Phenotype-aware prioritisation of rare Mendelian disease variants.

A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.

Predicting and Prioritising Community Assembly: Learning Outcomes via Experiments.

Community assembly provides the foundation for applications in biodiversity conservation, climate change, invasion, restoration and synthetic ecology. However, predicting and prioritising assembly outcomes remains difficult. We address this challenge via a mechanism-free approach useful when little data or knowledge exist (LOVE; Learning Outcomes Via Experiments). We carry out assembly experiments ('actions', here, random combinations of species additions) potentially in multiple environments, wait, and measure abundance outcomes. We then train a model to predict outcomes of novel actions or prioritise actions that would yield the most desirable outcomes. Across 10 single- and multi-environment datasets, when trained on 89 randomly selected actions, LOVE predicts outcomes with 0.5%-3.4% mean error, and prioritises actions for maximising richness, maximising abundance, or removing unwanted species, with 94%-99% mean true positive rate and 10%-84% mean true negative rate across tasks. LOVE complements existing mechanism-first approaches for community ecology and may help address numerous applied challenges.

Plant diversity darkspots for global collection priorities.

More than 15% of all vascular plant species may remain scientifically undescribed, and many of the > 350 000 described species have no or few geographic records documenting their distribution. Identifying and understanding taxonomic and geographic knowledge shortfalls is key to prioritising future collection and conservation efforts. Using extensive data for 343 523 vascular plant species and time-to-event analyses, we conducted multiple tests related to plant taxonomic and geographic data shortfalls, and identified 33 global diversity darkspots (those 'botanical countries' predicted to contain most undescribed and not yet recorded species). We defined priority regions for future collection according to several socio-economic and environmental scenarios. Most plant diversity darkspots are found within global biodiversity hotspots, with the exception of New Guinea. We identify Colombia, Myanmar, New Guinea, Peru, Philippines and Turkey as global collection priorities under all environmental and socio-economic conditions considered. Our study provides a flexible framework to help accelerate the documentation of global plant diversity for the implementation of conservation actions. As digitisation of the world's herbaria progresses, collection and conservation priorities may soon be identifiable at finer scales.

Conservation planning for retention, not just protection.

Most protected area (PA) planning aims to improve biota representation within the PA system, but this does not necessarily achieve the best outcomes for biota retention across regions when we also consider habitat loss in areas outside the PA system. Here, we assess the implications that different PA expansion strategies can have on the retention of species habitat across an entire region. Using retention of forest habitat for Colombia's 550 forest-dependent bird species as our outcome variable, we found that when a minimum of 30% of each species' habitat was included in the PA system, a pattern of PA expansion targeting areas at highest deforestation risk (risk-prevention) led to the retention, on average, of 7.2% more forest habitat per species by 2050 than did a pattern that targeted areas at lowest risk (risk-avoidance). The risk-prevention approach cost more per km2 of land conserved, but it was more cost-effective in retaining habitat in the landscape (50%-69% lower cost per km2 of avoided deforestation). To have the same effectiveness preventing habitat loss in Colombia, the risk-avoidance approach would require more than twice as much protected area, costing three times more in the process. Protected area expansion should focus on the contributions of PAs to outcomes not only within PA systems themselves, but across entire regions.

La mayor parte de la planificación de áreas protegidas (AP) tiene como objetivo mejorar la representación de la biota dentro del sistema de AP, pero esto no necesariamente logra los mejores resultados para la retención de biota a nivel de paisaje cuando también consideramos la pérdida de hábitat en áreas fuera del sistema de AP. Aquí evaluamos las implicaciones que diferentes estrategias de expansión de AP pueden tener en la retención del hábitat de las especies en toda una región. Utilizando la retención de hábitat forestal para las 550 especies de aves dependientes de bosque de Colombia como nuestra variable de resultado, encontramos que cuando un mínimo del 30% del hábitat de cada especie es incluido en el sistema de AP, se observó que un patrón de expansión de AP dirigido a áreas con mayor riesgo de deforestación (prevención de riesgos) condujo a la retención, en promedio, de un 7.2% más de hábitat por especie para 2050 que un patrón enfocado en áreas con menor riesgo (evasión de riesgos). El enfoque de prevención de riesgos costó más por km2 de tierra conservada, pero fue más rentable para retener el hábitat en el paisaje (entre un 50% y un 69% menos costo por km2 de deforestación evitada). Para tener la misma eficacia en la prevención de la pérdida de hábitat en Colombia, el enfoque de evasión de riesgos requeriría más del doble de área protegida, lo que costaría tres veces más en el proceso. La expansión de las AP debería centrarse en las contribuciones de las AP a los resultados no sólo dentro de los propios sistemas de AP, sino en regiones enteras.

Artificial Intelligence-Driven Prediction Revealed CFTR Associated with Therapy Outcome of Breast Cancer: A Feasibility Study.

INTRODUCTION: In silico tools capable of predicting the functional consequences of genomic differences between individuals, many of which are AI-driven, have been the most effective over the past two decades for non-synonymous single nucleotide variants (nsSNVs). When appropriately selected for the purpose of the study, a high predictive performance can be expected. In this feasibility study, we investigate the distribution of nsSNVs with an allele frequency below 5%. To classify the putative functional consequence, a tier-based filtration led by AI-driven predictors and scoring system was implemented to the overall decision-making process, resulting in a list of prioritised genes. METHODS: The study has been conducted on breast cancer patients of homogeneous ethnicity. Germline rare variants have been sequenced in genes that influence pharmacokinetic parameters of anticancer drugs or molecular signalling pathways in cancer. After AI-driven functional pathogenicity classification and data mining in pharmacogenomic (PGx) databases, variants were collapsed to the gene level and ranked according to their putative deleterious role. RESULTS: In breast cancer patients, seven of the twelve genes prioritised based on the predictions were found to be associated with response to oncotherapy, histological grade, and tumour subtype. Most importantly, we showed that the group of patients with at least one rare nsSNVs in cystic fibrosis transmembrane conductance regulator (CFTR) had significantly reduced disease-free (log rank, p = 0.002) and overall survival (log rank, p = 0.006). CONCLUSION: AI-driven in silico analysis with PGx data mining provided an effective approach navigating for functional consequences across germline genetic background, which can be easily integrated into the overall decision-making process for future studies. The study revealed a statistically significant association with numerous clinicopathological parameters, including treatment response. Our study indicates that CFTR may be involved in the processes influencing the effectiveness of oncotherapy or in the malignant progression of the disease itself.

Operationalisation of health equity principles in physiotherapy hospital triage policies.

BACKGROUND: Healthcare triage policies are vital for allocating limited resources fairly and equitably. Despite extensive studies of healthcare equity, consensus on the applied definition of equity in triage remains elusive. This study aimed to investigate how the principles of equity are operationalised in Australian hospital physiotherapy triage tools to guide resource distribution. METHODS: A retrospective, qualitative content analysis of 13 triage policies from 10 hospitals across Australia was conducted. Triage policies from both inpatient and outpatient settings were sourced. Data were coded deductively using the five discrete domains of the multi-faceted operational definition of health equity posited by Lane et al. (2017): 1) point of equalisation in the health service supply/access/outcome chain, 2) need or potential to benefit, 3) groupings of equalisation, 4) caveats to equalisation, 5) close enough is good enough. Descriptive summative statistics were used to analyse and present the frequency of reported equity domains. RESULTS: Within the included triage tools, four out of five domains of equity were evident in the included documents to guide decision making. Allocation based on perceived patient need and overall health outcomes were the central guiding principles across both inpatient and outpatient settings. Equal provision of service relative to patient need and reducing wait times were also prioritised. However, explicit inclusion of certain equity domains such as discrimination, ensuring equal capability to be healthy and other patient factors was limited. CONCLUSIONS: Physiotherapy triage policies consider various domains of equity to guide resource allocation decisions. Policymakers and service providers can use the insights gained from this study to review the application and operationalisation of equity principles within their healthcare systems through mechanisms such as patient triage tools.

The self can be associated with novel faces of in-group and out-group members: A cross-cultural study.

The self can be associated with arbitrary images, such as geometric figures or unknown faces. By adopting a cross-cultural perspective, we explored in two experiments whether the self can be associated with faces of unknown people from different ethnic groups. In Experiment 1, Asian Japanese participants completed a perceptual matching task, associating Asian or White faces with themselves. The same task was used in Experiment 2 with White Italians. Both experiments showed a reliable association between the self and facial stimuli. Importantly, this association was similar for both Asian and White faces. Additionally, no correlations were found between the strength of this association and an index of implicit bias towards Asian and White individuals. These results suggest that the self is malleable and can incorporate social stimuli from different groups.

Older people's goals of care in relation to frailty status-the COOP-study.

BACKGROUND: Literature relating older people's goals of care to their varying frailty status is scarce. OBJECTIVE: To investigate goals of care in case of acute and/or severe disease in relationship to frailty status among the general older population. METHOD: Older people aged ≥70 in the Netherlands completed a questionnaire. They were divided into three subgroups based on a self-reported Clinical Frailty Scale: fit (CFS 1-3), mildly frail (CFS 4-5) and severely frail (CFS 6-8). Seven goals were graded as unimportant (1-5), somewhat important (6-7) or very important (8-10): extending life, preserving quality of life (QoL), staying independent, relieving symptoms, supporting others, preventing hospital admission and preventing nursing home admission. RESULTS: Of the 1,278 participants (median age 76 years, 63% female), 57% was fit, 32% mildly frail and 12% severely frail. Overall, participants most frequently considered preventing nursing home admission as very important (87%), followed by staying independent (84%) and preserving QoL (83%), and least frequently considered extending life as very important (31%). All frailty subgroups reported similar preferences out of the surveyed goals as the overall study population. However, participants with a higher frailty status attached slightly less importance to each individual goal compared with fit participants (Ptrend-values ≤ 0.037). CONCLUSION: Preferred goals of care are not related to frailty status, while the importance ascribed to individual goals is slightly lower with higher frailty status. Future research should prioritise outcomes related to the shared goals of fit, mildly frail and severely frail older people to improve personalised medicine for older patients.

The self-bias in working memory: the favorability of self-referential stimuli in resource allocation.

Self-representations guide and shape our thoughts and behaviour. People usually exhibit inherent biases in perception, attention, and memory to favour the information associated with themselves over that associated with others. The present study explored the phenomenon of self-bias in working memory (WM), specifically how self-referential processing impacts WM precision. Four precision-based experiments were conducted to assess the recall precision of self-referential items and items associated with other social agents. The findings revealed a robust self-prioritisation effect in WM precision, wherein self-referential items were recalled with greater precision than items associated with other social agents. Additionally, increased precision for self-referential items did not decrease the precision for simultaneously remembered items. This effect was limited by the total amount of WM resources and not influenced by a perceptual distractor. The inherent self-bias in WM can serve as a proxy to access the role self-representation in goal-oriented cognitive processing, providing a means of exploring the interaction between self-reference and high-level cognitive function.

Reasons influencing the nurses' prioritization process while preventing and managing delirium: findings from a qualitative study.

BACKGROUND: Nurses play an important role in the prevention and management of delirium episodes. However, some studies have reported that not all interventions recommended are applied due to time and resource constraints, resulting in patients receiving less care than required because other patients and/or interventions are prioritised. The concept of prioritization is part of the broader concept of decision-making as the ability to choose between two or more alternatives to ensure patient safety. Understanding the reasons influencing the prioritization process in patients at risk or with delirium may inform interventions to prevent and/or minimise the unfinished nursing care. AIM: The purpose of this study was to explore the reasons that inform the prioritisation process among nurses when they are challenged to make decisions for patients at risk and with delirium. METHODS: A descriptive qualitative study performed according to the COnsolidated criteria for Reporting guidelines, in 2021. An intentional sample of nurses working full-time with older patients in medical, geriatric, and post-acute care facilities affiliated with the National Health System was involved. Semi-structured interviews were conducted and narratives thematic analysed. RESULTS: A total of 56 nurses (55.4% in internal medicine, 26.8% in geriatrics and 17.8% in post-acute/intermediate care) participated with an average age of 31.6 years. The reasons informing the prioritisation process while providing preventive or managerial interventions towards a patient at risk of or with delirium are set at three levels: (1) unit level, as reasons belong to the inadequacy of the 'Environment', the 'Human Resources', and the 'Organisation and Work Processes', (2) nurse's level, as issues in 'Competencies' and 'Attitudes' possessed, and (3) patient level, due to the 'Multidimensional Frailty'. CONCLUSION: Nurses caring for patients at risk of and with delirium face several challenges in providing care. To prioritise preventive and managerial interventions, it is essential to implement multilevel and multifaced organizational and educational strategies.

Stimulus valence moderates self-learning.

Self-relevance has been demonstrated to impair instrumental learning. Compared to unfamiliar symbols associated with a friend, analogous stimuli linked with the self are learned more slowly. What is not yet understood, however, is whether this effect extends beyond arbitrary stimuli to material with intrinsically meaningful properties. Take, for example, stimulus valence an established moderator of self-bias. Does the desirability of to-be-learned material influence self-learning? Here, in conjunction with computational modelling (i.e. Reinforcement Learning Drift Diffusion Model analysis), a probabilistic selection task was used to establish if and how stimulus valence (i.e. desirable/undesirable posters) impacts the acquisition of knowledge relating to object-ownership (i.e. owned-by-self vs. owned-by-friend). Several interesting results were observed. First, undesirable posters were learned more rapidly for self compared to friend, an effect that was reversed for desirable posters. Second, learning rates were accompanied by associated differences in reward sensitivity toward desirable and undesirable choice selections as a function of ownership. Third, decisional caution was greater for self-relevant (vs. friend relevant) responses. Collectively, these findings inform understanding of self-function and how valence and stimulus relevance mutually influence probabilistic learning.

Observational learning of threat-related attentional bias.

Attentional bias to threat has been almost exclusively examined after participants experienced repeated pairings between a conditioned stimulus (CS) and an aversive unconditioned stimulus (US). This study aimed to determine whether threat-related attentional capture can result from observational learning, when participants acquire knowledge of the aversive qualities of a stimulus without themselves experiencing aversive outcomes. Non-clinical young-adult participants (N = 38) first watched a video of an individual (the demonstrator) performing a Pavlovian conditioning task in which one colour was paired with shock (CS+) and another colour was neutral (CS-). They then carried out visual search for a shape-defined target. Oculomotor measures evidenced an attentional bias toward the CS+ colour, suggesting that threat-related attentional capture can ensue from observational learning. Exploratory analyses also revealed that this effect was positively correlated with empathy for the demonstrator. Our findings extend empirical and theoretical knowledge about threat-driven attention and provide valuable insights to better understand the formation of anxiety disorders.

Prioritising patients for semi-urgent surgery: A scoping review.

BACKGROUND: Semi-urgent surgery where surgical intervention is required within 48 h of admission and the patient is medically stable is vulnerable to scheduling delays. Given the challenges in accessing health care, there is a need for a detailed understanding of the factors that impact decisions on scheduling semi-urgent surgeries. AIM: To identify and describe the organisational, departmental and contextual factors that determine healthcare professionals' prioritising patients for semi-urgent surgeries. METHODS: We used the Joanna Briggs Institute guidance for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) checklist. Four online databases were used: EBSCO Academic Search Complete, EBSCO Cumulative Index to Nursing and Allied Health Literature, OVID Embase and EBSCO Medline. Articles were eligible for inclusion if they published in English and focussed on the scheduling of patients for surgery were included. Data were extracted by one author and checked by another and analysed descriptively. Findings were synthesises using the Patterns, Advances, Gaps, Evidence for practice and Research recommendations framework. RESULTS: Twelve articles published between 1999 and 2022 were included. The Patterns, Advances, Gaps, Evidence for practice and Research recommendations framework highlighted themes of emergency surgery scheduling and its impact on operating room utilisation. Gaps in the management of operating room utilisation and the incorporation of semi-urgent surgeries into operating schedules were also identified. Finally, the lack of consensus on the definition of semi-urgent surgery and the parameters used to assign surgical acuity to patients was evident. CONCLUSIONS: This scoping review identified patterns in the scheduling methods, and involvement of key decision makers. Yet there is limited evidence about how key decision makers reach consensus on prioritising patients for semi-urgent surgery and its impact on patient experience. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Inference of Essential Genes of the Parasite Haemonchus contortus via Machine Learning.

Over the years, comprehensive explorations of the model organisms Caenorhabditis elegans (elegant worm) and Drosophila melanogaster (vinegar fly) have contributed substantially to our understanding of complex biological processes and pathways in multicellular organisms generally. Extensive functional genomic-phenomic, genomic, transcriptomic, and proteomic data sets have enabled the discovery and characterisation of genes that are crucial for life, called 'essential genes'. Recently, we investigated the feasibility of inferring essential genes from such data sets using advanced bioinformatics and showed that a machine learning (ML)-based workflow could be used to extract or engineer features from DNA, RNA, protein, and/or cellular data/information to underpin the reliable prediction of essential genes both within and between C. elegans and D. melanogaster. As these are two distantly related species within the Ecdysozoa, we proposed that this ML approach would be particularly well suited for species that are within the same phylum or evolutionary clade. In the present study, we cross-predicted essential genes within the phylum Nematoda (evolutionary clade V)-between C. elegans and the pathogenic parasitic nematode H. contortus-and then ranked and prioritised H. contortus proteins encoded by these genes as intervention (e.g., drug) target candidates. Using strong, validated predictors, we inferred essential genes of H. contortus that are involved predominantly in crucial biological processes/pathways including ribosome biogenesis, translation, RNA binding/processing, and signalling and which are highly transcribed in the germline, somatic gonad precursors, sex myoblasts, vulva cell precursors, various nerve cells, glia, or hypodermis. The findings indicate that this in silico workflow provides a promising avenue to identify and prioritise panels/groups of drug target candidates in parasitic nematodes for experimental validation in vitro and/or in vivo.

Prioritising gully remediation in a Great Barrier Reef catchment: An approach using two independent methods of assessing erosion activity in 22,300 gullies.

The strategic reduction and remediation of degraded land is a global environmental priority. This is a particular priority in the Great Barrier Reef catchment area, Australia, where gully erosion a significant contributor to land degradation and water quality deterioration. Urgent action through the prioritisation and remediation of gully erosion sites is imperative to safeguard this UNESCO World Heritage site. In this study, we analyze a comprehensive dataset of 22,311 mapped gullies within a 3480 km2 portion of the lower Burdekin Basin, northeast Australia. Utilizing high-resolution lidar datasets, two independent methods - Minimum Contemporary Estimate (MCE) and Lifetime Average Estimate (LAE) - were developed to derive relative erosion rates. These methods, employing different data processing approaches and addressing different timeframes across the gully lifetime, yield erosion rates varying by up to several orders of magnitude. Despite some expected divergence, both methods exhibit strong, positive correlations with each other and additional validation data. There is a 43% agreement between the methods for the highest yielding 2% of gullies, although 80.5% of high-yielding gullies identified by either method are located within a 1 km proximity of each other. Importantly, distributions from both methods independently reveal that ∼80% of total volume of gully erosion in the study area is produced from only 20% of all gullies. Moreover, the top 2% of gullies generate 30% of the sediment loss and the majority of gullies do not significantly contribute to the overall catchment sediment yield. These results underscore the opportunity to achieve significant environmental outcomes through targeted gully management by prioritising a small cohort of high yielding gullies. Further insights and implications for management frameworks are discussed in the context of the characteristics of this cohort. Overall, this research provides a basis for informed decision-making in addressing gully erosion and advancing environmental conservation efforts.

Protecting and restoring freshwater biodiversity across urban areas in Aotearoa New Zealand: Citizens' reporting of pollution in stormwater drains and waterways.

Urbanization poses numerous challenges to freshwater biodiversity. This paper describes two studies with the joint aim of demonstrating the benefits of applying a systematic behaviour change framework and providing the foundational knowledge to inform future behavior change work to protect and restore urban freshwater biodiversity. In Study 1 we used a mixed-methods research design, involving 14 key informant interviews followed by an online survey targeting 17 freshwater biodiversity experts and another targeting a representative sample of 550 urban residents, to identify and prioritize the most promising resident behaviors to target to reduce stormwater pollution and improve natural waterway habitats in urban areas. Study 2 focused on the top-ranked short-term behavior identified in Study 1, citizen reporting of pollution in stormwater drains and waterways. We surveyed a representative sample of 1901 urban residents across Aoteraoa New Zealand to identify four main determinants influencing this behavior: awareness and uncertainty about reporting, lack of opportunity to report, social motivation and personal motivation to report, and five potential target audiences: 'Supportive', 'Unaware but receptive', 'Motivated but lack support', 'Reluctant', and 'Not my problem'. We make recommendations for the most appropriate intervention designs to target each of these audience segments to promote the reporting of stormwater pollution in urban areas. This knowledge will allow for a more coordinated and effective approach for addressing the 'human element' that lies at the heart of many urban freshwater management problems.

Nurses prioritization processes to prevent delirium in patients at risk: Findings from a Q-Methodology study.

BACKGROUND: This study aimed at (a) exploring how nurses prioritise interventions to prevent delirium among patients identified at risk and (b) describing the underlying prioritisation patterns according to nurses' individual characteristics. METHODS: There was used the Q-methodology a research process following specific steps: (a) identifying the concourse, (b) the Q-sample, and (c) the population (P-set); (d) collecting data using the Q-sort table; (e) entering the data and performing the factor analysis; and (f) interpreting the factors identified. RESULTS: There were involved 56 nurses working in medical, geriatric and log-term facilities (46; 82.2 %). The preventive intervention receiving the highest priority was 'Monitoring the vital parameters (heart rate, blood pressure, oxygen saturation)' (2.96 out of 4 as the highest priority; CI 95 %: 2.57, 3.36). Two priority patterns emerged among nurses (explained variance 44.78 %), one 'Clinical-oriented' (36.19 %) and one 'Family/caregiver-oriented' (8.60 %) representing 53 nurses out 56. CONCLUSION: Alongside the overall tendency to prioritise some preventive interventions instead of others, the priorities are polarised in two main patterns expressing two main individual characteristics of nurses. Knowing the existence of individual patterns and their aggregation informs how to shape educational interventions.

Prioritising Cochrane reviews to be updated with health equity focus.

BACKGROUND: The prioritisation of updating published systematic reviews of interventions is vital to prevent research waste and ensure relevance to stakeholders. The consideration of health equity in reviews is also important to ensure interventions will not exacerbate the existing inequities of the disadvantaged if universally implemented. This study aimed to pilot a priority setting exercise based on systematic reviews of interventions published in the Cochrane Library, to identify and prioritise reviews to be updated with a focus on health equity. METHODS: We conducted a priority setting exercise with a group of 13 international stakeholders. We identified Cochrane reviews of interventions that showed a reduction in mortality, had at least one Summary of Findings table and that focused on one of 42 conditions with a high global burden of disease from the 2019 WHO Global Burden of Disease report. This included 21 conditions used as indicators of success of the United Nations Universal Health Coverage in attaining the Sustainable Development Goals. Stakeholders prioritised reviews that were relevant to disadvantaged populations, or to characteristics of potential disadvantage within the general population. RESULTS: After searching for Cochrane reviews of interventions within 42 conditions, we identified 359 reviews that assessed mortality and included at least one Summary of Findings table. These pertained to 29 of the 42 conditions; 13 priority conditions had no reviews with the outcome mortality. Reducing the list to only reviews showing a clinically important reduction in mortality left 33 reviews. Stakeholders ranked these reviews in order of priority to be updated with a focus on health equity. CONCLUSIONS: This project developed and implemented a methodology to set priorities for updating systematic reviews spanning multiple health topics with a health equity focus. It prioritised reviews that reduce overall mortality, are relevant to disadvantaged populations, and focus on conditions with a high global burden of disease. This approach to the prioritisation of systematic reviews of interventions that reduce mortality provides a template that can be extended to reducing morbidity, and the combination of mortality and morbidity as represented in Disability-Adjusted Life Years and Quality-Adjusted Life Years.

Developing and validating a multi-criteria decision analytic tool to assess the value of cancer clinical trials: evaluating cancer clinical trial value.

BACKGROUND: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation. METHODS: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value. RESULTS: Seven criteria were identified: 'unmet need', 'size of target population', 'eligible participants can access the trial', 'patient outcomes', 'total trial cost', 'academic impact' and 'use of trial results'. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an 'Unmet Need' was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved 'Patient Outcomes' with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials. CONCLUSION: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.

Managing surgical waiting lists through dynamic priority scoring.

Prioritising elective surgery patients under the Australian three-category system is inherently subjective due to variability in clinician decision making and the potential for extraneous factors to influence category assignment. As a result, waiting time inequities can exist which may lead to adverse health outcomes and increased morbidity, especially for patients deemed to be low priority. This study investigated the use of a dynamic priority scoring (DPS) system to rank elective surgery patients more equitably, based on a combination of waiting time and clinical factors. Such a system enables patients to progress on the waiting list in a more objective and transparent manner, at a rate relative to their clinical need. Simulation results comparing the two systems indicate that the DPS system has potential to assist in managing waiting lists by standardising waiting times relative to urgency category, in addition to improving waiting time consistency for patients of similar clinical need. In clinical practice, this system is likely to reduce subjectivity, increase transparency, and improve overall efficiency of waiting list management by providing an objective metric to prioritise patients. Such a system is also likely to increase public trust and confidence in the systems used to manage waiting lists.