No description available.

OBJECTIVE: This study investigated how upper limb post-operative patients defined quality care. We specifically assessed the following three aims: (1) determining patient expectations following upper limb surgery, (2) identifying patient recognized barriers to receiving quality care, and (3) analyzing patient identified areas of improvement in patient education. METHOD: In total, 52 patients, aged 19 – 89 years (mean age: 48 years) who received upper limb surgery were surveyed with an open-ended questionnaire during their six to eight week post-operative visit at Stanford Medicine Outpatient Center in Redwood City or Stanford Orthopaedic Surgery Clinic in Los Gatos. Responses were electronically transcribed to REDcap, Research Electronic Data Capture System, for analysis of responses to demographic questions. Open-ended questions were evaluated by thematic analysis until data saturation was reached. RESULTS: Thematic analysis of open-ended responses revealed three main themes: (1) Pain, (2) Function; and (3) Patient Unpreparedness. Both pain and function involved pre- and post-operative factors. Of our three identified themes, elimination of pain and regaining function were the two main health-outcomes that upper limb patients identified as successful treatments of their condition. Patient unpreparedness was recognized as a main barrier in patients receiving quality care and an important area to improve patient education about their problem and treatment. CONCLUSION: By understanding the desired health outcomes and limitations in achieving those outcomes for post-operative upper limb patients, we can improve how medical care is practiced. Our results highlighted that both process and outcome domains of care are important elements in patients’ definition of quality care when seeking medical treatment for their upper limb problems. Specifically, patients identified that elimination of pain and regaining function were important health outcomes during their care. In order to achieve those desired health-outcomes, we recognized that improvements need to be made with regard to patient education about their health condition and treatment process, in order to foster better physician-patient communication. Overall, our findings support the need for continued focus on patient-centered care to ensure the delivery of quality healthcare to all patients.

acase@tulane.edu

According to the National Council of Teachers of Mathematics (NCTM) standard of communication, ??Instructional programs from pre-kindergarten through grade 12 should enable all students to...communicate their mathematical thinking coherently and clearly to peers, teachers, and others?? and students need to learn ??what is acceptable as evidence in mathematics?? (NCTM, 2000, p. 60). But do teachers have a clear understanding of what is acceptable or do they believe that the only acceptable explanations are the ones that they themselves gave to the students? Can teachers accept alternative forms of explanation and methods of solution as mathematically accurate or do they want students to simply restate the teachers?? understandings of mathematics and the problem? The focus of this dissertation is the authoritative discourse practices of classroom teachers as they relate to individual students and large and small groups of students. In this case study, I examine the interactions in one eighth-grade mathematics classroom and the possible sharing of mathematical authority and development of mathematical agency that take place via the teacher??s uses of authoritative discourse. A guiding objective of this research was to examine the ways a teacher??s discursive practices were aligned with her pedagogical intentions. The teacher for this study was an experienced eighth-grade mathematics teacher at a rural Central Texas middle school. The teacher was a participant in the Middle School Mathematics Project at Texas A&M University. Results of an analysis of the discourse of six selected classes were combined with interview and observation data and curriculum materials to inform the research questions. I found that through the teacher??s regular use of authoritative discursive devices, mathematical authority was infrequently shared. Also the teacher??s uses of authoritative discourse helped create an environment where mathematical agency was not encouraged or supported. The teacher??s use of various discursive devices helped establish and maintain a hierarchy of mathematical authority with students at the lowest level reliant on others for various mathematical decisions.

Business Intelligence (BI) enables organizations to collect and analyze internal and external business data to generate knowledge and business value, and provide decision support at the strategic, tactical, and operational levels. The consolidation of data coming from many sources as a result of managerial and operational business processes, usually referred to as Extract-Transform-Load (ETL) is itself a statically defined process and knowledge workers have little to no control over the characteristics of the presentable data to which they have access. There are two main reasons that dictate the reassessment of this stiff approach in context of modern business environments. The first reason is that the service-oriented nature of today’s business combined with the increasing volume of available data make it impossible for an organization to proactively design efficient data management processes. The second reason is that enterprises can benefit significantly from analyzing the behavior of their business processes fostering their optimization. Hence, we took a first step towards quality-aware ETL process design automation by defining through a systematic literature review a set of ETL process quality characteristics and the relationships between them, as well as by providing quantitative measures for each characteristic. Subsequently, we produced a model that represents ETL process quality characteristics and the dependencies among them and we showcased through the application of a Goal Model with quantitative components (i.e., indicators) how our model can provide the basis for subsequent analysis to reason and make informed ETL design decisions. In addition, we introduced our holistic view for a quality-aware design of ETL processes by presenting a framework for user-centered declarative ETL. This included the definition of an architecture and methodology for the rapid, incremental, qualitative improvement of ETL process models, promoting automation and reducing complexity, as well as a clear separation of business users and IT roles where each user is presented with appropriate views and assigned with fitting tasks. In this direction, we built a tool —POIESIS— which facilitates incremental, quantitative improvement of ETL process models with users being the key participants through well-defined collaborative interfaces. When it comes to evaluating different quality characteristics of the ETL process design, we proposed an automated data generation framework for evaluating ETL processes (i.e., Bijoux). To this end, we classified the operations based on the part of input data they access for processing, which facilitated Bijoux during data generation processes both for identifying the constraints that specific operation semantics imply over input data, as well as for deciding at which level the data should be generated (e.g., single field, single tuple, complete dataset). Bijoux offers data generation capabilities in a modular and configurable manner, which can be used to evaluate the quality of different parts of an ETL process. Moreover, we introduced a methodology that can apply to concrete contexts, building a repository of patterns and rules. This generated knowledge base can be used during the design and maintenance phases of ETL processes, automatically exposing understandable conceptual representations of the processes and providing useful insight for design decisions. Collectively, these contributions have raised the level of abstraction of ETL process components, revealing their quality characteristics in a granular level and allowing for evaluation and automated (re-)design, taking under consideration business users’ quality goals.

Business Intelligence (BI) enables organizations to collect and analyze internal and external business data to generate knowledge and business value, and provide decision support at the strategic, tactical, and operational levels. The consolidation of data coming from many sources as a result of managerial and operational business processes, usually referred to as Extract-Transform-Load (ETL) is itself a statically defined process and knowledge workers have little to no control over the characteristics of the presentable data to which they have access. There are two main reasons that dictate the reassessment of this stiff approach in context of modern business environments. The first reason is that the service-oriented nature of today’s business combined with the increasing volume of available data make it impossible for an organization to proactively design efficient data management processes. The second reason is that enterprises can benefit significantly from analyzing the behavior of their business processes fostering their optimization. Hence, we took a first step towards quality-aware ETL process design automation by defining through a systematic literature review a set of ETL process quality characteristics and the relationships between them, as well as by providing quantitative measures for each characteristic. Subsequently, we produced a model that represents ETL process quality characteristics and the dependencies among them and we showcased through the application of a Goal Model with quantitative components (i.e., indicators) how our model can provide the basis for subsequent analysis to reason and make informed ETL design decisions. In addition, we introduced our holistic view for a quality-aware design of ETL processes by presenting a framework for user-centered declarative ETL. This included the definition of an architecture and methodology for the rapid, incremental, qualitative improvement of ETL process models, promoting automation and reducing complexity, as well as a clear separation of business users and IT roles where each user is presented with appropriate views and assigned with fitting tasks. In this direction, we built a tool —POIESIS— which facilitates incremental, quantitative improvement of ETL process models with users being the key participants through well-defined collaborative interfaces. When it comes to evaluating different quality characteristics of the ETL process design, we proposed an automated data generation framework for evaluating ETL processes (i.e., Bijoux). To this end, we classified the operations based on the part of input data they access for processing, which facilitated Bijoux during data generation processes both for identifying the constraints that specific operation semantics imply over input data, as well as for deciding at which level the data should be generated (e.g., single field, single tuple, complete dataset). Bijoux offers data generation capabilities in a modular and configurable manner, which can be used to evaluate the quality of different parts of an ETL process. Moreover, we introduced a methodology that can apply to concrete contexts, building a repository of patterns and rules. This generated knowledge base can be used during the design and maintenance phases of ETL processes, automatically exposing understandable conceptual representations of the processes and providing useful insight for design decisions. Collectively, these contributions have raised the level of abstraction of ETL process components, revealing their quality characteristics in a granular level and allowing for evaluation and automated (re-)design, taking under consideration business users’ quality goals.

No description available.

Define the role/function of an interprofessional team in the management of complex outpatients. Identify the types of patients that would benefit most from a team-based approach. Implement elements of our team-based patient care model into individual practices.

ETL processes play an increasingly important role for the support of modern business operations. These business processes are centred around artifacts with high variability and diverse lifecycles, which correspond to key business entities. The apparent complexity of these activities has been examined through the prism of Business Process Management, mainly focusing on functional requirements and performance optimization. However, the quality dimension has not yet been thoroughly investigated and there is a need for a more human-centric approach to bring them closer to business-users requirements. In this paper we take a first step towards this direction by defining a sound model for ETL process quality characteristics and quantitative measures for each characteristic, based on existing literature. Our model shows dependencies among quality characteristics and can provide the basis for subsequent analysis using Goal Modeling techniques.

No description available.