Enhancing Well Delivery Performance Through Discipline Integration

Background: Regional variation in the utilization of health services is a well-documented phenomenon in health care with numerous studies reporting substantial and unexplained variations in coronary revascularization. In the Canadian province of British Columbia (BC), five cardiac centers provide coronary revascularization services. In 2011 Cardiac Services BC (CSBC) undertook a study that identified substantial regional variation in coronary revascularization that could not be explained by patient characteristics or risk factors. Following this initial project, CSBC launched an initiative to help better understand the regional variations and possibly devise and implement strategies to reduce them. Methods: Using Lean methodology, we are mapping the key processes of care for ACS patients across BC (initially excluding emergent STEMI and cardiogenic shock) at each cardiac centre. The ACS patient journey will be mapped from admission to discharge through several key decision points that determine whether they will continue through to diagnostic catheterization and revascularization or to be medically managed alone. The key decision points are: 1. Decision to refer to diagnostic catheterization and subsequent transfer if necessary. 2. Decision to continue to a revascularization procedure (PCI or CABG) after diagnostic catheterization. The map will summarized these key decision points using multiple sources of data: 1. Flow and patient volumes into and out of each of these decision 2. Times between decision points and key care processes 3. Clinical influencers (ex: standard orders, best practice, established patterns of referral, and consultations) and non-clinical influencers (ex: resource capacity, transportation) that are considered at each decision point (process mapping and interview data). Discussion: BC is attempting to reduce unexplained variation in coronary revascularization using the Lean methodology to take a systematic approach to the analysis of the process of ACS care across the province. Involving physicians and point of care staff in the detailed mapping process has proven to be a significant step in engaging key stakeholders in the project by allowing input into the process of describing the factors affecting variation of practice at each site. The next step is to convene provincially to determine where to improve standardized practice in order to improve patient outcomes at key points along the value stream.

The primary output of a decision making process is a decision and a key outcome measure is therefore decision quality. However, being a formative construct, 'decision quality' is both preference- and context-sensitive and legitimate alternative measures accordingly exist. A decision maker wishing to measure decision quality in the evaluation of a decision or decision making process needs to be aware of the attributes of the measures on offer. This paper establishes some of the key conceptual differences by examining two measures: Decision Quality Instruments and MyDecisionQuality. Four of their main conceptual differences relate to: the timing of the measurement (at the point of decision or at follow-up when the 'downstream' outcome is known); (whether or not an objective assessment of the information state of the individual is included (as opposed to self-reported state); whether the instrument itself is preference-sensitive; and whether the measure is to be used in the context of individualised clinical practice at the point of care or only in research to produce group level feedback. Establishing agreed measures of decision quality is necessary and useful, so long as it is accepted that it is a preference- and context-sensitive construct, in the way that is widely acknowledged in relation to, for example, Health-Related Quality of Life, with its many measures.

Decision-making in operative vaginal delivery: when to intervene, where to deliver and which instrument to use? Qualitative analysis of expert clinical practice

Rationale and aims: Contextual factors are increasingly recognized as having a significant influence on clinical-decision-making. Contextual influences however, are considered ‘less scientific’ or ‘non-clinical’ in the eyes of practicing clinicians, making it a sensitive issue for discussion. Therefore, exploring these contextual influences can be challenging. Methods which can circumvent this challenge are required to evaluate clinical decision making at natural settings. This paper reports on the development of an innovative research method to address this challenge of exploring contextual influences and similar sensitive and complex clinical practice issues. Method: The researchers conducted a field research to test an interview based method which was termed as ‘Clinician Recalled Vignette (CRV) Method’. Based on reflections on the field research experience this preliminary method was refined to develop an innovative method which is potentially capable of eliciting sensitive and complex clinical practice issues. Results: Reflections on field test data provided preliminary evidence on the usefulness of the CRV method and limitations. The method that was refined, in response to limitations, focused on key decision points relevant to the clinical vignettes recalled by clinicians, and included a mechanism to identify how contextual factors influence these key decision points. This innovative method was termed ‘Vignette-based Decision Point Analysis’. Conclusions: The innovative method discussed in this paper will assist other researchers in conceptualising and conducting research projects to explore sensitive and complex clinical practice issues in natural settings.

PurposeDefective stakeholder management has frequently resulted in conflicts and partial failures. Integrated project delivery (IPD) and team integration provides opportunities for organizations to achieve more than they could on their own. The purpose of this study is to analyze the level and challenges of team integration. In addition, study tries to recognize the cornerstones for creating integrated teams in construction projects.Design/methodology/approachThis paper discusses the characteristics and level of team integration in a construction project, but the main purpose is to derive the cornerstones for creating integrated teams. Results are derived from the analysis of current literature and an empirical case study.FindingsThis paper describes the 12 characteristics of an integrated project team. In addition, the cornerstones for creating integrated teams were recognized as the early involvement and assessment of stakeholders, continuous communication and interaction, cultural change, and making the IPD process well known.Practical implicationsThe construction industry is aware of the need to improve control over its delivery processes. In addition, the customers are aware of waste and have started to demand more value. Because IPD and team integration supports the controlling over delivery processes and enables the more efficient value creation, these are extensive issues in developing construction industry.Originality/valueTeam integration is an important part of value creation. Limited research attention has been directed at what the level of integration is compared with the characteristics of integration. This paper also advances team integration research by identifying the cornerstones for integration.

Data analyses are based on a series of including data filtering, feature operationalization and selection, model specification, and parametric assumptions. Analysis research has shown that a lack of exploration of these decisions can lead to non-robust conclusions based on highly sensitive decision points. Importantly, even if myopic analyses are technically correct, analysts' focus on one set of decision points precludes them from exploring alternate formulations that may produce very different results. Prior work has also shown that analysts' exploration is often limited based on their training, domain, and personal experience. However, supporting analysts in exploring alternative approaches is challenging and typically requires expert feedback that is costly and hard to scale. Here, we formulate the tasks of identifying decision points and suggesting alternative analysis approaches as a classification task and a sequence-to-sequence prediction task, respectively. We leverage public collective data analysis knowledge in the form of code submissions to the popular data science platform Kaggle to build the first predictive model which supports Multiverse Analysis. Specifically, we mine this code repository for 70k small differences between 40k submissions, and demonstrate that these differences often highlight key decision points and alternative approaches in their respective analyses.We leverage information on relationships within libraries through neural graph representation learning in a multitask learning framework. We demonstrate that our model, MULTIVERSE, is able to correctly predict decision points with up to 0.81 ROC AUC, and alternative code snippets with up to 50.3% GLEU, and that it performs favorably compared to a suite of baselines and ablations. We show that when our model has perfect information about the location of decision points, say provided by the analyst, its performance increases significantly from 50.3% to 73.4% GLEU. Finally, we show through a human evaluation that real data analysts find alternatives provided by MULTIVERSE to be more reasonable, acceptable, and syntactically correct than alternatives from comparable baselines, including other transformer-based seq2seq models.

Military Operations Research studies often involve the analysis of structured descriptions of plausible contingencies called ‘scenarios’. While scenarios attempt to provide a sufficient account of an unfolding contingency they do not typically include details of specific types of missions undertaken at the operational level or even the broad roles of the military forces undertaking those missions. Some means of linking key events, decision points and military activities in the chosen scenario to the roles and missions undertaken by a military force was thus sought for recent studies in joint operations. This article discusses a Mission-to-Scenario methodology developed, which provides a repeatable framework to structure the analysis of related problems. Application of the Mission-to-Scenario methodology for military macro-system analysis may then be used to explore the efficacy of military capabilities, operational effectiveness of specific platforms and the impact of proposed insertion of new technologies or organisational changes.

BackgroundStudies show that system inefficiency and processes that take away from the joy of medicine contribute to burnout. Using the Hawaii Pacific Health model, a program was established to allow...

The project development process is a critical component of highway projects. Decisions made during this phase have a significant impact on the final project outcomes. This paper describes a research project that studied this process and subsequently developed a method to help the highway project team improve the project development process. This method does so by proactively identifying risk sources based on the analysis of the project scope. This method uses a comprehensive list of scope elements with descriptions and a mechanism to evaluate quantitatively the scope elements' level of definition. Assessing the level of definition of each scope element and of the project as a whole allows the project team to determine the potential level of risk to which the project is exposed. The project team can then develop risk mitigation plans to respond to the potential high risk elements. The proposed method was tested on real completed and ongoing projects undertaken by experienced professionals. The method was well received by the subject matter experts, and a number of benefits were observed, including the use as an integrated checklist, a mechanism for monitoring the project development progress, as well as a means for improving communication and promoting alignment within the project team.

OBJECTIVE To describe strengths and weaknesses of peer reviews of manuscripts received in Gaceta Sanitaria in order to guide reviewers selection, to improve quality of peer reviews and to establish an internal system to be incorporated to the editorial process of handling manuscripts. METHODS 100 peer reviews of 55 manuscripts received during 2000 and 2001 were included. A questionnaire containing closed questions assessing specific and general components of reviews' quality was applied (answers Yes/No or on a 5-points scale). Descriptive and correlation analyses were performed for the different items in the questionnaire. An Index of Quality was obtained by adding the ratings on the items in the questionnaire measuring specific quality components. RESULTS Peer reviews were rated high regarding completeness of the forms for reviewers (84%), constructiveness of the comments (reviews over 3: 63%), identification of the strengths and weaknesses of the method (reviews over 3: 59%) and substantiation of the reviewer comments (reviews over 3: 58%). Assessment of the manuscript's relevance (reviews over 3: 40%) or originality (reviews over 3: 35%) were less frequent. CONCLUSIONS Quality of peer reviews in Gaceta Sanitaria is good. Some weaknesses in the reviews have been pointed out. It is possible to establish a systematic process for assessing peer reviewers using simple indicators such as general utility of the review for the editorial decision and general quality of the review.

The demanding of assessment in learning process was impact by policy changes. Nowadays, assessment is not only emphasizing knowledge, but also skills and attitudes. However, in reality there are many obstacles in measuring them. This paper aimed to describe how to develop integrated assessment instrument and to verify instruments’ validity such as content validity and construct validity. This instrument development used test development model by McIntire. Development process data was acquired based on development test step. Initial product was observed by three peer reviewer and six expert judgments (two subject matter experts, two evaluation experts and two chemistry teachers) to acquire content validity. This research involved 376 first grade students of two Senior High Schools in Bantul Regency to acquire construct validity. Content validity was analyzed used Aiken’s formula. The verifying of construct validity was analyzed by exploratory factor analysis using SPSS ver 16.0. The result show that all constructs in integrated assessment instrument are asserted valid according to content validity and construct validity. Therefore, the integrated assessment instrument is suitable for measuring critical thinking abilities and science process skills of senior high school students on electrolyte solution matter.

The rapid development of science and technology has been accompanied by an exponential growth in peer-reviewed scientific publications. At the same time, the review of each paper is a laborious process that must be carried out by subject matter experts. Thus, providing high-quality reviews of this growing number of papers is a significant challenge. In this work, we ask the question “can we automate scientific reviewing? ”, discussing the possibility of using natural language processing (NLP) models to generate peer reviews for scientific papers. Because it is non-trivial to define what a “good” review is in the first place, we first discuss possible evaluation metrics that could be used to judge success in this task. We then focus on the machine learning domain and collect a dataset of papers in the domain, annotate them with different aspects of content covered in each review, and train targeted summarization models that take in papers as input and generate reviews as output. Comprehensive experimental results on the test set show that while system-generated reviews are comprehensive, touching upon more aspects of the paper than human-written reviews, the generated texts are less constructive and less factual than human-written reviews for all aspects except the explanation of the core ideas of the papers, which are largely factually correct. Given these results, we pose eight challenges in the pursuit of a good review generation system together with potential solutions, which, hopefully, will inspire more future research in this direction. We make relevant resource publicly available for use by future research: https://github. com/neulab/ReviewAdvisor. In addition, while our conclusion is that the technology is not yet ready for use in high-stakes review settings we provide a system demo, ReviewAdvisor (http://review.nlpedia.ai/), showing the current capabilities and failings of state-of-the-art NLP models at this task (see demo screenshot in A.2). A review of this paper written by the system proposed in this paper can be found in A.1.

Prioritizing Reviewer Training.

This study aims to investigate: (1) the feasibility of computer-assisted learning media based problem based learning (PBL) on Environmental Pollution materials for high school students of class X, and (2) the effectiveness of instructional media for improving of critical thinking skill (CTS) learners class X SMA Negeri 5 Magelang. This research was adapted from the ADDIE model of development that includes analyze, design, develop, implement, and evaluate. Products validated by subject matter experts, media experts, educators of Biology, and peer reviewer. Subject of this study is tenth grade students of SMA Negeri 5 Magelang. Collecting data was using questionnaires, observation sheets, and test critical thinking skills. The media according to the validator and the students is classified to the category of good. Instructional media was improved to learners' critical thinking skills effectively, which demonstrated by the significant value of 0:00. This results showed that media computer-assisted learning based PBL is effective for improving of the critical thinking skills of learners.

Astronaut behavioral and mental health are key factors for space mission success. NASA’s Cognition test battery is often preceded by a brief 18-item Alertness and Mood Survey (AMS) adding subjective assessments to Cognition’s 10 objective neuropsychological tests. Therefore, the main objective of this study was to generate a single AMS summary score for short (<6 months) and long (>6 months) space missions based on the relevance of individual items. With the paired comparison (PC) method, 19 subject matter experts (SMEs) were asked to rate the relevance of 14 AMS items for astronaut behavioral health. Boredom (22.1% of comparisons), monotony (23.1%), and sleepiness (35.6%) were considered the least relevant, and health (74.3%), depression (76.5%), and crew conflicts (77.9%) were considered the most relevant by SMEs. Six of the fourteen items differed statistically significantly between PCs for short- and long-duration missions: sleepiness, tiredness, energy level, and mental status were considered more relevant for short-duration missions, while monotony and loneliness were considered more relevant for long-duration missions (all adjusted p < 0.05). We also demonstrated systematic changes in AMS summary scores during a 60-day 6° head-down tilt bed rest (HDBR) study, with increased alertness and mood disturbance during and after the HDBR period relative to pre-HDBR levels. This analysis identified the AMS domains considered most relevant for space mission success by SMEs, and highlighted differences between long- and short-duration missions. The resulting AMS summary scores were based on item relevance and will be useful for monitoring astronaut behavioral health on short- and long-duration space missions.