DOUBLE-SIDED LATEX PRINT JOB WORKFLOW IMPROVEMENT

Printing of small-width, double-side latex print jobs is performed with a 25% improvement in productivity by simultaneously printing the first side of each print job on separate media rolls

Crawfordsville Technical Services Asset Management Workflow Improvement Project

The Indiana Department of Transportation (INDOT) is divided into six districts, with district offices located in LaPorte, Fort Wayne, Crawfordsville, Greenfield, Vincennes, and Seymour. Each district has a Technical Services Department responsible for (with support from INDOT Central Office staff) managing the INDOT assets within the district and providing technical support to the district (including capital programs, maintenance, construction projects, and others). They also provide input to Statewide Asset Management and Capital Programs. Each Technical Services Department has assigned Asset Owners responsible for management of assets such as roadways/pavement, bridges, large culverts, small culverts, traffic/safety, mobility, and (in the case of Crawfordsville) drainage

Analog to Digital Workflow Improvement: A Quantitative Study

This study tracked a radiology department’s conversion from utilization of a Kodak Amber analog system to a Kodak DirectView DR 5100 digital system. Through the use of ProModel(®) Optimization Suite, a workflow simulation software package, significant quantitative information was derived from workflow process data measured before and after the change to a digital system. Once the digital room was fully operational and the radiology staff comfortable with the new system, average patient examination time was reduced from 9.24 to 5.28 min, indicating that a higher patient throughput could be achieved. Compared to the analog system, chest examination time for modality specific activities was reduced by 43%. The percentage of repeat examinations experienced with the digital system also decreased to 8% vs. the level of 9.5% experienced with the analog system. The study indicated that it is possible to quantitatively study clinical workflow and productivity by using commercially available software

Analysis of Pharmacy Technician Workflow and the Identification of Opportunities for Improvement

PURPOSE: The objective of this study was to identify opportunities for pharmacy technician workflow improvement using the principles of Lean Six Sigma. The impact of this study may streamline pharmacy technician workflow as well as eliminate/consolidate tasks resulting in increased efficiency while maintaining quality. METHODS: This study took place at St. Luke’s Episcopal Hospital (SLEH) in Houston, TX. The focus group was used to identify the problem. Two methods for data collection were utilized to establish baseline information; automated information and observational time and motion studies. Observational and automated data was presented to the focus group and the focus group was responsible for recommending and piloting changes. The focus group also identified pharmacy technician tasks that needed improvement as well as relate these tasks back to the voice of the customer and task purpose. Data was presented to the focus group and the focus group was responsible for recommending and piloting changes. The suggested changes were implemented in a pilot study. RESULTS: The focus group identified “ordered medications not loaded” (OMNL) as an area for workflow improvement. OMNL cycle time was defined as the time from when the user logs in the Acudose machine to the point the user completed the OMNL process. There were five parts to OMNL which were conducted at various times throughout the day: restocking, pulling, assigning, unassigning and loading. Time studies were conducted and technicians were shadowed on all three shifts. Observational and automated data findings were presented to focus group. These studies found technicians spent approximately 69.5 hours a week on OMNL for 1096 line items. On average, a patient had an active order for this medication for 2 days. The focus group recommended two changes to the OMNL process. The first change was to consolidate the three aspects of OMNL to one step. The second was to eliminate loading scheduled daily medications during OMNL. These changes were piloted and implemented which resulted in reducing OMNL by 39.1% and a net time savings of 33.6 hours a week. Although the cart fill volume did increase, there was no impact on missing doses. CONCLUSION: The application of Lean Six Sigma can improve operational workflow of pharmacy technicians as well as reduce waste as seen in this study. The SLEH should continue to utilize these concepts to identify further opportunities for pharmacy technician workflow improvement and reduction in waste.Pharmacy, College o

The informational system model of Ukrainian national transport workflow improvement based on electronic signature introduction management

Proposed model of informational system supposes improvement of newconceptual method on the work with e-signature in transport nformational systems. Problems and aims that may be solved with the help of this system and the most important economical and technical advantages of the proposed system in comparison with traditional methods of e-signing use are marked out

Quality Improvement of Workflow for Contrast-Enhanced Mammography

This project is a workflow quality improvement for Contrast-Enhanced Mammography (CEM) at Rush Breast Imaging. With this new technology being implemented, workflow improvement has been noted. The method used in this initiative was Plan-Do-Study Act (PDSA) and involved observation while exams were being performed. Standard operating procedures (SOP’s) were written up for internal stakeholders. Findings are monitored from feedback given from internal and external stakeholders on the workflow setup. Findings that have been noted so far are: issues starting IV’s, limited positioning of patients, and communication on certain areas with the procedure. Since this exam is still new, continued adjustments to the workflow will be made from workflow observations and feedback

IMRT QA using machine learning: A multi-institutional validation.

PurposeTo validate a machine learning approach to Virtual intensity-modulated radiation therapy (IMRT) quality assurance (QA) for accurately predicting gamma passing rates using different measurement approaches at different institutions.MethodsA Virtual IMRT QA framework was previously developed using a machine learning algorithm based on 498 IMRT plans, in which QA measurements were performed using diode-array detectors and a 3%local/3 mm with 10% threshold at Institution 1. An independent set of 139 IMRT measurements from a different institution, Institution 2, with QA data based on portal dosimetry using the same gamma index, was used to test the mathematical framework. Only pixels with ≥10% of the maximum calibrated units (CU) or dose were included in the comparison. Plans were characterized by 90 different complexity metrics. A weighted poison regression with Lasso regularization was trained to predict passing rates using the complexity metrics as input.ResultsThe methodology predicted passing rates within 3% accuracy for all composite plans measured using diode-array detectors at Institution 1, and within 3.5% for 120 of 139 plans using portal dosimetry measurements performed on a per-beam basis at Institution 2. The remaining measurements (19) had large areas of low CU, where portal dosimetry has a larger disagreement with the calculated dose and as such, the failure was expected. These beams need further modeling in the treatment planning system to correct the under-response in low-dose regions. Important features selected by Lasso to predict gamma passing rates were as follows: complete irradiated area outline (CIAO), jaw position, fraction of MLC leafs with gaps smaller than 20 or 5 mm, fraction of area receiving less than 50% of the total CU, fraction of the area receiving dose from penumbra, weighted average irregularity factor, and duty cycle.ConclusionsWe have demonstrated that Virtual IMRT QA can predict passing rates using different measurement techniques and across multiple institutions. Prediction of QA passing rates can have profound implications on the current IMRT process

Capability development in Chinese manufacturing:a quasi-biotic perspective of knowledge evolution

A quasi-biotic model of knowledge evolution has been applied to manufacturing technology capability development which includes product design and development and manufacturing process/workflow improvement. The concepts of “knowledge genes” and “knowledge body” are introduced to explain the evolution of technological capability. It is shown that knowledge development within the enterprise happens as a result of interactions between an enterprise’s internal knowledge and that acquired from external sources catalysed by: (a) internal mechanisms, recources and incentives, and (b) actions and policies of external agencies. A matrix specifying factors contributing to knowledge development and types of manufacturing capabilities (product design, equipment development or use, and workflow) is developed to explain technological knowledge development. The case studies of Tianjin Pipe Corporation (TPCO) and Tianjin Tianduan Press Co. are presented to illustrate the application of the matrix