Improve Practice Performance Research Articles

Performance analysis of a modified solar assisted ejection-compression heat pump cycle for drying application

In this paper, a modified solar assisted ejection-compression heat pump cycle (SEHPC) is proposed for drying application. Based on the basic ejection-compression heat pump cycle (BEHPC), an auxiliary flash tank and an internal heat exchanger are introduced to improve its heating performances. The introduction of flash tank can improve the heat absorption in evaporator and increase the volumetric heating capacity in condenser, which eventually reduce the throttling losses and enhance the performance of the SEHPC. The performances of the modified cycle with refrigerant R1234yf are analyzed and compared to those of basic cycle by developing the thermodynamic models based on the energy, exergy and economic analysis. Moreover, the main parameters, including evaporation temperature, condensation temperature, generation temperature, ejector back pressure, and the solar radiation intensity, are selected as variables for research. The theoretical results indicate that compared to BEHPC, the mechanical coefficient of heating performance COPw, the thermal coefficient of heating performance COPt, the volumetric heating capacity qhv and the exergy efficiency ηex of SEHPC are increased by 5.2%, 8.4%, 17.1%, and 8.0%, respectively, under a specified working condition. Furthermore, the SEHPC outperforms BEHPC under all given working conditions, especially at high condensation temperature and high generation temperature. The economic analysis results show that the cost per unit of exergy production by SEHPC is 6% lower than that of BEHPC. Additionally, the maximum exergy destruction occurred in the solar collector, which means great optimization potential in solar collector. This study demonstrates that SEHPC has practical performance improvement potential for heat pump drying application.

74 Development and content validation of a tool to assess quality of primary care practice

OBJECTIVES/GOALS: Primary care practices struggle to identify which combination of care structures and processes need to be implemented to improve practice performance and subsequently, patient outcomes. The goal of this study is to develop and validate a tool to assess care structures and processes that are associated with better quality and patient outcomes. METHODS/STUDY POPULATION: Data from a scoping review, Delphi study, and qualitative interviews with high-performing primary care practices contributed to the development and content validation of the Tool for Advancing Practice Performance (TAPP). From these sources we identified 314 items representing care structures (e.g., care team makeup, use of electronic health records) and processes (e.g., care coordination, panel management). We developed criteria for deleting and rescuing items and received input from our expert panel to refine the pool of items. We eliminated items that were redundant and lacked clarity/specificity. The tool was further modified based on feedback from cognitive interviewing and pilot testing with practice managers, quality improvement leaders, and physicians from primary care practices. RESULTS/ANTICIPATED RESULTS: The pool of 314 items was winnowed to 188 after applying criteria for deleting and rescuing items. During the expert review, 70 items were eliminated and 8 new items were added, resulting in a working tool of 126 items. We conducted eight cognitive interviews with the 126-item tool and received feedback on the content, item structure, and language, which led to the elimination of 13 items that were poorly or incorrectly understood by respondents. We also modified the language of 23 items for clarity. After cognitive interviewing, the resulting tool comprised 113 items. Fifteen practices piloted the tool and no additional items were eliminated. We modified the instructions for completing the tool and resolved technical issues related to online administration. DISCUSSION/SIGNIFICANCE: TAPP is a novel tool for assessing care structures and processes that are associated with better quality and patient outcomes in primary care settings. The tool can be used by researchers and primary care clinicians to identify areas for improvement in practice performance and patient outcomes related to chronic disease prevention and management.

Understanding online ratings of joint arthroplasty surgeons: A national cross-sectional analysis

BackgroundPatient reviews provide an important referral source for physicians and an opportunity to improve practice performance. This study's objective was to characterize the online reviews of hip and knee arthroplasty surgeons published by three of the industry's leading platforms. MethodsA random sample of 1000 hip and knee arthroplasty surgeons across all 50 US states (10 hip and 10 knee surgeons per state) was generated using Google Search. A total of 7842 online reviews posted for those surgeons on Healthgrades, Vitals, and Google were analyzed. A range of surgeons, affiliated hospitals, and reviewer attributes was compared to identify significant predictors of patient satisfaction. ResultsThe study cohort had 98.1% male surgeons with a mean age of 53.55 ± 8.94 years and mean experience of 26.43 ± 9.21 years. Younger age (p < 0.001), shorter years of experience (p < 0.001), and arthroplasty fellowship training (p < 0.001) were associated with more positive ratings. Reviewer anonymity, observed in 30.93% of all reviews, tended to correlate with more negative ratings (p < 0.001). Overall, 86.93% of patient remarks were positive, and only 74.81% of remarks centered on physician attributes. The five leading components of patient satisfaction were perceptions of physician competence (34.81%, p < 0.001), bedside manner (23.83%, p = 0.002), and communication (16.17%, p = 0.94); interactions with physician extenders (14.75%, p < 0.001); and wait time (2.73%, p < 0.001). ConclusionWhile most ratings of hip and knee arthroplasty surgeons were positive, more than a quarter of reviews were either not directly related to the individual surgeons or were submitted anonymously. Caution is advised regarding overreliance on patient experience surveys as predictors of physician performance.

Dancing on the inside: A qualitative study on online dance learning with teacher-AI cooperation.

Recent technologies have extended opportunities for online dance learning by overcoming the limitations of space and time. However, dance teachers report that student-teacher interaction is more likely to be challenging in a distant and asynchronous learning environment than in a conventional dance class, such as a dance studio. To address this issue, we introduce DancingInside, an online dance learning system that encourages a beginner to learn dance by providing timely and sufficient feedback based on Teacher-AI cooperation. The proposed system incorporates an AI-based tutor agent(AI tutor, in short) that uses a 2D pose estimation approach to quantitatively estimate the similarity between a learner's and teacher's performance. We conducted a two-week user study with 11 students and 4 teachers. Our qualitative study results highlight that the AI tutor in DancingInside could support the reflection on a learner's practice and helpthe performance improvement withmultimodal feedback resources. The interview results also revealthat the human teacher's role isessential in complementing the AI feedback. We discuss our design and suggest potential implications for future AI-supported cooperative dance learning systems.

Using the Medical Audit to Improve Practice Performance.

Feedback to physicians on their clinical performance is critical to continuous learning and maintenance of skills as well as maintaining patient safety. However, it is fraught with challenges around both implementation and acceptance. Additionally, rewarding of performance improvement is not often done, putting into question the efficacy of the process. Physician audit and feedback have been studied extensively and shown to be beneficial in many fields of medicine. Documenting physician performance and sharing individual and group data have been positively linked to changing physician behavior, ultimately leading to improved patient outcomes. Although casual review of one's own performance is often the easiest approach, it is frequently over- or underestimated by self-evaluation. Objective measures are therefore important to provide concrete data on which physicians can act. A fundamental question remains in mammography: Is reporting the information to the physician and accreditation bodies enough, or should there be consequences for the radiologist and/or facility if there is outlier behavior?

Editors’ Note and Prologue

Editors’ Note and Prologue

Implementing and Evaluating the Practice Environment Model Using Action Research

The psychological factors that influence performance in the practice environment, where competitive athletes engage in deliberate practice, have recently been given specific research attention. The current study employed an action research approach to implement the practice environment model as an education strategy to increase the practice performance of players in a U.K. basketball academy team over a 20-week period. The aim of the study was to evaluate the effect of the education strategy on practice performance. The team competed nationally and consisted of the head coach, the assistant coach, and 18 male players aged 16–19 years. Data were collected through focus groups, joint semistructured interviews, field observations, and a practice environment model web-based questionnaire. Qualitative data were analysed using thematic narrative analysis and the Friedman test analysed quantitative data. Quantitative results suggested that the education strategy decreased perceptions of stress and increased effort, preparation activities, and teammate support. Qualitative results provided an in-depth narrative of the environmental changes undertaken to improve practice performance. Discussion focuses on the key strategies of effort and control, performance expectations, team drive, positive communication, and preparation. This study is the first to apply the practice environment model to a real-world sporting domain.

An Ultra-Fast and Parallelizable Algorithm for Finding k-Mismatch Shortest Unique Substrings.

This paper revisits the k-mismatch shortest unique substring finding problem and demonstrates that a technique recently presented in the context of solving the k-mismatch average common substring problem can be adapted and combined with parts of the existing solution, resulting in a new algorithm which has expected time complexity of O(n logk n), while maintaining a practical space complexity at O(kn), where n is the string length. When , which is the hard case, our new proposal significantly improves the any-case O(n2) time complexity of the prior best method for k-mismatch shortest unique substring finding. Experimental study shows that our new algorithm is practical to implement and demonstrates significant improvements in processing time compared to the prior best solution's implementation when k is small relative to n. For example, our method processes a 200 KB sample DNA sequence with k=1 in just 0.18 seconds compared to 174.37 seconds with the prior best solution. Further, it is observed that significant portions of the adapted technique can be executed in parallel, using two different simple concurrency models, resulting in further significant practical performance improvement. As an example, when using 8 cores, the parallel implementations both achieved processing times that are less than 1/4 of the serial implementation's time cost, when processing a 10 MB sample DNA sequence with k=2. In an age where instances with thousands of gigabytes of RAM are readily available for use through Cloud infrastructure providers, it is likely that the trade-off of additional memory usage for significantly improved processing times will be desirable and needed by many users. For example, the best prior solution may spend years to finish a DNA sample of 200MB for any , while this new proposal, using 24 cores, can finish processing a sample of this size with k=1 in 206.376 seconds with a peak memory usage of 46 GB, which is both easily available and affordable on Cloud. It is expected that this new efficient and practical algorithm for k-mismatch shortest unique substring finding will prove useful to those using the measure on long sequences in fields such as computational biology. We also give a theoretical bound that the k-mismatch shortest unique substring finding problem can be solved using O(n logk n) time and O(n) space, asymptotically much better than the one we implemented, serving as a new discovery of interest.

Non-linear association of efficiency of practice of adult elite athletes with their youth multi-sport practice

ABSTRACT We explored associations of elite athletes’ multi-year efficiency of practice and improvement of performance with their current and earlier participation patterns. Participants were 80 adult German track-and-field national-squad athletes. Performance improvement was measured as development of athletes’ highest track-and-field championship level and placing from 19 to 25 years (t 1-t 2). Practice efficiency was defined as performance improvement per amount of coach-led athletics practice from t 1 to t 2. Participation variables included amounts of coach-led practice and peer-led play in athletics and other sports through t 1 and t 1-t 2. Analyses involved an advanced machine learning procedure, XGBoost, allowing non-linear, multivariate exploration. We computed two models, one for performance improvement (“good” discriminative performance, AUC = 0.82) and one for practice efficiency (“fair”, AUC = 0.73). Four central findings emerged: 1. Childhood/adolescent coach-led multi-sport practice was a critical discriminator of adult practice efficiency and performance improvement. 2. Associations were non-linear, displaying a saturation pattern. 3. The likelihood of achieving high adult practice efficiency was greatest when combining ~1,000–2,500 track-and-field practice hours until t 1 with ~1,250 other-sports practice hours until t 1. 4. Peer-led engagement in any sport had negligible effects. Childhood/adolescent multi-sport coach-led practice apparently facilitated long-term sustainability of athletes’ development of adult practice efficiency and performance improvement in athletics.

Efficiency Optimization Strategy for Switched Reluctance Generator System With Position Sensorless Control

A novel efficiency optimization strategy combined with a position estimation method is proposed for switched reluctance generators (SRGs) in this article. This practical performance improvement strategy can expand the application of SRGs small-scale wind energy generation system, which is a good solution for mitigating the fossil energy crisis. First, the position estimation method based on current injection of the idle phase is presented. The angle error caused by sampling in this method aggravates with speed. Accordingly, an error compensation strategy in the linear range of inductance is suggested. Second, a method for improving the efficiency of SRG system current is proposed. It determines the range of turn- off angle with the minimum root-mean-square value of phase current, and further obtains the optimal turn- on angle by the fitting expression to improve the efficiency. This efficiency optimization strategy combined with the new position estimation method can greatly enhance the efficiency and reliability of SRG system and eliminate the position sensor. There are many simulation and experiment results that validate the effectiveness of the proposed schemes.

The Complete Performance Map of Gas Wave Ejector and Analysis on the Variation Laws and Limitation of Performance

Abstract The gas wave ejector (GWE) is an efficient gas wave equipment using pressure waves to realize energy exchange. In this paper, a theoretical analysis of the limitation of application range and the factors affecting the performance of GWE was carried out by numerical simulation. And a complete experimental system including an adjustable GWE was employed to obtain the specific performance values in various working conditions. Such theoretical analysis showed that the device became inapplicable with a relatively high driving pressure ratio, resulting from the generation of supersonic flow at the outlet end of the passages. A relatively high supercharging ratio also limited the equipment application because of the weakening of the reflected expansion waves and the enhancement of the reversed compression wave. Furthermore, the mixing, vortex, viscosity, and other flow losses could also affect the equipment performance. Then, a complete performance map indicating the specific performance values in the application range was obtained by plenty of experiments. The performance map proved that GWE had excellent efficiency and broad applicability especially as the driving pressure ratio was lower than 2.6. The results are significant for practical application and performance improvement of GWE.

Aggregating Claims Data Across Payers: Approaches, Challenges, and Lessons Learned From the Comprehensive Primary Care Initiative.

The Comprehensive Primary Care (CPC) initiative fueled the emergence of new organizational alliances and financial commitments among payers and primary care practices to use data for performance improvement. In most regions of the country, practices received separate confidential feedback reports of claims-based measures from multiple payers, which varied in content and provided an incomplete picture of a practice's patient panel. Over CPC's last few years, participating payers in several regions resisted the tendency to guard data as a proprietary asset, instead working collaboratively to produce aggregated performance feedback for practices. Aggregating claims data across payers is a potential game changer in improving practice performance because doing so potentially makes the data more accessible, comprehensive, and useful. Understanding lessons learned and key challenges can help other initiatives that are aggregating claims or clinical data across payers for primary care practices or other types of providers.

Gradual efficiency improvement through a sequence of targets

The goal in efficiency analysis is not only to evaluate a decision-making unit (DMU) performance, but also to find an efficient target which provides information on inputs reduction and outputs increment values that are necessary to remove inefficiencies for each inefficient DMU. In data envelopment analysis (DEA), the target unit is located on the efficient frontier and possibly far from the unit under assessment. Therefore, in practice performance improvement seems to be disappointing or even impossible to achieve in only one step for some inefficient DMUs. In this regard, finding intermediate targets is of great importance in benchmarking literature. In this article, we find a sequence of targets instead of a single target for each inefficient unit. In our method, the intermediate target at each step has three properties: (I) the intermediate targets and the unit under evaluation are all similar in size; (II) efficiency scores are ascending through the sequence of targets; (III) the target unit at each step is close to the special part of the efficient frontier as much as possible. These properties lead to finding a target that is more achievable in real applications.

Quarter-Car Experimental Study for Series Active Variable Geometry Suspension

In this paper, the recently introduced series active variable geometry suspension (SAVGS) for road vehicles is experimentally studied. A realistic quarter-car test rig equipped with double-wishbone suspension is designed and built to mimic an actual grand tourer real axle, with a single-link variant of the SAVGS and a road excitation mechanism implemented. A linear equivalent modeling method is adopted to synthesize an H-infinity control scheme for the SAVGS, with the geometric nonlinearity compensated. Simulations with a theoretical nonlinear quarter-car indicate the SAVGS potential to enhance suspension performance, in terms of ride comfort and road holding. Practical features in the test rig are further considered and included in the nonlinear model to compensate the difference between the theoretical and testing behaviors. Experiments with a sinusoidal road, a smoothed bump and hole, and a random road are performed to evaluate the SAVGS practical feasibility and performance improvement, the accuracy of the model, and the robustness of the control schemes. Compared with the conventional passive suspension, ride comfort improvements of up to 41% without any deterioration of the suspension deflection are demonstrated, while the SAVGS actuator power is kept very low, at levels below 500 W.

Faster algorithms for extensive-form game solving via improved smoothing functions

Sparse iterative methods, in particular first-order methods, are known to be among the most effective in solving large-scale two-player zero-sum extensive-form games. The convergence rates of these methods depend heavily on the properties of the distance-generating function that they are based on. We investigate both the theoretical and practical performance improvement of first-order methods (FOMs) for solving extensive-form games through better design of the dilated entropy function—a class of distance-generating functions related to the domains associated with the extensive-form games. By introducing a new weighting scheme for the dilated entropy function, we develop the first distance-generating function for the strategy spaces of sequential games that has only a logarithmic dependence on the branching factor of the player. This result improves the overall convergence rate of several FOMs working with dilated entropy function by a factor of $$\Omega (b^dd)$$, where b is the branching factor of the player, and d is the depth of the game tree. Thus far, counterfactual regret minimization methods have been faster in practice, and more popular, than FOMs despite their theoretically inferior convergence rates. Using our new weighting scheme and a practical parameter tuning procedure we show that, for the first time, the excessive gap technique, a classical FOM, can be made faster than the counterfactual regret minimization algorithm in practice for large games, and that the aggressive stepsize scheme of CFR+ is the only reason that the algorithm is faster in practice.

Dynamic off-resonance correction for spiral real-time MRI of speech.

To improve the depiction and tracking of vocal tract articulators in spiral real-time MRI (RT-MRI) of speech production by estimating and correcting for dynamic changes in off-resonance. The proposed method computes a dynamic field map from the phase of single-TE dynamic images after a coil phase compensation where complex coil sensitivity maps are estimated from the single-TE dynamic scan itself. This method is tested using simulations and in vivo data. The depiction of air-tissue boundaries is evaluated quantitatively using a sharpness metric and visual inspection. Simulations demonstrate that the proposed method provides robust off-resonance correction for spiral readout durations up to 5 ms at 1.5T. In -vivo experiments during human speech production demonstrate that image sharpness is improved in a majority of data sets at air-tissue boundaries including the upper lip, hard palate, soft palate, and tongue boundaries, whereas the lower lip shows little improvement in the edge sharpness after correction. Dynamic off-resonance correction is feasible from single-TE spiral RT-MRI data, and provides a practical performance improvement in articulator sharpness when applied to speech production imaging.

Missed opportunities for improving practice performance in adult immunizations: a meta-narrative review of the literature

BackgroundWe sought to characterize how the term “missed opportunities” is reported in the literature in the context of immunization rates and to assess how missed opportunities can be operationalized.MethodsPeer-reviewed literature searches were conducted in April – May, 2015, to answer: “What methods research studies used to operationalize missed opportunities to vaccinate?” A meta-narrative review methodology was used.ResultsSeven studies met inclusion criteria. The methodologies for quantifying missed opportunities fell into two general categories based on: 1. the number of healthcare encounters per patient without appropriate vaccination services, defined as a number of visits per patient with no vaccination related services (Missed opportunities per patient); 2. vaccination status as “non-vaccinated” among a group of patients who had a healthcare encounter where the vaccination should/could have had happened (Missed opportunities per population).ConclusionsOur study provided an initial overview of the methods reported in the literature, and concluded that the quantifiable missed opportunity holds promise as a measurable outcome (variable) for research and quality improvement projects aimed to increase adult immunization recommendation and uptake in primary care.

Assessing and enhancing quality through outcomes-based continuing professional development (CPD): a review of current practice

Numerous professional bodies have questioned whether traditional input-based continuing professional development (CPD) schemes are effective at measuring genuine learning and improving practice performance and patient health. The most commonly used...

Effect of Physician it Use on Practice Performance

The role of information technology (IT) remains important within the medical community. However, little is known about the extent to which practicing physicians improve practice performance by having and utilizing IT at the national level. The present study, analyzing a national physician survey (n = 4,720), seeks to explore associations of IT availability and utilization with practice performance at the national level. The multivariate regression analysis results suggest that patient information IT functionality upholds physician advantages in annual income but prescription drug IT functionality was reversely linked to annual income. We also found a negative association of patient information IT functionality with patient visit volume. Our study results revealed mixed findings. Not all IT functionalities would offer benefits to practicing physicians. Our data suggest that patient information IT functionality can moderate cost concerns related to IT investment among providers.

Assuring Quality Cancer Survivorship Care: We've Only Just Begun.

Clinical practice guidelines, quality metrics, and performance improvement projects are the key tools of the national movement to improve and assure quality cancer care. Each of these evaluation instruments is intended to assess quality from a unique perspective, including that of the individual provider, the practice/hospital, and the health care system. A number of organizations have developed or endorsed quality measures specific to cancer, however, these have not formally included survivorship measures. Fortunately, the American Society of Clinical Oncology (ASCO), the National Comprehensive Cancer Network, the American Cancer Society, and the American College of Surgeons (ACoS) have taken a leadership role in developing survivorship guidelines and quality metrics. Both ASCO and ACoS have focused their efforts on the treatment summary and care plan, a document that was proposed in the 2006 Institute of Medicine report on cancer survivorship. ASCO has proposed a care plan template for implementation and incorporation into the electronic health records (EHR), which will lend itself to structure, process, and outcome measurement. ACoS, conversely, has included the care plan in its cancer program standards with annual evaluation metrics. In addition, ASCO has developed a number of key survivorship-relevant metrics as part of its Quality Oncology Practice Initiative (QOPI), a tool developed to measure quality cancer care and assess adherence to guidelines across academic and community practices. Together, these efforts will direct us to more effective ways to disseminate guideline recommendations and to better methods of assessing quality survivorship care nationally.