A group intervention to improve quality of life for people with advanced dementia living in care homes: the Namaste feasibility cluster RCT

Background People with advanced dementia who live and die in nursing homes experience variable quality of life, care and dying. There is a need to identify appropriate, cost-effective interventions that facilitate high-quality end-of-life care provision. Objectives To establish the feasibility and acceptability to staff and family of conducting a cluster randomised controlled trial of the Namaste Care intervention for people with advanced dementia in nursing homes. Design The study had three phases: (1) realist review and (2) intervention refinement to inform the design of (3) a feasibility cluster randomised controlled trial with a process evaluation and economic analysis. Clusters (nursing homes) were randomised in a 3 : 1 ratio to intervention or control (usual care). The nature of the intervention meant that blinding was not possible. Setting Nursing homes in England providing care for people with dementia. Participants Residents with advanced dementia (assessed as having a Functional Assessment Staging Test score of 6 or 7), their informal carers and nursing home staff. Intervention Namaste Care is a complex group intervention that provides structured personalised care in a dedicated space, focusing on enhancements to the physical environment, comfort management and sensory engagement. Main outcome measures The two contender primary outcome measures were Comfort Assessment in Dying – End of Life Care in Dementia for quality of dying (dementia) and Quality of Life in Late Stage Dementia for quality of life. The secondary outcomes were as follows: person with dementia, sleep/activity (actigraphy), neuropsychiatric symptoms, agitation and pain; informal carers, satisfaction with care at the end of life; staff members, person-centred care assessment, satisfaction with care at the end of life and readiness for change; and other data – health economic outcomes, medication/service use and intervention activity. Results Phase 1 (realist review; 86 papers) identified that a key intervention component was the activities enabling the development of moments of connection. In phase 2, refinement of the intervention enabled the production of a user-friendly 16-page A4 booklet. In phase 3, eight nursing homes were recruited. Two homes withdrew before the intervention commenced; four intervention and two control homes completed the study. Residents with advanced dementia (n = 32) were recruited in intervention (n = 18) and control (n = 14) homes. Informal carers (total, n = 12: intervention, n = 5; control, n = 7) and 97 staff from eight sites (intervention, n = 75; control, n = 22) were recruited over a 6-month period. Recruitment is feasible. Completion rates of the primary outcome questionnaires were high at baseline (100%) and at 4 weeks (96.8%). The Quality of Life in Late Stage Dementia was more responsive to change over 24 weeks. Even where economic data were missing, these could be collected in a full trial. The intervention was acceptable; the dose varied depending on the staffing and physical environment of each care home. Staff and informal carers reported changes for the person with dementia in two ways: increased social engagement and greater calm. No adverse events related to the intervention were reported. Conclusions A subsequent definitive trial is feasible if there are amendments to the recruitment process, outcome measure choice and intervention specification. Future work In a full trial, consideration is needed of the appropriate outcome measure that is sensitive to different participant responses, and of clear implementation principles for this person-centred intervention in a nursing home context. Trial registration Current Controlled Trials ISRCTN14948133. Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 6. See the NIHR Journals Library website for further project information

Dynamic supply chain capabilities : a case of oil and gas industry in Malaysia

Supply chain (SC) is a dynamic process that entails continuous flow of information, materials and funds across multiple functional areas, within and between chain members to meet customer’s requirements and to maximize profit. However, organizations may encounter problems related to the dynamic process in SC. Oil and gas (O&G) industry is one of the SC entities which require dynamic processes of capabilities due to high degree of uncertainties. Motivated by the complexity and uncertainty of SC, this study intends to understand the concept of dynamic supply chain capabilities in the organizations specifically in Malaysia environment. The study focuses on the firm’s capabilities dimensions as well as the influence of the environmental uncertainties on dynamic supply chain capabilities dimensions of the O&G industry. Previous literatures related to supply chain management, and dynamic capabilities were reviewed to support the study. The researcher analyzed multiple cases from the perspectives of the O&G players in Malaysia via qualitative research methodology. Nine managers of services contractors and one manager of production sharing contractor were selected for interviews to share experiences on the needs for dynamic supply chain capabilities. Results showed that value chain coordination, client, supplier and operations are important in the SC orientation; knowledge accessing and coevolving are vital to the dynamic supply chain capabilities; finally, ethics and professional values, and technology driven are important in the environmental uncertainties. Such findings are necessary for emergent framework of dynamic supply chain capabilities on how O&G industry can benefit. Hence, the main contributions of the research findings are: (i) contribution to the body of knowledge in developing better understanding on the dimensions of dynamic supply chain capabilities towards strategies; and (ii) contribution to the managerial in understanding and capturing emergent dimensions of dynamic supply chain capabilities by providing a basis for future analysis

A maturity model for digital transformation

Various disruptive digital technologies such as IoT, Artificial Intelligence, Big Data and Analytics, 3D Printing, Augmented Reality, Cybersecurity, Clouding, Autonomous Robots, Simulation, Horizontal and Vertical Integration challenge the traditional means of doing business. Also, factors such as fierce price competition due to price transparency, the increased demand for customized product and services, and so on force organizations to adapt to the rapid change in digital technologies. However, many companies have doubts about where to start their transformation process. In order to develop a roadmap, the companies should first identify their weaknesses and strengths in the context of digital transformation. Maturity models have been used for years in order to identify companies’ weaknesses and strengths. In this work, we proposed one such maturity model to determine the current readiness level of the companies in the context of digital transformation. Overall, we defined 5 dimensions and developed/adopted 76 questions for assessing digital maturity. These dimensions include “Leadership”, “Strategy”, “People”, Partnership and Resources”, and “Product, Process, and Services”. The proposed maturity model is among the few models that are based on sound theoretical frameworks already validated in earlier studies and/or widely used in the literature and practic

Central Washington University 2020-2021 Undergraduate Catalog

https://digitalcommons.cwu.edu/catalogs/1184/thumbnail.jp

Effective Utilization of Historical Data to Increase Organizational Performance: Focus on Sales/ Tendering and Projects

Master's thesis in Offshore technologyIn Oil and Gas industry there was not enough focus on this topic as cost was not a big factor in good olden days. But the sensational drop in oil prices below US$40 per barrel at the end of 2015 made the price more than 60 percent down compared to the one in previous years. It’s clear that the sector is going through one of the most transformative periods in its history. This situation has created more challenges to all O&G company leaders by forcing them to change their business strategies. The operating companies in the Oil and Gas industry have been focusing to reduce costs and increase organizational performance. Accordingly suppliers companies need to acknowledge their focus on the efficiency and optimization of resources to be able to sustain and grow in a competitive market. It demands better control of estimates and cost on future sales/tendering process. As quoted by one of the Operations Managers “An informed organization saves cost and wins faster”. The only way to get reliable information for any organization is by analyzing ‘what happened in the past’ and what we learned from it. In other words this is achieved through utilization of historical data from previous projects and by developing benchmarking metrics. Further, usage of the historical data can improve estimation and scheduling, support strategic planning, and improve the organizational processes. The historical project data or information can help in making strategic business decisions in any Organization. It can play a significant role in providing very distinct advantage over the competitors. Historical data can help the management to decide what projects are right for the future of the company and which projects can be avoided. Further, it can help to learn from past mistakes and win future bids by not repeating them. Most of the top management understands the importance of having and using historical project information or data. The problem is that very few companies have the methodologies, procedures, and systems in place to effectively use this information to improve their project processes and to support the estimation, scheduling, and control of future projects (opportunities). The present work focuses on historical data, estimation process and lessons learned for enhancing organizational performance. Further, the work includes a case study and number of expert interviews conducted at ABB. The work discusses how to collect, normalize, and analyze historical project data to develop practical information. Three models have been developed for project estimation process with a feedback loop, Lessons learned process model and Historical data utilization process. The recommendations have been made to use the historical data for establishing references for the sales/tendering department for future estimates, which can reduce the dependency on manual or a single person’s judgment and improve the estimation process. Some suggestions have also been made for establishing lessons learned process which can improve organizational performance. The results from analysis show that by applying the recommended processes, organizations can achieve efficiency through easy access and storage of historical database, easy access to lessons learned, measurable KPIs. Also use of key variables like project complexity and severity of requirements for estimation process and historical data process can form a better relation for data analysis and utilization.AB

Central Washington University 2021-2022 Undergraduate Catalog

https://digitalcommons.cwu.edu/catalogs/1186/thumbnail.jp

USAF Aircraft Maintenance Officer Knowledge, Skills and Abilities and Commonalities among the Logistics Officer Corps

This study investigated options to improve 21A training and education by first validating the Air Force\u27s logistics mission sets as Deployment, Distribution, Supply Management, Repair Network Integration, Mission Generation, Lifecycle Logistics and Joint Logistics. Then, the Knowledge, Skills, and Abilities (KSAs) considered important to execute each mission set were gathered from a representative sample of Air Force Logistics Officers via field interviews and focus groups. An analysis of results categorizes probable needs (high, medium, low) of KSAs for each mission set and assesses how well they are currently taught, if at all. Additionally, lists of KSAs that overlap multiple mission sets were created along with process options for integrating them into training and education. Based on a discussion of the synergistic effects on acquiring these KSAs, it is also recommended that the Logistics Readiness Squadron be realigned under a common group at the operational wing with the rest of the Logistics Units (presently the Maintenance Group). Finally, a career tracking model is proposed to deliberately build experts in strategic 21A career paths, which this study identifies as Career Maintenance Officers, Air Force Materiel Managers and Joint Logistics Officers

The GoBiGas Project - Demonstration of the Production of Biomethane from Biomass via Gasification

In the GoBiGas project, a first-of-its-kind industrial scale biorefinery was built for the purpose of demonstrating and enabling commercial production of biomethane from woody biomass via gasification. This report summarizes the experience, lessons learnt and conclusions from the feasibility study, construction and operation of the GoBiGas plant with the aim of supporting development of commercial production plants for advanced biofuels. The GoBiGas plant, with a production capacity of 20 MW of biomethane gas delivered to the natural gas grid in Sweden, is located in Gothenburg. The plant was built by G\uf6teborg Energi AB with the support of the Swedish Energy Agency and the project was initiated in 2005. This report includes a summary of the main contractors and technology choices made during the project and describes the commissioning of the plant in 2013. The report also describes experience gained from the operation and evaluation of the process until it was decommissioned in 2018. The evaluation of the plant focused on how the technology can be commercialized through construction of a similar stand-alone plant with a production capacity of 100 MW or more. With more than 12,000 hours of operation, the GoBiGas project has demonstrated how the quality of the product gas from a biomass gasifier can be controlled using a range of different feedstocks including bark, wood pellets, wood chips and recovered wood of class A1. Results show that a biomass to biomethane efficiency of up to 70% (based on the lower heating value of the dry ashfree fuel) is possible and that biomethane with a reduction factor for greenhouse gas emissions of over 80% can be produced with this technology. To reach such high efficiency, it is necessary to dry the feedstock and this also benefits the stability of the process. Results also show that gas quality fulfils the European standard for injection into the natural gas grid, thereby showing that large scale production of biomethane delivered by injection to the natural gas grid is possible. The project has demonstrated that this type of process can be applied on a commercial scale with high performance using known technology and that future development should involve improved compatibility between different process steps as well as improved economic feasibility of production. With the current process setup and using forest residues as feedstock, the production cost for a plant with a 200 MW production capacity, estimated based on the economic data from GoBiGas, corresponds to about SEK 600/MWh