The Experts below are selected from a list of 494295 Experts worldwide ranked by ideXlab platform
Johanna I Westbrook - One of the best experts on this subject based on the ideXlab platform.
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validation of the work Observation Method by activity timing wombat Method of conducting time motion Observations in critical care settings an Observational study
BMC Medical Informatics and Decision Making, 2011Co-Authors: Mark Ballermann, Nicola T Shaw, Damon C Mayes, R Noel T Gibney, Johanna I WestbrookAbstract:Background: Electronic documentation handling may facilitate information flows in health care settings to support better coordination of care among Health Care Providers (HCPs), but evidence is limited. Methods that accurately depict changes to the workflows of HCPs are needed to assess whether the introduction of a Critical Care clinical Information System (CCIS) to two Intensive Care Units (ICUs) represents a positive step for patient care. To evaluate a previously described Method of quantifying amounts of time spent and interruptions encountered by HCPs working in two ICUs. Methods: Observers used PDAs running the Work Observation Method By Activity Timing (WOMBAT) software to record the tasks performed by HCPs in advance of the introduction of a Critical Care clinical Information System (CCIS) to quantify amounts of time spent on tasks and interruptions encountered by HCPs in ICUs. Results: We report the percentages of time spent on each task category, and the rates of interruptions observed for physicians, nurses, respiratory therapists, and unit clerks. Compared with previously published data from Australian hospital wards, interdisciplinary information sharing and communication in ICUs explain higher proportions of time spent on professional communication and documentation by nurses and physicians, as well as more frequent interruptions which are often followed by professional communication tasks. Conclusions: Critical care workloads include requirements for timely information sharing and communication and explain the differences we observed between the two datasets. The data presented here further validate the WOMBAT Method, and support plans to compare workflows before and after the introduction of electronic documentation Methods in ICUs.
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design application and testing of the work Observation Method by activity timing wombat to measure clinicians patterns of work and communication
International Journal of Medical Informatics, 2009Co-Authors: Johanna I Westbrook, Amanda J AmptAbstract:Abstract Background Evidence regarding how health information technologies influence clinicians' patterns of work and support efficient practices is limited. Traditional paper-based data collection Methods are unable to capture clinical work complexity and communication patterns. The use of electronic data collection tools for such studies is emerging yet is rarely assessed for reliability or validity. Aim Our aim was to design, apply and test an Observational Method which incorporated the use of an electronic data collection tool for work measurement studies which would allow efficient, accurate and reliable data collection, and capture greater degrees of work complexity than current approaches. Methods We developed an Observational Method and software for personal digital assistants (PDAs) which captures multiple dimensions of clinicians' work tasks, namely what task, with whom, and with what; tasks conducted in parallel (multi-tasking); interruptions and task duration. During field-testing over 7 months across four hospital wards, fifty-two nurses were observed for 250h. Inter-rater reliability was tested and validity was measured by (i) assessing whether Observational data reflected known differences in clinical role work tasks and (ii) by comparing Observational data with participants' estimates of their task time distribution. Results Observers took 15–20h of training to master the Method and data collection process. Only 1% of tasks observed did not match the classification developed and were classified as ‘other'. Inter-rater reliability scores of observers were maintained at over 85%. The results discriminated between the work patterns of enrolled and registered nurses consistent with differences in their roles. Survey data ( n =27) revealed consistent ratings of tasks by nurses, and their rankings of most to least time-consuming tasks were significantly correlated with those derived from the Observational data. Over 40% of nurses' time was spent in direct care or professional communication, with 11.8% of time spent multi-tasking. Nurses were interrupted approximately every 49min. One quarter of interruptions occurred while nurses were preparing or administering medications. Conclusions This Method efficiently produces reliable and valid data. The multi-dimensional nature of the data collected provides greater insights into patterns of clinicians' work and communication than has previously been possible using other Methods.
Amanda J Ampt - One of the best experts on this subject based on the ideXlab platform.
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design application and testing of the work Observation Method by activity timing wombat to measure clinicians patterns of work and communication
International Journal of Medical Informatics, 2009Co-Authors: Johanna I Westbrook, Amanda J AmptAbstract:Abstract Background Evidence regarding how health information technologies influence clinicians' patterns of work and support efficient practices is limited. Traditional paper-based data collection Methods are unable to capture clinical work complexity and communication patterns. The use of electronic data collection tools for such studies is emerging yet is rarely assessed for reliability or validity. Aim Our aim was to design, apply and test an Observational Method which incorporated the use of an electronic data collection tool for work measurement studies which would allow efficient, accurate and reliable data collection, and capture greater degrees of work complexity than current approaches. Methods We developed an Observational Method and software for personal digital assistants (PDAs) which captures multiple dimensions of clinicians' work tasks, namely what task, with whom, and with what; tasks conducted in parallel (multi-tasking); interruptions and task duration. During field-testing over 7 months across four hospital wards, fifty-two nurses were observed for 250h. Inter-rater reliability was tested and validity was measured by (i) assessing whether Observational data reflected known differences in clinical role work tasks and (ii) by comparing Observational data with participants' estimates of their task time distribution. Results Observers took 15–20h of training to master the Method and data collection process. Only 1% of tasks observed did not match the classification developed and were classified as ‘other'. Inter-rater reliability scores of observers were maintained at over 85%. The results discriminated between the work patterns of enrolled and registered nurses consistent with differences in their roles. Survey data ( n =27) revealed consistent ratings of tasks by nurses, and their rankings of most to least time-consuming tasks were significantly correlated with those derived from the Observational data. Over 40% of nurses' time was spent in direct care or professional communication, with 11.8% of time spent multi-tasking. Nurses were interrupted approximately every 49min. One quarter of interruptions occurred while nurses were preparing or administering medications. Conclusions This Method efficiently produces reliable and valid data. The multi-dimensional nature of the data collected provides greater insights into patterns of clinicians' work and communication than has previously been possible using other Methods.
Dachuan Tang - One of the best experts on this subject based on the ideXlab platform.
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improved perturb and Observation Method based on support vector regression
Energies, 2019Co-Authors: Xin Ke, Dachuan TangAbstract:Solar energy is the most valuable renewable energy source due to its abundant storage and is pollution-free. The output power of photovoltaic (PV) arrays will vary with external conditions, such as irradiance and temperature fluctuations. Therefore, an increase in the energy conversion rate is inseparable from maximum power point tracking (MPPT). The existing MPPT technology cannot either balance the tracking speed and tracking accuracy, or the implementation cost is too high due to the complexity of the calculation. In this paper, a new maximum power point tracking (MPPT) Method was proposed. It improves the traditional perturb and Observation (P&O) Method by introducing the support vector regression (SVR) algorithm. In this Method, the current maximum power point voltage is predicted by the trained model and compared with the current operating voltage to predict a reasonable step size. The boost DC/ DC (Direct current-Direct current converter) convert system applying the improved Method and the traditional P&O was simulated in MATLAB-Simulink, respectively. The results of the simulation show that compared with the traditional P&O Method, the proposed new Method both improves the convergence time and tracking accuracy.
Yamei Zhang - One of the best experts on this subject based on the ideXlab platform.
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using in situ Observation to understand the leaching behavior of portland cement and alkali activated slag pastes
Composites Part B-engineering, 2019Co-Authors: Zijian Jia, Ruilin Cao, Chun Chen, Yamei ZhangAbstract:Abstract This paper presents the leaching behavior of hydration products and unhydrated particles in Portland cement (PC) and alkali-activated slag (AAS) systems with a new in-situ Observation Method. After leaching in NH4Cl solution, obvious decalcification can be found in unhydrated C3S and C2S in PC, while the unhydrated slag keeps stable in AAS. The Ca in the gel of AAS is more vulnerable to leaching than that in PC due to the lack of phases with buffering capability like portlandite. In addition, the Mg–Al layered double hydroxide, which mainly exists in the dark rim of AAS, is not stable in NH4Cl solution. The in-situ Observation Method proposed in this study provides a new Methodology to investigate the leaching behavior of different phases directly and helps to understand the effect of leaching on cementitious materials from a new perspective, it can therefore be used to instruct the design of durable cementitious systems.
Xin Ke - One of the best experts on this subject based on the ideXlab platform.
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improved perturb and Observation Method based on support vector regression
Energies, 2019Co-Authors: Xin Ke, Dachuan TangAbstract:Solar energy is the most valuable renewable energy source due to its abundant storage and is pollution-free. The output power of photovoltaic (PV) arrays will vary with external conditions, such as irradiance and temperature fluctuations. Therefore, an increase in the energy conversion rate is inseparable from maximum power point tracking (MPPT). The existing MPPT technology cannot either balance the tracking speed and tracking accuracy, or the implementation cost is too high due to the complexity of the calculation. In this paper, a new maximum power point tracking (MPPT) Method was proposed. It improves the traditional perturb and Observation (P&O) Method by introducing the support vector regression (SVR) algorithm. In this Method, the current maximum power point voltage is predicted by the trained model and compared with the current operating voltage to predict a reasonable step size. The boost DC/ DC (Direct current-Direct current converter) convert system applying the improved Method and the traditional P&O was simulated in MATLAB-Simulink, respectively. The results of the simulation show that compared with the traditional P&O Method, the proposed new Method both improves the convergence time and tracking accuracy.
