of spatial management strategy evaluation tools and implications when regional management is conducted in isolation. Future work should incorporate additional spatial hypotheses and investigate the drivers of recruitment patterns range-wide.

Stock assessment of rock lobster stocks: Past, present and future

The aim of stock assessment is to provide managers with an understanding of the biomass and age-/size-composition of a stock, stock status (ideally relative to target and reference points), and to support management decision making, often through projections and application of harvest control rules. Stock assessments are increasingly being used to form the basis for the operating models used to evaluate the ability of management strategies to achieve the goals of fisheries management. Stock assessments for rock lobsters were among the first to adopt size-structured population models as the basis for stock assessment, and population model-based stock assessments have been used extensively to evaluate management strategies for rock lobster stocks in the USA, Australia, New Zealand and South Africa. This paper identifies how closely population model-based stock assessments for rock lobsters satisfy the guidelines identified for best practices for conducting stock assessments during meetings of, for example, the Center for the Advancement of Population Assessment Methodology and papers identifying best practice guidelines for stock assessment. The paper highlights some key directions for stock assessment science for rock lobsters, including considerations related to environmental variation and climate change.

Under pressure: an integrated assessment of human activities and their potential impact on the ecosystem components of the Southern Brazilian continental shelf

Economic activities in the South Brazilian Shelf (SBS) are concentrated on the coast, causing several impacts. To balance biodiversity and habitat conservation in coastal and marine areas with human activities relevant to society, it is important to identify and understand those sectors and pressures. We conducted an analysis to assess ecosystem risks from multiple drivers and pressures in the continental shelf that extends from the Southernmost point of Brazil (Chuí) to Cabo Frio cape, in Rio de Janeiro State. We used the Integrated Ecosystem Assessment (IEA) methodology, a framework for implementing ecosystem-based management grounded on five steps: scoping, indicator development, ecosystem assessment, risk analysis, and management strategy evaluation. This work presents the scoping step consisting of a semi-quantitative assessment identifying sector–pressure–ecological component pressure pathways. Subsequently, these pathways were scored using expert judgment supported by literature and data, regarding their level of overlap with each ecosystem component, frequency of occurrence, and degree of impact, enabling estimation of the magnitude of impact risk arising from each one of the sectors and pressures. The assessment involved 20 experts from multiple disciplines and backgrounds. To validate the results, we conducted a thorough literature review and engaged in further discussions with relevant stakeholders. As a result, 16 sectors and 19 pressures were identified as impacting 18 ecological components. Fishing, land-based industry, tourism and recreation, wastewater, and coastal infrastructure represented the main economic sectors impacting the area. The major associated pressures were the incidental catch of species, the introduction of contaminants and organic matter into the water, and the generation of waste. The most affected ecosystem components were, in turn, those located on or close to the coast, such as mangroves, saltmarshes, and rocky reefs while the preeminent impacted taxonomic groups were elasmobranchs, seabirds, reptiles, mammals, and bony fish. The literature review supported the expert assessment, and the stakeholders’ workshop endorsed our findings. Additionally, this assessment highlights the need to implement public policies that focus on reducing the impact of the most influential sectors and pressures and the necessity of strengthening research and monitoring. Identifying these priorities for integrated coastal and marine management is crucial, and our research outcomes can be key in promoting regional ocean sustainability.

Management strategy evaluation of static and dynamic harvest control rules under long-term changes in stock productivity: A case study from the SESSF

The harvest control rules (HCRs) for many fished marine populations rely on biological reference points. These reference points are often related to unfished biomass conditions (B0) and are calculated assuming that biological parameters and their associated functional forms (e.g., unfished recruitment (R0), natural mortality (M), growth) are stationary (‘static B0’). However, there is increasing evidence that the assumption of stationarity is untenable in the face of environmental change. In principle, non-stationarity can be addressed by defining stock status (i.e., spawning biomass relative to unfished spawning biomass) using ‘dynamic B0’ (the spawning biomass that would be expected in the absence of fishing). Previous work has examined the implications of adopting HCRs under the assumption that spawning biomass and hence target fishing mortalities are known exactly. However, this is an unrealistic assumption so management strategy evaluation (MSE) is used here to contrast the performance of a static B0 HCR and three variants of a dynamic B0 HCR for four stocks in Australia’s Southern and Eastern Scalefish and Shark Fishery. The MSE explores scenarios in which non-stationary is due to time-trends in M and R0, with performance measures based on static and dynamic B0, as well as total catches and catch variability. In declining productivity scenarios the use of a dynamic B0 HCR will on average maintain slightly higher catches than a static B0 HCR, but the stock biomass (in magnitude) will be less than if a static B0 HCR was adopted. Stock status then depends on the frame of reference – relative to static B0 the status will be lower than relative to an estimate of annual unfished biomass. In addition, the annual variability in catches is reduced with the dynamic B0 HCR compared to the static B0 HCR and there is a lower probability of zero Recommended Biological Catches. The preference for dynamic B0 or static B0 HCRs therefore relates to the aims of the harvest strategy to be implemented. Some harvest strategies may be focused on preserving the relative stock status through time and the management objectives do not pertain to the absolute numbers of individuals in the population, in which case a dynamic B0 HCR may meet the requirements of the harvest strategy. Other strategies may require that a population does not drop below a pre-specified absolute size, in which case an HCR that uses static B0 as the limit reference point would be preferable.

All I know – destination cognitive image latent profile analysis

Purpose Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies. Design/methodology/approach The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA). Findings The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets. Originality/value The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

Evidence from interpretable machine learning to inform spatial management of Palau's tuna fisheries

AbstractStatic and dynamic area‐based management tools hold substantial potential to balance socioeconomic benefits derived from fisheries and costs from bycatch mortality of at‐risk species. Palau longline fisheries have high bycatch of at‐risk species including the olive ridley marine turtle and silky and blue sharks. This study analyzed a two decades‐long time series of observer and electronic monitoring datasets from the Palau distant‐water and locally‐based pelagic longline fisheries. An interpretable or explainable machine learning‐based modeling approach was used to derive spatially resolved species‐specific catch rate predictions. These models were conditioned on a suite of potentially informative environmental, bathymetric, ocean‐climate metric, vessel, monitoring system, and set‐specific operational predictors. Overall, there would be limited ecological tradeoffs from focusing fishing effort within primary catch rate hotspots for target bigeye and yellowfin tunas. Mean field prediction surfaces also defined catch rate hotspots for at‐risk species of silky and blue sharks, olive ridley turtle, and pelagic stingray, which did not overlap the hotspots for target species. The predicted target species hotspots, however, overlap olive ridley and pelagic stingray warmspots. Results also identify opportunities for temporally dynamic spatial management to control catch rates of target and bycatch species. Management of fishery operational predictors of fishing depth and soak duration present additional opportunities to balance catch rates of at‐risk bycatch and target species. A transition to employing fleetwide or vessel‐based output controls that effectively constrain the fishery would alter the spatial management strategy to focus on zones with the lowest ratio of at‐risk bycatch to commercial catch. Our findings support evidence‐informed evaluation of spatial management strategies and complementary measures to meet objectives for balancing socioeconomic benefits derived from target species catch with costs to threatened species.

On the need and difficulty of evaluating management strategies improving species persistence

On the need and difficulty of evaluating management strategies improving species persistence

A retrospective analysis of 20,178 adult neurological infection admissions to United Kingdom critical care units from 2001 to 2020

BackgroundNeurological infection is an important cause of critical illness, yet little is known on the epidemiology of neurological infections requiring critical care.MethodsWe analysed data on all adults with proven or probable neurological infection admitted to UK (NHS) critical care units between 2001 and 2020 reported to the Intensive Care National Audit and Research Centre. Diagnoses, physiological variables, organ support and clinical outcomes were analysed over the whole period, and for consecutive 5-year intervals within it. Predictors of in-hospital mortality were identified using a backward stepwise regression model.ResultsWe identified 20,178 critical care admissions for neurological infection. Encephalitis was the most frequent presentation to critical care, comprising 6725 (33.3%) of 20,178 cases. Meningitis– bacterial, viral or unspecified cases - accounted for 10,056 (49.8%) of cases. In-hospital mortality was high, at 3945/19,765 (20.0%) overall. Over the four consecutive 5-year periods, there were trends towards higher Glasgow Coma Scale scores on admission, longer critical care admissions (from median 4 [IQR 2–8] to 5 days [IQR 2–10]), and reduced in-hospital mortality (from 24.9 to 18.1%). We identified 12 independent predictors of in-hospital death which when used together showed good discrimination between patients who die and those who survive (AUC = 0.79).ConclusionsAdmissions with neurological infection to UK critical care services are increasing and the mortality, although improving, remains high. To further improve outcomes from severe neurological infection, novel approaches to the evaluation of risk stratification, monitoring and management strategies are required.

Rejection sampling and agent-based models for data limited fisheries

Many of the world’s fisheries are “data-limited” where the information does not allow precise determination of fish stock status and limits the development of appropriate management responses. Two approaches are proposed for use in data-limited stock management strategy evaluations to guide the evaluations and to understand the sources of uncertainty: rejection sampling methods and the incorporation of more complex socio-economic dynamics into management evaluations using agent-based models. In rejection sampling (or rejection filtering) a model is simulated many times with a wide range of priors on parameters and outcomes are compared multiple filtering criteria. Those simulations that pass all the filters form an ensemble of feasible models. The ensemble can be used to look for robust management strategies, robust to both model uncertainties. Agent-based models of fishery economics can be implemented within the rejection framework, integrating the biological and economic understanding of the fishery. A simple artificial example of a difference equation bio-economic model is given to demonstrate the approach. Then rejection sampling is applied to an agent-based model for the hairtail (Trichiurus japonicas) fishery, where an operating model is constructed with rejection/agent-based methods and compared to known data and analyses of the fishery. The usefulness of information and rejection filters are illuminated and efficacy examined. The methods can be helpful for strategic guidance where multiple states of nature are possible as a part of management strategy evaluation.

Signatures of local adaptation to current and future climate in phenology-related genes in natural populations of Quercus robur

BackgroundLocal adaptation is a key evolutionary process that enhances the growth of plants in their native habitat compared to non-native habitats, resulting in patterns of adaptive genetic variation across the entire geographic range of the species. The study of population adaptation to local environments and predicting their response to future climate change is important because of climate change.ResultsHere, we explored the genetic diversity of candidate genes associated with bud burst in pedunculate oak individuals sampled from 6 populations in Poland. Single nucleotide polymorphism (SNP) diversity was assessed in 720 candidate genes using the sequence capture technique, yielding 18,799 SNPs. Using landscape genomic approaches, we identified 8 FST outliers and 781 unique SNPs in 389 genes associated with geography, climate, and phenotypic variables (individual/family spring and autumn phenology, family diameter at breast height (DBH), height, and survival) that are potentially involved in local adaptation. Then, using a nonlinear multivariate model, Gradient Forests, we identified vulnerable areas of the pedunculate oak distribution in Poland that are at risk from climate change.ConclusionsThe model revealed that pedunculate oak populations in the eastern part of the analyzed geographical region are the most sensitive to climate change. Our results might offer an initial evaluation of a potential management strategy for preserving the genetic diversity of pedunculate oak.

The MSC approach for developing harvest strategies and harvest control rules for Regional Fisheries Management Organisations (RFMOs)

Well-designed and robust harvest strategies are a key governance tool to achieve long term sustainability of target stocks. In some fisheries, however, such as those governed by Regional Fisheries Management Organisations (RFMOs), the development and adoption of harvest strategies can be challenging. Seafood eco-labelling programs, such as the Marine Stewardship Council (MSC), can be one way of incentivising fisheries to advocate for the adoption of harvest strategies and harvest control rules (HCRs). Here we illustrate the process through which the MSC Fisheries Standard was recently revised to guide the development and implementation of harvest strategies tested using management strategy evaluation, with particular focus on RFMOs. We identify three case studies that highlight the challenge of harvest strategy and HCR adoption: Indian Ocean skipjack tuna fisheries, Western and Central Pacific Ocean tuna fisheries, and North-East Atlantic mackerel fisheries. We discuss the problem statement that highlighted the challenges present when applying the previous MSC Fisheries Standard to stocks managed by RFMOs, and how the revised requirements within the MSC Fisheries Standard aim to overcome those challenges. These revised requirements provide an operational framework within the MSC Fisheries Standard for how RFMO-managed fisheries can implement ‘state-of-the-art' harvest strategies through management strategy evaluation. When applied by MSC certified fisheries, the new requirements are expected to contribute to delivering positive change with respect to implementing robust harvest strategies and HCRs across RFMOs, particularly in cases where there is a strong interest in the market benefits of certification.

Management strategy evaluation of harvest control rules for Pacific Herring in Prince William Sound, Alaska

Abstract Management strategy evaluation (MSE) provides a mechanism to test the relative performance of alternative management strategies on a fishery. For Pacific herring in Prince William Sound, Alaska, no directed fisheries have occurred in over 30 years, providing an opportunity to evaluate potential management strategies before a fishery is opened. Here we evaluate and compare 10 harvest control rules (HCRs) ranging from simple threshold rules to rules accounting for population age structure, biomass trends, and weight distribution using an MSE integrated with a fully Bayesian stock assessment estimation model. We developed a utility function that shows simple threshold HCRs outperform the more complex rules, especially for catch stability. According to this utility function, the best rule had a lower limit threshold than the current default rule, while the worst rule had a higher limit threshold. Our simulations demonstrate that sufficient computing power exists for MSEs based on Bayesian estimation methods, thus opening a pathway for MSEs to simulation test probabilistic control rules, which provide a buffer against scientific uncertainty and should reduce the risk of overfishing.

Development of a new control rule for managing anthropogenic removals of protected, endangered or threatened species in marine ecosystems.

Human activities in the oceans are increasing and can result in additional mortality on many marine Protected, Endangered or Threatened Species (PETS). It is necessary to implement ambitious measures that aim to restore biodiversity at all nodes of marine food webs and to manage removals resulting from anthropogenic activities. We developed a stochastic surplus production model (SPM) linking abundance and removal processes under the assumption that variations in removals reflect variations in abundance. We then consider several 'harvest' control rules, included two candidate ones derived from this SPM (which we called 'Anthropogenic Removals Threshold', or ART), to manage removals of PETS. The two candidate rules hinge on the estimation of a stationary removal rate. We compared these candidate rules to other existing control rules (e.g. potential biological removal or a fixed percentage rule) in three scenarios: (i) a base scenario whereby unbiased but noisy data are available, (ii) scenario whereby abundance estimates are overestimated and (iii) scenario whereby abundance estimates are underestimated. The different rules were tested on a simulated set of data with life-history parameters close to a small-sized cetacean species of conservation interest in the North-East Atlantic, the harbour porpoise (Phocoena phocoena), and in a management strategy evaluation framework. The effectiveness of the rules were assessed by looking at performance metrics, such as time to reach the conservation objectives, the removal limits obtained with the rules or temporal autocorrelation in removal limits. Most control rules were robust against biases in data and allowed to reach conservation objectives with removal limits of similar magnitude when averaged over time. However, one of the candidate rule (ART) displayed greater alignment with policy requirements for PETS such as minimizing removals over time.

Impact of Opioid Use on Duration of Therapy and Overall Survival for Patients with Advanced Non-Small Cell Lung Cancer Treated with Immune Checkpoint Inhibitors.

Immune checkpoint inhibitors (ICI) have significantly improved outcomes in advanced non-small cell lung cancer (NSCLC). We evaluated the effect of opioid use on outcomes in patients receiving ICI either alone or with chemotherapy. We conducted a retrospective review of 209 patients with advanced NSCLC who received an ICI at the University of Virginia between 1 February 2015 and 1 January 2020. We performed univariate and multivariate analyses to evaluate the impact of opioid use on duration of therapy (DOT) and overall survival (OS). Patients with no or low opioid use (n = 172) had a median DOT of 12.2 months (95% CI: 6.9-17.4) compared to 1.9 months (95% CI: 1.8-2.0) for those with high opioid use (n = 37, HR 0.26 95% CI: 0.17-0.40, p < 0.001). Patients with no or low opioid use had a median OS of 22.6 months (95% CI: 14.8-30.4) compared to 3.8 months (95% CI: 2.7-4.9) for those with high opioid use (HR 0.26 95% CI: 0.17-0.40 p < 0.001). High opioid use was associated with a shorter DOT and worse OS. This difference remained significant when accounting for possible confounding variables. These data warrant investigation of possible mechanistic interactions between opioids, tumor progression, and ICIs, as well as prospective evaluation of opioid-sparing pain management strategies, where possible.

A rigorous evaluation of earthquake management strategies in Morocco's Al Haouz province: a Multi-Criteria Decision-Making methodology

A rigorous evaluation of earthquake management strategies in Morocco's Al Haouz province: a Multi-Criteria Decision-Making methodology

Bridging proxy reference points to sustainable yields to support data-limited fisheries

Many of the world fisheries, especially small-scale fisheries, are in data-limited situations, for which proxy Biological Reference Points (BRPs) derived from per-recruit analyses are widely used to inform fisheries management. However, due to limited information on stock recruitment, per-recruit analyses usually assume constant recruitment and the influences of this key assumption have not been fully understood. In this study, we combined per-recruit analyses and stock-recruit relationship to build equilibrium models for eight species with different life history traits, and used the management strategy evaluation (MSE) framework to assess the uncertainty of proxy BRPs in achieving fisheries sustainability. Our results showed substantial variations in the performances of proxy BRPs on maintaining yield and biomass, and even conservative BRPs, e.g. F0.1 caused overexploitation in half of the cases (4 out of 8). The divergence of the performance between proxy BRPs and FMSY could be substantial, depending on steepness of stock-recruit relationships (correlation ranged from –0.55 to 0.9 for yield, and 0.53 to 0.96 for biomass). Accordingly, we presented an empirical approach for remediation, using correction coefficient to adjust the traditional proxy BRPs. The empirical approach showed satisfactory performances in the validation processes with an independent dataset. This paper demonstrates that proxy BRPs may introduce risks in achieving fisheries sustainability, whereas the errors can be readily adjusted with empirical estimates of steepness for most data-limited fisheries.

Enhancing disaster management in smart cities through MCDM-AHP analysis amid 21st century challenges

In the era of rapid urbanization and technological progress, smart cities offer a promising solution to multifaceted global challenges, leveraging advanced technologies to optimize resources and enhance the quality of life; however, this interconnectedness also exposes them to novel vulnerabilities, particularly in the face of natural and man-made disasters, necessitating inventive strategies to ensure resilience against cyber threats and extreme weather events. This article delves into the exploration of smart cities’ diverse aspects and the categories of disasters they face, followed by an analysis of strategic mitigation approaches and their underlying criteria; it subsequently introduces the Multi-Criteria Decision-Making methodology, particularly Analytical Hierarchy Process (AHP), as a robust tool for systematic evaluation and prioritization of disaster management strategies in the increasingly complex landscape. The study’s analysis of relative weights underscores the pivotal role of resilience enhancement and communication redundancy as primary considerations in evaluating disaster management strategies for smart cities, while other criteria such as accuracy and timeliness, scaleability and adaptability, cost-effectiveness, ethical and privacy considerations, and training and skill requirements assume varying degrees of importance in supporting roles, providing valuable insights into the decision-making process. The assessment of alternative strategies highlights their prioritization in effective disaster management for smart cities, with notable emphasis on citizen engagement and education, early warning systems, and data analytics; further strategies such as integrated communication systems, resilient infrastructure design, drones and robotics, artificial intelligence algorithms, and IoT-enabled sensors and monitoring exhibit varying degrees of significance, offering insights into their roles and potential contributions to disaster management strategies based on their weighted sums. This research has practical significance, guiding stakeholders like urban planners, policymakers, and disaster management professionals to enhance smart city resilience and prioritize strategies based on critical factors, ultimately enabling effective disaster management in smart cities amid 21st-century challenges.

Development and evaluation of an online home energy management strategy for load coordination in smart homes with renewable energy sources

In this paper, a real time implementable load coordination strategy is developed for the optimization of electric demands in a smart home. The strategy minimizes the electricity cost to the home owner, while limiting the disruptions associated with the deferring of flexible power loads. A multi-objective nonlinear mixed integer programming is formulated as a sequential model predictive control, which is then solved using genetic algorithm. The load shifting benefits obtained by deploying an advanced coordination strategy are compared against a baseline controller for various home characteristics, such as location, size and equipment. The simulation study shows that the deployment of the smart home energy management strategy achieves approximately 5% reduction in grid cost compared to a baseline strategy. This is achieved by deferring approximately 50% of the flexible loads, which is possible due to the use of the stationary energy storage.

Methodological approaches to assessing population-level impacts of bird collisions with wind turbines: a critical perspective

SummaryWind energy is a source of collision fatalities for birds and bats. To evaluate the risk that wind power development projects might pose to the conservation of protected species, it is essential to quantify the impact of collisions on the dynamics of wild populations. To address this challenge, two approaches are primarily employed: potential biological removal (PBR) and population projection analysis (PPA). PBR is a decision rule designed to calculate a sustainable fatality limit for a given population, whereas PPA relies on simulation-based modelling to forecast a population’s future trajectory under various scenarios. In the context of environmental impact assessments (EIAs), we argue that PPA offers a more suitable method than PBR for evaluating population-level impacts resulting from collisions with wind turbines. Unlike PBR, PPA can be focused on a single source of disturbance, aligning with the perspective of the EIA process. By contrast, PBR necessarily adopts a population-centred perspective and is therefore only relevant when considering all sources of mortality that jointly affect a population. Furthermore, robust utilization of the PBR approach requires the definition of quantitative conservation objectives and the implementation of a comprehensive management strategy evaluation, neither of which is ever undertaken within the context of an EIA.