Consensus Method Research Articles

A pediatric virtual care evaluation framework and its evolution using consensus methods

BackgroundThe use of virtual care has increased dramatically in response to the COVID-19 pandemic, yet evidence is lacking regarding the impact of virtual care on patient outcomes, particularly in pediatrics. A standardized evaluation approach is required to support the integration of virtual care into pediatric health care delivery programs. The objective of this work was to develop a comprehensive and structured framework for pediatric virtual care evaluation. This framework is intended to engage and guide care providers, health centres, and stakeholders towards the development of a standardized approach to the evaluation of pediatric virtual care.MethodsWe brought together a diverse multidisciplinary team, including pediatric clinicians, researchers, digital health leads and analysts, program leaders, a human factors engineer, a family advisor and our manager of health equity and diversity. The team reviewed the literature, including published evaluation frameworks, and used a consensus-based method to develop a virtual care evaluation framework applicable to a broad spectrum of pediatric virtual care programs. We used an iterative process to develop framework components, including domains and sub-domains, examples of evaluation questions, measures, and data sources. Team members met repeatedly over seven months to generate and provide feedback on all components of the framework, making revision as needed until consensus was reached. The framework was then applied to an existing virtual care program.ResultsThe resulting framework includes four domains (health outcomes, health delivery, individual experience, and program implementation) and 19 sub-domains designed to support the development and evaluation of pediatric virtual care programs. We also developed guidance on how to use the framework and illustrate its utility by applying it to an existing pediatric virtual care program.ConclusionsThis virtual care evaluation framework expands on previously developed frameworks by providing additional detail and a structure that supports practical application. It can be used to evaluate a wide range of pediatric virtual care programs in a standardized manner. Use of this comprehensive yet easy to use evaluation framework will inform appropriate implementation and integration of virtual care into routine practice and support its sustainability and continuous improvement.

Validation of an Educational Tool for Skin Abscess Incision and Drainage by Delphi and Angoff Methods.

Bedside incision and drainage (I&D) of skin abscesses is a common medical procedure performed in a variety of medical settings. Yet, there is a paucity of published validated educational tools to teach and assess competency for this procedure. To validate an educational tool to teach and assess competency for bedside I&D of skin abscesses via the Delphi consensus and Angoff standard setting methods. Expert consensus on the importance of each procedural step in the educational tool was obtained using the Delphi method, consisting of four rounds of iterative revisions based on input from a panel of experts. The passing cut-off score for a proficient provider was determined using the modified dichotomous Angoff method. All participants met the minimum criteria of active involvement in resident education and performance of at least 20 skin abscess I&D's within the past 5years. Participant specialties included general surgery, emergency medicine, and internal medicine. The primary outcome was consensus on procedural steps and errors, defined as an interquartile range ≤ 2 on a 9-point Likert scale. A cut-off score was determined by the average across all respondents for the anticipated number of errors that would be committed by a provider with the level of proficiency defined in the survey. Qualitative input was incorporated into the educational tool. At the end of four rounds of review via the Delphi process, participants achieved consensus on 93% of items on the clinical checklist and 85% of errors on the assessment checklist. Via the modified dichotomous Angoff method, the determined passing cut-off for competency was 6 out of 22 errors. An educational and evaluation tool for bedside I&D of skin abscesses was validated via the Delphi and Angoff methods.

Strategies to preventing pressure injuries among intensive care unit patients mechanically ventilated in prone position: a systematic review and a Delphi study.

Although the incidence of pressure injury in the prone position is high for the mechanically ventilated patients in the intensive care unit, evidence-based strategies are still lacking. To conduct a systematic review of current evidence, and to propose a series of strategies to prevent pressure injuries among mechanically ventilated patients with prone position in the intensive care unit. The study was guided by the Medical Research Council framework. After a systematic review of current evidence of original articles, guidelines, expert consensus and theories, a strategy draft was developed. Then we invited 20 experts to modify and refine these strategies through two rounds of Delphi consensus method. After two rounds of Delphi process, the importance of coefficient of variation (Cv) and Kendall's coefficient of concordance in the strategies repository were 0.067 and 0.311, respectively. And the operability of Cv and Kendall's coefficient of concordance in the strategy draft was 0.055 and 0.294, respectively. Ultimately, we established 31 strategies for including 7 themes (assess risk factors, assess skin and tissue, body position management, skin care, nutrition, preventing medical device-related pressure injuries, education and supervision). In addition, we also developed a strategy framework to clarify our strategies. According to the Medical Research Council framework, we developed 7 themes and 31 strategies to prevention prone-position pressure injuries among the intensive care unit mechanically ventilated patients. This study was considered to improve the clinical management of pressure injuries among prone position patients in the intensive care unit settings.

Foundational domains and competencies for baccalaureate health informatics education.

Foundational domains are the building blocks of educational programs. The lack of foundational domains in undergraduate health informatics (HI) education can adversely affect the development of rigorous curricula and may impede the attainment of CAHIIM accreditation of academic programs. This White Paper presents foundational domains developed by AMIA's Academic Forum Baccalaureate Education Committee (BEC) which include corresponding competencies (knowledge, skills, and attitudes) that are intended for curriculum development and CAHIIM accreditation quality assessment for undergraduate education in applied health informatics. The AMIA BEC used the previously published master's foundational domains as a guide to creating a set of competencies for health informatics at the undergraduate level to assess graduates from undergraduate health informatics programs for competence at graduation. A consensus method was used to adapt the domains for undergraduate level course work and harmonize the foundational domains with the currently adapted domains for HI master's education. Ten foundational domains were developed to support the development and evaluation of baccalaureate health informatics education. This article will inform future work towards building CAHIIM accreditation standards to ensure that higher education institutions meet acceptable levels of quality for undergraduate health informatics education.

Robust Monocular Visual Inertial Odometry in γ Radioactive Environments using Edge-based Point Features

Abstract In the γ radioactive environment, high-energy photons induce degradation of the image sensor, which effects feature detection and tracking in the Visual Inertial Odometry (VIO) algorithm and deteriorates its localization performance. To address this issue, in this work, we propose a monocular VIO method using edge-based point features. To mitigate the effects of radiation noise, firstly, in the image preprocessing module, the median filter is used for real-time image denoising. Secondly, in the data association module, both Shi-Tomasi and edge-based point features are detected. The edge-based point feature is the endpoint or corner point in the salient edge map, which is more robust to radiation noise. Then, the bi-directional motion parallaxes and the RANdom SAmple Consensus (RANSAC) method are exploited to reject outliers. Finally, the point features measurements and Inertial Measurement Unit (IMU) pre-integration measurements are added into a tightly-coupled sliding window optimization VIO framework for localization estimation. The proposed method is verified by synthetic and real γ radioactive environment datasets. The experimental results show that the proposed method achieves more accurate and robust localization than the state-of-the-art VIO approaches in the γ radioactive environments.

Identification of potential invasive alien species in Spain through horizon scanning

Invasive alien species have widespread impacts on native biodiversity and ecosystem services. Since the number of introductions worldwide is continuously rising, it is essential to prevent the entry, establishment and spread of new alien species through a systematic examination of future potential threats. Applying a three-step horizon scanning consensus method, we evaluated non-established alien species that could potentially arrive, establish and cause major ecological impact in Spain within the next 10 years. Overall, we identified 47 species with a very high risk (e.g. Oreochromis niloticus, Popillia japonica, Hemidactylus frenatus, Crassula helmsii or Halophila stipulacea), 61 with high risk, 93 with moderate risk, and 732 species with low risk. Many of the species categorized as very high or high risk to Spanish biodiversity are either already present in Europe and neighbouring countries or have a long invasive history elsewhere. This study provides an updated list of potential invasive alien species useful for prioritizing efforts and resources against their introduction. Compared to previous horizon scanning exercises in Spain, the current study screens potential invaders from a wider range of terrestrial, freshwater, and marine organisms, and can serve as a basis for more comprehensive risk analyses to improve management and increase the efficiency of the early warning and rapid response framework for invasive alien species. We also stress the usefulness of measuring agreement and consistency as two different properties of the reliability of expert scores, in order to more easily elaborate consensus ranked lists of potential invasive alien species.

Committee experiences of using formal consensus in healthcare guidelines: a longitudinal qualitative study

BackgroundThis feasibility study has the primary aim of capturing and comparing participant expectations and experiences of using a formal consensus method (FCM) and to explore whether these views change following participation within a guideline committee where FCM are used.MethodsTwelve healthcare committee members and associated technical team members participated in semi-structured qualitative interviews before and after using FCM during guideline committee meetings. Interviews also focused on past experiences and expectations of informal consensus methods.ResultsParticipants said formal consensus included a greater range of evidence. They described positive reactions and found it a useful way to encourage involvement by balancing group power dynamics. Group discussion time was identified as important to clarify ideas, supported by good group chairing. However, participants reported that undertaking FCM required additional resources and suggested targeting its use for low quality evidence, limited committee expertise, or where the evidence is controversial.ConclusionsFCM is an acceptable alternative to informal consensus methods that has qualities specifically helpful to healthcare guidelines such as encouraging participation, inclusivity of a broad range of evidence, and managing group dynamics. More research is required to better understand when using formal consensus is most appropriate and effective.

Building consensus in research partnerships: a scoping review of consensus methods

Background: Research partnership approaches that engage community members within the research team (for example, integrated knowledge translation, community-based participatory research) are typically used to enhance the relevance and usefulness of research findings. However, research outcomes generated through partnered research do not de facto address the priorities of those most affected nor take inclusion or power dynamics into consideration. Consensus methods (for example, Delphi, Deliberative Dialogue) can be used to develop evidence-based solutions by addressing the groups’ needs and priorities. Limited research has examined how consensus methods are used by research partnerships. Aims and objectives: Using the PRISMA-ScR checklist as a guide, this scoping review sought to better understand the use of consensus methods in research partnerships. Methods: The search strategy involved four databases (MEDLINE, PsycINFO, EMBASE and CINAHL Plus). A total of 6,654 citations were screened, 404 were advanced for full text review, and 34 studies met eligibility criteria. Data from the 34 studies were extracted and iteratively analysed by three members of our research team. Findings: At least 11 different consensus methods were used with variations of the Delphi being most common. Issues of inclusion and power dynamics were rarely discussed. Overall, there was limited reporting of consensus methods, partnership approaches, and/or power dynamics. Discussion and conclusions: This review extends the literature by providing an overview of consensus methods that have been conducted in research partnerships and how they have been executed. We offer initial considerations for conducting and reporting on the use of consensus methods in research co-production.

Principal component analysis yields results comparable to those of an elaborate Boolean strategy: simplifying the assessment of measurable residual disease in chronic lymphocytic leukemia patients.

Measurable residual disease (MRD) is becoming increasingly important in the chronic lymphocytic leukemia (CLL) context. It is of independent prognostic significance in terms of favorable progression-free and overall survival. The standardized methods used to assess CLL MRD are based on flow cytometry and real-time quantitative PCR. We here present a nine-color assay for CLL MRD with the ROR-1 marker antigen as recommended by the European Research Initiative (ERIC) on CLL; the sensitivity is at least 10-5. We used 54 samples to develop a new principal component analysis (PCA) method based on the Kaluza© "radar" presentation mode. We used a Navios flow cytometer (Beckman Coulter©). We confirmed the linearity of our method over more than five dilutions. The specificity limit was 1.3×10-6 and the lower limit of detection was 3.6×10-6. Compared to the Boolean method, the sensitivity, specificity, and positive and negative predictive values of our PCA method were 100%. When MRD was detectable, PCA and Boolean assays were in agreement (linear regression, R2=0.99). We developed a new PCA-based method for detection of CLL MRD. Our method is comparable to that of the consensus method in terms of sensitivity, and it is also much easier and faster.

Analysis of Consensus Mechanisms: PoW and PoS

Along with the trend of Bitcoin blockchain, the concept behind all virtual currency has be-come popular in the study of the Internet. This essay mainly researches two kinds of common consensus mechanisms for the current blockchain network and looks forward to the future development of the technologys usage in daily life. This research aims to overview the two most common consensus mechanisms in the construction of blockchain. By reviewing re-sources from other research, an explanation of the goal of the consensus method, the ad-vantages, and disadvantages of each approach and the future development of these two meth-ods are summarized and developed. The result of the review explains the shifts of mature vir-tual currencies from proof of work to proof of stake and advises what mechanism should be used at starting stage and why a shift is necessary for proof of stake currencies.

Optimizing Blockchain Network Creation: Automation with Ansible on Private Blockchain Hyperledger Fabric Using Simplified RAFT Consensus Method

In the rapidly evolving world of blockchain technology, efficient and reliable blockchain network creation poses a significant challenge. Manual processes in blockchain network setup often consume time, are prone to errors, and difficult to maintain. This research aims to optimize the creation of blockchain networks by leveraging Ansible automation tools on private blockchains using Hyperledger Fabric and implementing a simplified RAFT method. The approach involves configuring blockchain infrastructure with Ansible and integrating the simplified RAFT method into the private blockchain network. The test results demonstrate that the proposed approach significantly reduces the time required for blockchain network creation. In testing with a 92 Mbps internet connection, the time needed to create a blockchain network with 1 orderer and 1 peer with 44 connected channels, ready for transactions, was successfully reduced from 102.6 minutes to only 51.4 minutes. Moreover, the Ansible automation approach reduces the risk of errors and simplifies network maintenance. In conclusion, this research confirms the effectiveness of the proposed approach in optimizing the blockchain network creation process, reducing the required time, and enhancing efficiency and ease of maintenance. The proposed solution provides a valuable contribution to the development of efficient private blockchain infrastructure while minimizing errors and increasing flexibility.

Data-driven robust cost consensus model with individual adjustment willingness in group decision-making

In the consensus reaching process, the moderator, as the representative of collective interests, needs to consume certain resources to help decision-makers (DMs) reach a consensus. However, in real life, when the adjustment opinions provided by the moderator are too different from the initial opinions of the DMs, they may not accept the adjustment. On the other hand, it is difficult for the moderator to determine the unit consensus cost of every DM. However, existing consensus methods ignore the above two problems. Therefore, a data-driven robust minimum cost consensus model with individual adjustment willingness (DDR-MCCM-IAW) is proposed. First, an IAW function based on the approximation degree between the adjustment opinion and the original opinion is provided to construct the MCCM-IAW. Subsequently, principal component analysis and kernel density estimation are combined to obtain a data-driven uncertainty set of unit consensus cost, to reduce the conservatism of classical robust cost consensus models. Meanwhile, the tractable DDR-MCCM-IAW is obtained by using linear dual theory. Finally, to test the effectiveness and rationality of the proposed method, some experiments and comparative analysis are presented.

Efficient and Accurate Vehicle Localization Based on LiDAR Place Recognition

An efficient and accurate LiDAR place recognition methodology is proposed for vehicle localization. First, the Iris-LOAM is proposed to overcome the disadvantages of low accuracy of loop-closure detection and low efficiency of map construction in the existing LOAM-series methods. The method integrates the LiDAR-Iris global descriptor and Normal Distribution Transform (NDT) registration method into the loop-closure detection module of LiDAR Odometry and Mapping (LOAM), thereby improving the accuracy and efficiency of map construction. For the shortcomings of low map loading and matching efficiency, the Random Sample Consensus method is used to remove the ground point cloud information. The Voxel Grid method is used to down sample the loaded map. Finally, the NDT method is adopted for point cloud map matching to obtain the position information. Show that the Iris-LOAM has higher efficiency than the SC-LeGO-LOAM. The average time of point cloud map matching is reduced by 39.5%. The place recognition can be executed to achieve accuracy vehicle localization.

Core sample consensus method for two-view correspondence matching

Core sample consensus method for two-view correspondence matching

Educator's blueprint: A primer on consensus methods in medical education research.

Consensus methods such as the Delphi and nominal group techniques are increasingly utilized within medical education research. This educator's blueprint paper provides practical strategies regarding five key steps for ensuring best practices when using consensus methods. These strategies include deciding which consensus method is best, developing the initial questionnaire, identifying the participants, determining the number of rounds and consensus threshold, and describing and justifying any modifications. These strategies will help guide education researchers on their next study using consensus methods.

Transperineal laser ablation of the prostate as a treatment for benign prostatic hyperplasia and prostate cancer: The results of a Delphi consensus project

ObjectiveTo evaluate transperineal laser ablation (TPLA) with Echolaser® (Echolaser® TPLA, Elesta S. p.a, Calenzano, Italy) as a treatment for benign prostatic hyperplasia (BPH) and prostate cancer (PCa) using the Delphi consensus method. MethodsItalian and international experts on BPH and PCa participated in a collaborative consensus project. During two rounds, they expressed their opinions on Echolaser® TPLA for the treatment of BPH and PCa answering online questionnaires on indications, methodology, and potential complications of this technology. Level of agreement or disagreement to reach consensus was set at 75%. If the consensus was not achieved, questions were modified after each round. A final round was performed during an online meeting, in which results were discussed and finalized. ResultsThirty-two out of forty invited experts participated and consensus was reached on all topics. Agreement was achieved on recommending Echolaser® TPLA as a treatment of BPH in patients with ample range of prostate volume, from <40 mL (80%) to >80 mL (80%), comorbidities (100%), antiplatelet or anticoagulant treatment (96%), indwelling catheter (77%), and strong will of preserving ejaculatory function (100%). Majority of respondents agreed that Echolaser® TPLA is a potential option for the treatment of localized PCa (78%) and recommended it for low-risk PCa (90%). During the final round, experts concluded that it can be used for intermediate-risk PCa and it should be proposed as an effective alternative to radical prostatectomy for patients with strong will of avoiding urinary incontinence and sexual dysfunction. Almost all participants agreed that the transperineal approach of this organ-sparing technique is safer than transrectal and transurethral approaches typical of other techniques (97% of agreement among experts). Pre-procedural assessment, technical aspects, post-procedural catheterization, pharmacological therapy, and expected outcomes were discussed, leading to statements and recommendations. ConclusionEcholaser® TPLA is a safe and effective procedure that treats BPH and localized PCa with satisfactory functional and sexual outcomes.

Large-scale pathogenicity prediction analysis of cancer-associated kinase mutations reveals variability in sensitivity and specificity of computational methods.

Mutations in kinases are the most frequent genetic alterations in cancer; however, experimental evidence establishing their cancerous nature is available only for a small fraction of these mutants. Predicition analysis of kinome mutations is the primary aim of this study. Further objective is to compare the performance of various softwares in pathogenicity prediction of kinase mutations. We employed a set of computational tools to predict the pathogenicity of over forty-two thousand mutations and deposited the kinase-wise data in Mendeley database (Estimated Pathogenicity of Kinase Mutants [EPKiMu]). Mutations are more likely to be drivers when being present in the kinase domain (vs. non-kinase domain) and belonging to hotspot residues (vs. non-hotspot residues). We identified that, while predictive tools have low specificity in general, PolyPhen-2 had the best accuracy. Further efforts to combine all four tools by consensus, voting, or other simple methods did not significantly improve accuracy. The study provides a large dataset of kinase mutations along with their predicted pathogenicity that can be used as a training set for future studies. Furthermore, a comparative sensitivity and selectivity of commonly used computational tools is presented. Primary-structure-based in silico tools identified more cancerous/deleterious mutations in the kinase domains and at the hot spot residues while having higher sensitivity than specificity in detecting deleterious mutations.

Phylogenetic congruence, conflict and consilience between molecular and morphological data

Morphology and molecules are important data sources for estimating evolutionary relationships. Modern studies often utilise morphological and molecular partitions alongside each other in combined analyses. However, the effect of combining phenomic and genomic partitions is unclear. This is exacerbated by their size imbalance, and conflict over the efficacy of different inference methods when using morphological characters. To systematically address the effect of topological incongruence, size imbalance, and tree inference methods, we conduct a meta-analysis of 32 combined (molecular + morphology) datasets across metazoa. Our results reveal that morphological-molecular topological incongruence is pervasive: these data partitions yield very different trees, irrespective of which method is used for morphology inference. Analysis of the combined data often yields unique trees that are not sampled by either partition individually, even with the inclusion of relatively small quantities of morphological characters. Differences between morphology inference methods in terms of resolution and congruence largely relate to consensus methods. Furthermore, stepping stone Bayes factor analyses reveal that morphological and molecular partitions are not consistently combinable, i.e. data partitions are not always best explained under a single evolutionary process. In light of these results, we advise that the congruence between morphological and molecular data partitions needs to be considered in combined analyses. Nonetheless, our results reveal that, for most datasets, morphology and molecules can, and should, be combined in order to best estimate evolutionary history and reveal hidden support for novel relationships. Studies that analyse only phenomic or genomic data in isolation are unlikely to provide the full evolutionary picture.

Output-feedback anti-disturbance consensus for multi-agent systems with application to secondary voltage regulation for microgrids

This paper investigates a distributed finite-time consensus problem for second-order multi-agent systems (MASs) with disturbances and unmeasurable states. Output-feedback anti-disturbance consensus protocols are designed by finite-time observer (FTO) methods and the nonsingular integral terminal sliding-mode control (NITSMC). Some FTOs are first introduced for the agents to estimate the disturbances and unmeasurable states together. Then, the nonsingular integral terminal sliding-mode surfaces are proposed, based on which consensus protocols are proposed. Moreover, the consensus methods are also applied to microgrids (MGs). Based on MG systems, output voltages achieve consensus through secondary regulation. Simulations verify the effectiveness.

Dopamine agonist therapy in Parkinson’s disease: Spanish expert consensus on its use in different clinical situations

BackgroundDifferent types of therapies were proven effective for the medical management of motor and non-motor symptoms in Parkinson’s disease (PD). We aimed to gain consensus on the dopamine agonist (DA) therapy use in different clinical scenarios of Parkinson’s disease (PD) patients. MethodsThis consensus study was based on the nominal group technique. Initially, a consensus group comprising 12 expert neurologists in the PD field identified the topics to be addressed and elaborated different evidence-based preliminary statements. Next, a panel of 48 Spanish neurologists expressed their opinion on an internet-based systematic voting program. Finally, initial ideas were reviewed and rewritten according to panel contribution and were ranked by the consensus group using a Likert-type scale. The analysis of data was carried out by using a combination of both qualitative and quantitative methods. The consensus was achieved if the statement reached ≥ 3.5 points in the voting process. ResultsThe consensus group produced 76 real-world recommendations. The topics addressed included 12 statements related to DA therapy in early PD, 20 statements concerning DA treatment strategy in patients with motor complications, 11 statements associated with DA drugs and their side effects, and 33 statements regarding DA therapy in specific clinical scenarios. The consensus group did not reach a consensus on 15 statements. ConclusionThe findings from this consensus method represent an exploratory step to help clinicians and patients in the appropriate use of DA in different stages and clinical situations of PD.