Set Of Teams Research Articles

The constitution, functions and skill sets of teams

The constitution, functions and skill sets of teams

The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT.

Healthcare crowdsourcing events (e.g. hackathons) facilitate interdisciplinary collaboration and encourage innovation. Peer-reviewed research has not yet considered a healthcare crowdsourcing event focusing on generative artificial intelligence (GenAI), which generates text in response to detailed prompts and has vast potential for improving the efficiency of healthcare organizations. Our event, the New York University Langone Health (NYULH) Prompt-a-thon, primarily sought to inspire and build AI fluency within our diverse NYULH community, and foster collaboration and innovation. Secondarily, we sought to analyze how participants' experience was influenced by their prior GenAI exposure and whether they received sample prompts during the workshop. Executing the event required the assembly of an expert planning committee, who recruited diverse participants, anticipated technological challenges, and prepared the event. The event was composed of didactics and workshop sessions, which educated and allowed participants to experiment with using GenAI on real healthcare data. Participants were given novel "project cards" associated with each dataset that illuminated the tasks GenAI could perform and, for a random set of teams, sample prompts to help them achieve each task (the public repository of project cards can be found at https://github.com/smallw03/NYULH-Generative-AI-Prompt-a-thon-Project-Cards). Afterwards, participants were asked to fill out a survey with 7-point Likert-style questions. Our event was successful in educating and inspiring hundreds of enthusiastic in-person and virtual participants across our organization on the responsible use of GenAI in a low-cost and technologically feasible manner. All participants responded positively, on average, to each of the survey questions (e.g., confidence in their ability to use and trust GenAI). Critically, participants reported a self-perceived increase in their likelihood of using and promoting colleagues' use of GenAI for their daily work. No significant differences were seen in the surveys of those who received sample prompts with their project task descriptions. The first healthcare Prompt-a-thon was an overwhelming success, with minimal technological failures, positive responses from diverse participants and staff, and evidence of post-event engagement. These findings will be integral to planning future events at our institution, and to others looking to engage their workforce in utilizing GenAI.

Special considerations in managing pain and psychosocial distress in patients with opioid use disorder and cancer: the role of the supportive care and psycho-oncology interdisciplinary team.

People with a substance use disorder (SUD) have shortened lifespans due to complications from their substance use and challenges engaging with traditional health care settings and institutions. This impact on life expectancy is especially prominent in patients with co-occurring SUDs and cancer, and often has a much worse prognosis from the cancer than a similar patient without a SUD. Palliative care teams are experts in serious illness communication and symptom management and have become increasingly embedded in the routine care of patients with cancer. We argue that the skill set of palliative care teams is uniquely suited for addressing the needs of this oft marginalized group. We provide a comprehensive review of tools for addressing these needs, including medications that can both treat pain and opioid use disorder (OUD), and highlight psychosocial approaches to treating patients with OUD and cancer in a way that is respectful and effective. Using a trauma informed framework, we focus on the application of harm reduction principles from addiction medicine and the principles of clear communication, accompaniment, and emotional presence from palliative care to maximize support. We also focus on ways to reduce stigma in the delivery of care, by providing language that reduces barriers and increases patient engagement. Finally, we describe a clinic embedded within our institution's cancer center which aims to serve patients with cancer and SUDs, built on the framework of harm reduction, accompaniment and trauma informed care (TIC). Overall, we aim to provide context for addressing the common challenges that arise with patients with cancer and OUD, including the direct impact of psychosocial stress on substance use and cancer treatment, delays in disease directed treatment that can potentially impact further treatment options and outcomes, challenging pain management due to greater opioid debt, and potential loss of primary coping mechanism through substance use in the face of potential terminal diagnosis.

Challenges of liver transplantation programs in low‐ and middle‐income countries: An experience from Sri Lanka

AbstractLiver diseases lead to 1.3 million deaths per year around the world, the majority of which are secondary to cirrhosis. In the management of liver diseases in chronic and acute conditions, liver transplant (LT) plays a major role in improving the survival and quality of life of patients. LT programmes require the technical capabilities in performing the pre‐transplant evaluation, transplant surgery and post‐transplant care supported by adequate infrastructure and a set of trained teams. Globally, there were 28,000 deceased donor LTs, and 14,000 living donor LTs were performed in 2021. In the South Asia region, India, Pakistan and Sri Lanka conducted 2998 LTs in 2021. Many countries report sociocultural, religious and legislative barriers to acquiring adequate donor livers. We describe the challenges in LT programmes in low‐ and middle‐income countries and experiences from Sri Lanka. Sri Lanka carried out its first LT in 2010, and the service is provided free of charge in the state health sector. In Sri Lanka, the common indications for LT in adults are non‐alcoholic steatohepatitis, cirrhosis, hepatocellular carcinoma and alcoholic liver disease. In children, the indications are biliary atresia, hepatocellular carcinoma and Wilson disease. The common challenges include a lack of an adequate number of doctors and post‐transplant team members, a low number of organ donors and a long waiting list, all of which can be disadvantageous for transplant programmes. To continue providing LT services, there is a need to adopt multimodal strategies in the areas of providing additional skills training to the operating team and promoting organ donation culture in the background of supportive organ donation legislation. With the adoption of the national strategic plan for organ, tissue and cell transplantation, the country hopes to strengthen its capacity of providing transplant services to its people.

Consistent social ranking solutions

The performance of coalitions is an important measure for evaluating individuals. Sport players, researchers, and firm workers are often judged with their team performances. The social ranking solution (SRS) is a function that maps the ranking on the set of all feasible coalitions (the domain of coalitions) into the ranking of individuals. Importing the axiom of consistency from voting theory, we study consistent SRSs under the variable domains of coalitions. We suppose that there are several domains of coalitions (e.g., a set of research teams made up of only young researchers and a set of research teams including senior researchers), and the individuals are required to be evaluated consistently on each domain of coalition. Such a situation is typical because all the logically possible coalitions are often too huge to deal with. We obtain a new characterization of the lexicographic excellence solution (LES) and its dual (DLES): they are the only SRSs satisfying consistency, neutrality, weak coalitional anonymity, and complete dominance. This characterization is expected to provide a new ground for determining the impacts of individuals based on the lexicographic comparisons of their team performances.

МОДЕЛЬ СИСТЕМНОГО ЛИДЕРСТВА В ЦИФРОВОМ УПРАВЛЕНИИ РЕСУРСАМИ, УЧИТЫВАЮЩАЯ ДИНАМИЧЕСКИЕ ВОЗМОЖНОСТИ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ

The purpose of this article is to develop conceptual provisions on the formation of an educational organization management model taking into account dynamic capabilities and the development of ecosystems in the field of education. The methodology of the research is the use of resource-based approaches to the management of an educational organization in the context of digitalization of activities and educational processes. The results consist in the development of a model representing a combination of a system leader and a set of project management teams that, within the framework of an educational organization, ensure the formation of new technologies for using resources within an already virtual space (in the form of educational ecosystems). Conclusions: system leadership can be implemented through ecosystem integration of educational organizations with methodical subordination to the system leader of a successful organization and his team.

Pay for performance in Brazilian primary health care: quality of work processes, actions and services

PurposeIn 2011, Brazil introduced a national pay-for-performance (P4P) scheme called the National Program for Improving Primary Health Care Access and Quality (PMAQ), rolled out over three cycles and reaching more than 5,000 municipalities and 40,000 family health teams (FHTs). There is little evidence on how the PMAQ was implemented locally and whether this variation in implementation affects performance, particularly, in terms of work process indicators. This study compared different cases of municipal-level PMAQ implementation (bonuses paid or not to FHTs) over the last two program cycles to analyze the quality of the work processes, actions and services of FHTs.Design/methodology/approachThis was a cross-sectional analytical study using secondary data from an external evaluation of the Brazilian PMAQ. In total, 27,500 FHTs participated in the evaluation. They were divided into four clusters based on whether or not municipalities paid bonuses to workers during cycles 2 and 3 of the program (2013–2019). Variables regarding work processes, actions and services were classified as “Quality Assurance – QA” or “Continued Quality Improvement – CQI”, and an individual score was assigned based on the average score of each variable.FindingsThe four clusters displayed an increase in overall QA and CQI scores between the two program cycles; though this increase was small between the set of primary health care teams that received bonuses and those that did not.Originality/valueThis paper contributes to bridging the gap in the scientific literature for evaluative studies on the relationship between direct payment for performance to health professionals and better quality actions and services in low and middle-income countries.

Creating Strategies for Enhancing Complex New Product Development: Cluster Analysis of DEA Results

Firms need to constantly innovate to survive and remain competitive in the marketplace. Despite this, little research has examined the dynamics that affect innovation in large-scale, complex organizations that leverage multiple teams. This study utilizes data envelopment analysis output from a sample of new product development teams to create clusters based on how teams need to change communication-related inputs to increase creative efficiency. The study results exemplify how this approach can provide recommendations that sets of teams can implement, optimizing the use of resources compared to making individual adjustments. Implications are provided for new product development and large multinational enterprises.

Drafting strategies in fantasy football: A study of competitive sequential human decision making

AbstractDrafting is a competitive task in which a set of decision makers choose from a set of resources sequentially, with each resource becoming unavailable once selected. How people make these choices raises basic questions about human decision making, including people’s sensitivity to the statistical regularities of the resource environment, their ability to reason about the behavior of their competitors, and their ability to execute and adapt sophisticated strategies in dynamic situations involving uncertainty. Sports provides one real-world example of drafting behavior, in which a set of teams draft players from an available pool in a well-regulated way. Fantasy sport competitions provide potentially large data sets of drafting behavior. We study fantasy football drafting behavior from the 2017 National Football League (NFL) season based on 1350 leagues hosted by the http://sleeper.app platform. We find people are sensitive to some important environmental regularities in the order in which they draft players, but also present evidence that they use a more narrow range of strategies than is likely optimal in terms of team composition. We find little to no evidence for the use of the complicated but well-documented strategy known as handcuffing, and no evidence of irrational influence from individual-level biases for different NFL teams. We do, however, identify a set of circumstances for which there is clear evidence that people’s choices are strongly influenced by the immediately preceding choice made by a competitor.

Exact and greedy algorithms of allocating experts to maximum set of programmer teams

The allocation of experts to programmer teams, which meet constraints on professional competences related to programming technologies, languages and tools an IT project specifies is a hard combinatorial problem. This paper solves the problem of forming the maximum number of teams whose experts meet all the constraints within each team. It develops and compares two algorithms: a heuristic greedy and exact optimal. The greedy algorithm iteratively solves the set cover problem on a matrix of expert competences until can create the next workable team of remaining experts. The paper proves that the allocation greedy algorithm is not accurate even if the set cover algorithm is exact. We call the allocation algorithm as double greedy if the set cover algorithm is greedy. The exact algorithm we propose finds optimal solution in three steps: generating a set of all non-redundant teams, producing a graph of team’s independency, and searching for a maximum clique in the graph. The algorithm of generating the non-redundant teams traverses a search tree constructed in such a way as to guarantee the creation of all non-redundant teams and absorbing all redundant teams. The edges of the non-redundant team independency graph connect teams that have no common expert. The maximum clique search algorithm we propose accounts for the problem and graph features. Experimental results show that the exact algorithm is a reference one, and the double-greedy algorithm is very fast and can yield suboptimal solutions for large-size allocation problems.

Assessment on the Integration of the Basic Education Department of Notre Dame of Marbel University: Input for Strategic Management Plan

The term integration refers to merging the Elementary and High School Departments. The merging entailed alignment of the curriculum and management system from kindergarten to the secondary levels, where there is a unified set of administrative teams for both elementary and high school to plan, implement, monitor, and evaluate the curriculum and other administrative components. Using a descriptive research design, this study assessed the implementation of the integrated system of basic education at Notre Dame of Marbel University. Specifically, this study has determined the level of satisfaction of the personnel and retirees on the implementation of the integrated system of the basic education department of Notre Dame of Marbel University; and determining the strengths and weaknesses of the implementation of the integrated system as perceived by the personnel and retirees of NDMU-IBED. The result of the study reveals that all the areas being assessed, such as the Organizational Structure, Academic/Instructional Management, Program Implementation Scheme, Human Relationship, Leadership, and Participation, have obtained very satisfactory results. Strengths and Weaknesses were also identified in each of the areas mentioned. It can be concluded that the integrated system being implemented in the basic education of Notre Dame of Marbel University has brought more positive changes in terms of the organizational structure, academic management, program implementation monitoring scheme, human resource relationship, leadership, and participation.

Teaching & learning guide for: Risky‐choice framing and rational decision‐making

Teaching & learning guide for: Risky‐choice framing and rational decision‐making

Carbon footprinting of carbon capture and -utilization technologies: discussion of the analysis of Carbon XPRIZE competition team finalists

Abstract Life cycle assessments (LCAs) of early-stage technologies can provide valuable insights about key drivers of emissions and aid in prioritizing research into further emissions-reduction opportunities. Despite this potential value, further development of LCA methods is required to handle the increased uncertainty, data gaps, and confidentially of early-stage data. This study presents a discussion of the life cycle carbon footprinting of technologies competing in the final round of the NRG COSIA Carbon XPRIZE competition—a US$20 million competition for teams to demonstrate the conversion of CO2 into valuable products at the scale of a small industrial pilot using consistent deployment conditions, boundaries, and methodological assumptions. This competition allowed the exploration of how LCA can be used and further improved when assessing disparate and early-stage technologies. Carbon intensity estimates are presented for two conversion pathways: (i) CO2 mineralization and (ii) catalytic conversion (including thermochemical, electrochemical, photocatalytic and hybrid process) of CO2, aggregated across teams to highlight the range of emissions intensities demonstrated at the pilot for individual life cycle stages. A future scenario is also presented, demonstrating the incremental technology and deployment conditions that would enable a team to become carbon-avoiding relative to an incumbent process (i.e. reducing emissions relative to a reference pathway producing a comparable product). By considering the assessment process across a diverse set of teams, conversion pathways and products, the study presents generalized insights about opportunities and challenges facing carbon capture and -utilization technologies in their next phases of deployment from a life cycle perspective.

A Practical Approach to Introducing Pre-Hospital Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA), the Problems Encountered and Lessons Learned

Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) is an endovascular procedure which utilises a catheter- based balloon device to achieve aortic occlusion. The aim of this resuscitative measure is to improve blood pressure proximal to the occlusion site and therefore preserve cardiac and cerebral perfusion to prevent cardiac arrest. In addition, there is a relative reduction in arterial flow to the site of injury distal to the balloon. Endovascular techniques are gaining acceptance for the in-hospital management of haemorrhage; however, their use in pre-hospital care is still limited. This is due to several factors including the technical challenges, training and skill sets of pre-hospital care teams and the potential for harm of REBOA, particularly with extended balloon occlusion times. However, non-com pressible torso haemorrhage is associated with a mortality of approximately 50% and a significant proportion of these deaths occur in the pre-hospital phase of care. In the exsanguinating patient, resuscitative thoracotomy with direct aortic compression is often the only means to control haemorrhage. This resuscitative measure is now a more established pre-hospital intervention which has significantly improved outcomes in the context of penetrating trauma, particularly thoracic injury. However, in the context of blunt injury and subdiaphragmatic haemorrhage, the outcomes from pre-hospital resuscitative thoracotomy remain poor. We present our initial technique for successfully introducing REBOA for the pre-hospital management of exsanguinating pelvic or groin haemorrhage following trauma, our indications for REBOA and comments on the problems and limitations encountered, as well as the lessons learned.

Recursive Constraint Manifold Subsearch for Multirobot Path Planning with Cooperative Tasks

The Cooperative Path Planning (CPP) problem seeks to determine a path for a group of robots which form temporary teams to perform tasks. The multi-scale effects of simultaneously coordinating many robots distributed across the workspace while also tightly coordinating the members of teams increases the difficulty of planning. Previous research produced the Constraint Manifold Subsearch (CMS) algorithm that can find minimal length paths to the CPP problem. However, CMS as currently formulated cannot handle more general cost functions, such as minimizing energy expenditure, and cannot handle task schedules that require multiple input teams to merge to form a set of multiple output teams. Furthermore, as CMS must couple planning for all interacting teams, it does not scale well to very large environments. In this paper, we rederive the CMS algorithm using a task graph to reason about inter-team dependencies, allowing the use of more general cost functions and task schedules. We then introduce the recursive CMS (rCMS) algorithm that exploits the reformulation to split the CPP into independent subproblems, significantly reducing computational complexity. Simulation studies show that rCMS can solve substantially larger problems than CMS.

A set partitioning based goal programming model for the team formation problem

AbstractIn this paper, we offer a multi‐objective set‐partitioning formulation for team formation problems using goal programming. Instead of selecting team members to teams, we select suitable teams from a set of teams. This set is generated using a heuristic algorithm that uses the social network of potential team members. We then utilize the proposed multi‐objective formulation to select the desired number of teams from this set that meets the skill requirements. Therefore, we ensure that selected teams include individuals with the required skills and effective communication with each other. Two real datasets are used to test the model. The results obtained with the proposed solution are compared with two well‐known approaches: weighted and lexicographic goal programming. Results reveal that weighted and lexicographic goal programming approaches generate almost identical solutions for the datasets tested. Our approach, on the other hand, mostly picks teams with lower communication costs. Even in some cases, better solutions are obtained with the proposed approach. Findings show that the developed solution approach is a promising approach to handle team formation problems.

Examining the Influence of Power Distance on Psychological Safety Within Healthcare Teams

Cultivating good teamwork practices within healthcare teams is important for providing effective patient care and preventing adverse health outcomes. Psychological safety is one factor which is instrumental in developing a positive team environment, which fosters effective teamwork. The historically hierarchical nature of healthcare ascribes status to individuals based on profession, and this power differential is a contributing factor to a team member’s psychological safety. This study seeks to identify relationships between cultural backgrounds and teamwork in healthcare through examining how power distance influences psychological safety within healthcare teams. A cross-sectional questionnaire containing the Psychological Safety Scale and the Personal Cultural Orientation Scale was fielded to sets of Internal medicine teams working in a health system located in the Midwest region of the United States ( n=17). Levels of power-distance and psychological safety were similar amongst leaders and their team members. Upon comparison, there was no correlation found between power distance and psychological safety. Moderate to significant correlations were found between other deep cultural constructs.

A Roadmap to Inform the Implementation of Evidence-Based Collaborative Care Interventions in Communities: Insights From the Michigan Mental Health Integration Partnership.

Background: Despite increasing calls for further spread of evidence-based collaborative care interventions (EBIs) in community-based settings, practitioner-driven efforts are often stymied by a lack of experience in addressing barriers to community-based implementation, especially for those not familiar with implementation science. The Michigan Mental Health Integration Partnership (MIP) is a statewide initiative that funds projects that support implementation and uptake of EBIs in community-based settings. MIP also provides an in situ implementation laboratory for understanding barriers to the uptake of EBIs across a variety of settings. We report findings from a statewide qualitative study of practitioners involved in MIP projects to garner their perspectives of best practices in the implementation of EBIs.Methods: Twenty-eight semi-structured interviews of practitioners and researchers from six MIP Projects were conducted with individuals implementing various MIP EBI projects across Michigan, including stakeholders from project teams, implementation sites, and the State of Michigan, to identify common barriers, challenges, and implementation strategies deployed by the project teams, with the purpose of informing a set of implementation steps and milestones.Results: Stakeholders identified a number of barriers to and strategies for success, including the need for tailoring program deployment and implementation to specific site needs, development of web-based tools for facilitating program implementation, and the importance of upper-level administration buy-in. Findings informed our resultant community-based Implementation Roadmap, which identifies critical steps across three implementation phases—pre-implementation, implementation, and sustainability—for implementation practitioners to use in their EBI implementation efforts.Conclusion: Implementation practitioners interested in community-based EBI implementation often lack access to operationalized implementation “steps” or “best practices” that can facilitate successful uptake and evaluation. Our community-informed MIP Implementation Roadmap, offering generalized steps for reaching successful implementation, uses experiences from a diverse set of MIP teams to guide practitioners through the practices necessary for scaling up EBIs in community-based settings over pre-implementation, implementation and sustainability phases.

Integer programming approaches to the multiple team formation problem

Given a group of individuals, each one with a single skill, and a social network capturing the mutual affinity among them, the Multiple Team Formation Problem (MTFP) consists in finding a set of teams, as harmonious as possible, each one comprising a given number of required skills. Dedication time of individuals can be partitioned into time fractions, thus allowing an individual to work in more than one team. In this work, we propose an Integer Linear Programming (ILP) formulation and sets of valid inequalities for the problem. Computational experiments carried out on test instances, generated according to the literature or based on real-world social networks, attest that the ILP model strengthened by valid inequalities consistently outperforms the existing quadratic formulation for MTFP.

Organizing sports matches with a hybrid monkey search algorithm

This academic piece of the paper illustrates an approach of organizing sports matches to be as a tool of sports schedule maker via a proposed hybrid Monkey search algorithm by doubles elimination tournament. Input are a set of teams represented by monkeys. It states that the natural behavior of monkeys and its climbing to obtain (solution) through uphill (climbing), watch-jumping, and somersault process. The parameters in the climb were represented by whether or not sports team won. The distribution of the teams, whether in the upper or the lower half, represented in the watch-jumping by mathematical equations, in addition to representing the variables in somersault process. The consequences behind the suggested algorithm used have tackled steps to reach an optimal schedule for a variety of teams for the same championship. The team cannot play more than two consecutive matches with the condition of starting with a random population of feasible solutions. The performance of the presented algorithm was very well through providing a flexible and easy organization of sports matches without using classic or manual routine. Furthermore, the search space reduced so that can give a guarantee to achieve a globally optimum solution. The software platform was MATLAB m-files.