Evaluating Project Success for Emergency Healthcare Infrastructure Based on the Cloud Matter-Element Model

PurposeThis paper aims to develop a crisis readiness framework for road traffic crisis response for law enforcement agencies in the United Arab Emirates (UAE).Design/methodology/approachA Delphi method was used that combined questionnaire-based survey and the analytical hierarchy process to collect quantitative and qualitative data from an expert panel of crisis readiness professionals on how they prioritise and weigh the different strategic criteria, sub-criteria and performance indicators in the context of law enforcement agencies’ traffic response.FindingsThe findings of this paper resulted in the identification, ranking and validation of ten key dimensions of crisis readiness clustered into three distinct sets of priority rankings: response planning, resources, training and coordination; information management and communication and risk and hazard assessment; and early warning, legal and institutional frameworks, recovery initiation and property protection. The results additionally established the relative priority of sub-criteria for each criterion and validated a broad set of key performance indicators (KPIs) for the top six ranked criteria.Research limitations/implicationsThe findings are based on a single case study focused on a specific area of operation within crisis response and one group of organisations of the UAE police sector. This potentially places a constraint on the wider generalisation of the findings to different operational areas and agencies, as they may have different priorities or organisational conditions that have implications for the framework application and the relative importance of certain criteria and sub-criteria.Practical implicationsThis paper provides strategic guidance in the form of a prioritised list of criteria, sub-criteria and KPIs that can direct efforts to optimise different dimensions of crisis readiness at a strategic and operational level.Originality/valueThis paper makes an original contribution in identifying the key criteria and performance indicators of crisis readiness for road traffic situations. The findings contribute a comprehensive strategic readiness framework that supports planning and decision-making for the development of organisational capacities that can enhance response times of police to road traffic crises. This framework ranks dimensions of crisis readiness and key sub-criteria in order of priority and validates the key components of crisis readiness that can support practitioners to structure, standardise and benchmark key processes and elements of crisis response.

IntroductionMost people with schizophrenia in China are supported by their family members in community. The patient’s family is confronted with severe care burden and pressure, which directly affects the caregiver’s...

Medical Science Liaisons (MSLs) serve a vital role in facilitating the exchange of scientific knowledge between pharmaceutical companies and health care professionals (HCPs), including pharmacists, ensuring the dissemination of accurate, evidence-based information to support clinical decision-making. Evaluating MSL performance is critical for demonstrating their value, yet defining appropriate key performance indicators (KPIs) remains challenging due to the combination of scientific engagement, relationship-building, and other activities that are difficult to measure. This study examines the current and perceived ideal use of quantitative and qualitative metrics for MSL performance evaluation, the difficulties in measuring MSL impact, and the perceived effectiveness of existing KPIs. A global survey of 1023 medical affairs professionals across 63 countries was conducted, gathering data on which KPIs are currently used versus which should be used, the preferred weighting of qualitative vs. quantitative metrics, and opinions on measurement difficulty and KPI effectiveness. The results reveal a strong preference for qualitative metrics (52%) over quantitative metrics (7%), though most organizations primarily use activity-based metrics such as the number of key opinion leader (KOL) engagements (92%). Despite these practices, many respondents believe that MSL KPIs should focus more on impact-based qualitative metrics, such as the quality of KOL/HCP relationships and/or engagements (70%) and the quality of actionable insights gathered (67%). Furthermore, 67% of participants reported it is "difficult" or "very difficult" to measure MSL performance accurately, and only 3% revealed current KPIs and metrics used to measure MSL performance are "very effective". These findings highlight a disconnect between the way MSLs are evaluated and the value they provide. This study demonstrates the need for a balanced KPI framework that integrates both qualitative and quantitative measures. A more refined performance evaluation system (incorporating stakeholder feedback, insight quality, and strategic impact) can ensure fair assessments and drive MSL effectiveness.

IntroductionThe use of electronic patient reported outcome measures (ePROMs) is increasing in routine cancer care, with benefit demonstrated in improving patient survival, satisfaction and response time. ePROMs represent a complex intervention, with successful implementation reliant upon a range of questionnaires, platform, patient and clinician characteristics alongside the wider organisational readiness and environment. Key performance indicators (KPIs) assess the performance of a system. A KPI framework would offer value in assessing ePROM implementation projects, however the outcomes and indicators of importance are not clear.MethodA modified Delphi methodology was used to define a framework of KPIs for assessing the deployment of ePROMs in routine cancer care. Potential KPIs were identified through literature searches, de-duplicated and allocated to a matrix of domains. Delphi participants were identified through a literature review and study team networks. KPIs were presented to participants for prioritisation using an online platform. A final set of KPIs was identified through two rounds of consensus with participants rating each KPI for relevance.ResultsThe literature search generated a list of 196 potential KPIs of which 48 were considered by 15 experts in the Delphi process. Consensus was reached to include 12 KPIs in the first round and a further 2 KPIs in the second round. Participant’s open text responses were analysed, suggesting a number of areas of debate regarding which KPIs are most pertinent.DiscussionThis work provides a framework of 14 KPIs, covering those of relevance to patients, clinicians and health services and recognising the acceptability, feasibility and impact of ePROMs. This framework offers a means to appraise the implementation of ePROMs, supporting teams as they implement ePROMs in routine cancer care and other healthcare settings.

Purpose When facing major emergencies, emergency healthcare facilities (EHFs) are vital in mitigating the medical pressures of traditional hospitals by providing immediate and flexible healthcare services. Performance measurement of EHF projects is crucial to ensuring that emergency medical services can respond effectively and efficiently to health demands. However, there is a lack of comprehensive understanding regarding the appropriate performance metrics that can measure the performance of these projects. This study aims to bridge this gap by identifying and assessing the quantitative metrics (QMs) for measuring the performance of EHF projects throughout their lifecycle, with a focus on their application in China. Design/methodology/approach A four-stage multi-criteria decision-making framework was employed to carry out this study. Initially, preliminary QMs for EHF projects were identified through in-depth expert interviews in China. Three rounds of Delphi surveys and statistical analysis were then conducted in China to determine the QMs most appropriate for EHF projects. Lastly, the priority of the shortlisted QMs was evaluated using the C-OWA (Combination Ordered Weighted Averaging) operator, considering three evaluation dimensions: importance, data availability, and overall suitability. Findings Twenty QMs that are most appropriate for measuring the performance of EHF projects in China are identified. Among these QMs, “schedule deviation”, “deconstruction casualty rate”, “engineering quality qualification rate”, “cost deviation”, “schedule efficiency”, and “bed density”, are deemed as the top six QMs in the overall suitability. In the overall ranking of top metrics, those related to scheduling are prominently positioned, highlighting the time-sensitivity of EHFs. Originality/value This study provides a framework for measuring emergency healthcare facility project performance, thereby addressing the theoretical void in the fields of performance measurement and emergency management. It also enables healthcare administrators, emergency management staff, and project managers to quantitatively measure the performance of EHF projects, facilitating the rapid deployment and provision of effective emergency medical care under major crises.

A significant need for flexibility and organizational performance improvement has initiated an increased implementation of the project management concept and a shift from a functional to a project-oriented organization. The need for a flexible, yet integrated management system that will provide both strategic, as well as operational excellence in organizations is caused by the uniqueness of contemporary business environment. The most common issues faced by these organizations are the alignment between projects implemented by an organization and that organization's strategy, and models for measuring project success in terms of its contribution to an organization's strategic goals. The aim of this paper is to analyze the known frameworks and models used for measuring project success and present recommendations for developing conceptual framework that would allow for a systematic selection of key performance indicators (KPIs) to be used as a base for measuring project success. The paper gives an overview of the different characteristics and categories of the KPIs, the links between measurements and KPIs, KPI interdependence, and indicates the possibility of an integrated performance index adapted application. Key recommendations for the development of a conceptual framework for measurement and analysis of project success are to determine KPIs based on project life cycle phases and an analysis of project environment. This is especially important during the formulation of KPIs that will serve as a basis for project success measurement and evaluation in terms of contribution to an organization's strategic goals.

The Fourth Industrial Revolution (4IR) has changed the rules of competition, resulting in organisations needing new and improved business strategies. The execution of these strategies is critical to organisational success. One way of ensuring that employees execute strategies optimally is by developing key performance areas (KPAs) and key performance indicators (KPIs). This study focused on the IKM related departments or teams. Thus, the study aimed to determine KPAs and KPIs needed by IKM teams for success in the 4IR. To fulfil the aim of the study, the researchers took on a Delphi study where experts participated in two rounds of data collection. One was to identify the KPAs and KPIs necessary for IKM teams, and the second was to get the experts to share their thoughts on each other's views regarding KPAs and KPIs necessary for success in the 4IR. The experts identified 54 KPAs and 33 KPIs in total. Individual organisations should undertake further research to determine whether they help them achieve optimum success. Furthermore, there is a need to decide whether they need to update the existing KPAs and KPIs or not.

South Oman has several pre-Cambrian reservoirs that are highly pressured (400-1000 bar), deep (3-5 km) and critically sour (H2S up to 10%). The combined STOIIP of these reservoirs makes it one of the largest gas EOR projects in the world. The objective here is to highlight the key performance indicators and digitalization techniques used for continuous and effective well, reservoir and facility management (WRFM) and production optimization, while honoring the facility constraints and gas export requirements. Real time pressure data such as tubing head pressures, injection/production rates along with other data including maps, static pressures and production logs are used to define an appropriate set of performance metric at various levels, e.g. reservoir, sector or well. Digitalization of surveillance data helps in real time production optimization such as offtake management based on creaming curves according to gas sink availability and facility constraints. Key business performance indicators include gas utilization efficiency; MGI performance indicators include incremental oil, throughput, instantaneous and cumulative voidage replacement ratios, gas breakthrough level and time, ratio of reservoir pressure to the target minimum miscibility pressure; and facility constraints are optimized through gas balance, along with tracking field performance against the initial FDP forecasts. Real time performance data is tracked using a commercial Real-Time Data Analysis tool (RTDA) and Database Analytics Visualization Tool (DAVT), with surveillance indicators targeted at well, reservoir and facility level. The above-defined Key Performance Indicators (KPI) are tracked against predictions from the field development plan in web-based portal developed at PDO (Nibras). Digitalization has enabled quick and effective monitoring of these KPI, short-term optimization of injection distribution and offtake rates to maximize oil production and overall value within facilities constraints and varying export gas commitments based on South Oman Gas Line (SOGL) network optimization. Using dimensionless plots and a standardized set of parameters help in developing a common understanding and benchmarking the MGI reservoir response with analogs and amongst different reservoirs. This work presents a set of performance KPIs and short-term optimization methodology using digitalization and LEAN framework that are tracked in a web-based portal, RTDA and DAVT. It provides means to facilitate offtake decisions to meet variable export requirements while honoring facilities constraints, assess reservoir performance, providing valuable insights that helps in speedy reservoir management decisions. This process has been replicated across PDO for all related MGI projects and can benefit other development types, e.g. chemical/steam injection.

Objective: the scientific understanding of the individual key performance indicators function within the mechanism of stimulating the participants of project activities of executive authorities is supplemented with knowledge of the direction and impact of their actions.Methods: combination of logical and analytical deduction of theories and methodologies of stimulating the project activity participants under the stimulating influence of key performance indicators at executive authority bodies; identification of correlation dependence of the stimulated participants’ behaviour by the data of questionnaire survey of project activity experts. Results: on the basis of theoretical and methodological provisions and evidence of the stimulating effect of key performance indicators in the activity of project participants, it is proved that the effect has a complex mechanism inherent in project activities of executive authorities. It is determined that the key performance indicators serve as a means of identifying problem areas of the system of project participants’ motivation. The quantitative ratios are found of the stimulating influence of non-material and material individual key performance indicators on the project success, as well as the required working hours and the value-oriented importance of observing them. It is proposed to supplement the individual key performance indicators with an indicator that focuses the project activities towards the project success. The results show that unsystematic adoption of any key performance indicators as the main one leads to a significant deterioration of the stimulating impact of the remaining indicators on the project participants. It is revealed that the activities of the project participants are mostly (26,2 %) focused on the qualitative implementation of the project activities, and to the least degree (14,9 %) - on the observance of discipline. The most time-consuming activity (15,2 %) for the project participants is obtaining unique results. The quantitative rule is found that the maximization of the project complexity stimulation leads to the minimization of the incentives for the qualitative implementation of the project activities and the uniqueness of its results.Scientific novelty: for the first time it is determined that the key performance indicators in their economic form reflect three types of costs: conditionally constant and variable part of payment, as well as transaction costs for the purpose-orientation of the project participants.Practical significance: the main provisions and conclusions of the article can be used in research of the stimulating effect of key performance indicators on the activity of project participants and in the development of methods for building systems of key performance indicators to stimulate them in the executive authority bodies.

The driving strategy of train drivers has a large impact on the energy consumption. In recent studies the focus was on calculating the optimal eco-driving strategy, and measuring the exact amount of energy used during train runs. However, energy consumption is not the only key performance indicator that affects the operational performance of train or freight operating companies. In this study we define a set of key performance indicators, relevant to train operation, that are specific, measurable, assignable, realistic and time-related, and that are influenced by the driving strategy of the driver. These key performance indicators are safety, timeliness, energy consumption, workload of the driver, the environment, cost of maintenance and brand image. We chose four driving strategies that are most used in daily practice or most studied in the literature to assess these key performance indicators. Per key performance indicator we defined evaluation criteria to measure the impact of a driving strategy. We then defined key characteristics (e.g. track length, gradients), and conditions (e.g. speed restrictions, and load factor) based on which we defined test scenarios for three different train types. We then used the Radau Pseudospectral Method for solving the various optimal train control problems to compute the effect of the driving strategies on most of the key performance indicators. Our findings show amongst others, that a maximal coasting strategy causes the least environmental pollution, and in most scenarios its energy consumption coincided with the optimal energy-efficient train control strategy or it had an energy efficiency close to the optimal one. Furthermore, we found that on other key performance indicators there are differences between the driving strategies (e.g. in cost of maintenance), which should be considered when choosing a preferred driving strategy. Our results enable train and freight operating companies to make an informed decision when choosing a preferred driving strategy for their drivers, or when choosing a Driver Advisory System that supports this preferred driving strategy.

В данной статье проводится анализ существующих моделей оценки уровня успешности проектов информационного моделирования зданий и предлагается новый метод, основанный на применении технологии поддержки принятия решений. Предложенный метод оценки успеха проекта BIM разработан на основе того, что успех проекта нельзя оценить без предварительного определения его целей. Из чего выходит, что ключевые показатели эффективности могут варьироваться в зависимости от цели проекта. Данный метод состоит из шести этапов, которые состоят из определения целей BIM, выбора инструментария, использования ключевых показателей эффективности, деления проекта на универсальные блоки, создания и анализа хрономодели проекта, а также выбора форм сбора данных. Для определения подходящих ключевых показателей эффективности BIM учитывались собираемость, измеримость и сопоставимость возможных ключевых показателей эффективности BIM. This article analyzes existing models for assessing the level of success of building information modeling projects and proposes a new method based on the use of decision support technology. The proposed method for assessing the success of a BIM project is developed on the basis that the success of a project cannot be assessed without first defining its objectives. This means that key performance indicators may vary depending on the purpose of the project. This method consists of six stages, which consist of defining BIM goals, selecting tools, using key performance indicators, dividing the project into universal blocks, creating and analyzing a chronological model of the project, and selecting data collection forms. To identify suitable BIM KPIs, the collectability, measurability and comparability of possible BIM KPIs were considered.

Evaluating Success in PPP Road Projects in Europe: A Comparison of Performance Measurement Approaches

Mission engineering is a growing field with many practical opportunities and challenges. The goal of mission engineering is to increase system effectiveness, reduce life cycle costs, and aid in communicating system capabilities to key stakeholders. Optimizing system designs for their mission context is important to achieving these goals. However, system optimization is generally done using multiple key performance indicators (KPIs), which are not always directly representative of, nor easily translatable to, mission success. This paper introduces, motivates, and proposes a new approach for performing mission-level optimization (MLO), where the objective is to design systems that maximize the probability of mission success over the system life cycle. This builds on previous literature related to mission engineering, modeling, and analysis, as well as optimization under uncertainty. MLO problems are unique in their high levels of design, operational, and environmental uncertainty, as well as the single binary objective representing mission success or failure. By optimizing for mission success, designers can account for large numbers of KPIs and external factors when determining the best possible system design.

Understanding the relationship between safety culture and safety performance indicators in U.S. nuclear waste cleanup operations

The Faculty of Engineering, Udayana University is one of the faculties in Udayana University. The Faculty of Engineering has 5 departments that have a lot of interest. Currently, the Faculty of Engineering is preparing to support Udayana University in obtaining the Asean University Network - Quality Assurance (AUN-QA) certification which is targeted for a visitation in 2021. One of the supporters in obtaining this certification is that the Faculty of Engineering must have a performance measurement system. In this research using an integrated performance measurement system that designed through the Malcolm Baldrige Criteria For Performance Excellent (Education Criteria) approach which is integrated with several methods, namely IPMS in determining the Key Performance Indicator (KPI) which becomes a determining indicator of later performance. assisted by using the Analytical Hierarchy Process (AHP) method in giving the weight of each KPI. After the KPI has a weight, then a comprehensive scoring is carried out using the Objectives Matrix (OMAX) method so that an index number per period is generated which is the reference for the level of performance of the department, as well as a Traffic Light System (TLS) to find out which KPIs require improvement based on color. With the creation of an integrated performance measurement system, it is hoped that the Faculty of Engineering can make continuous improvements. The results showed that the Performance Indicator from the Faculty of Engineering in this period was 427.19 with 24 KPIs being measured. The Performance Indicator shows that the overall performance of the Faculty of Engineering is above average (300). Only 2 categories are in the red zone of 21%, namely Student Criteria (KPI 1 and KPI 4) and Management Criteria (KPI 18, KPI 19, and KPI 20). In the following year, the Faculty of Engineering must focus on the five KPIs so that later they can improve performance.