The Continuous Learning Cycle: A Multi-phase Post-occupancy Evaluation (POE) of Decentralized Nursing Unit Design

2021 ◽  
pp. 193758672110516
Author(s):  
Hui Cai ◽  
Kent Spreckelmeyer
Keyword(s):  
Phase I ◽  
Lessons Learned ◽  
Learning Cycle ◽  
Continuous Learning ◽  
Patient Room ◽  
Design Quality ◽  
Syntax Analysis ◽  
Nursing Unit ◽  
Unit Unit ◽  
Multi Phase

Purpose: This study aims to demonstrate how multiphase postoccupancy evaluation (POE) research was integrated into multiple projects to develop a continuous learning cycle. Background: Despite the well-recognized importance of POE, few studies have reported how knowledge from POE is applied in new designs. Method: This study is developed as a multiphase POE that spanned 3 years and across three units. Phase I POE compared an existing unit (Unit A) in Hospital A and a new Unit B in Hospital B that has implemented innovative design features such as decentralized nurse stations. The idea was to understand the challenges of the existing facility in Hospital A and gather lessons learned from the new design in Unit B to inform the design of the Hospital A expansion (Unit C). After the new expansion was occupied, the Phase II POE was conducted using the same set of POE tools in both Unit C and Unit A. The POE applied the following methods: (1) patient room evaluations using the Center for Health Design standardized POE tools, (2) space syntax analysis of visibility, and (3) a pre- and postmove analysis of Press Ganey data. Results: The results demonstrated that by incorporating lessons learned from the Phase I POE, Unit C has further improvement on patient room design ratings, improved patient satisfaction, and better visibility among nurse work areas compared to Unit A and Unit B. Conclusions: The multiphase, multisite POE with standardized tools has demonstrated its value as an important tool for continuous design quality improvement.

LESSONS LEARNED FROM CROSS-VALIDATION OF FIBER OPTICS AND PRODUCTION LOGGING CLUSTER PERFORMANCE ASSESSMENT IN THE UNCONVENTIONAL WELLS

2021 ◽  
Author(s):  
Yegor Se ◽  
◽  
Michael Sullivan ◽  
Vahid Tohidi ◽  
Michael Lazorek ◽  
...  
Keyword(s):  
Fiber Optics ◽  
Cross Validation ◽  
Flow Behavior ◽  
Lessons Learned ◽  
Unconventional Reservoirs ◽  
Sensor Technology ◽  
Phase Flow ◽  
Cluster Performance ◽  
Multi Phase Flow ◽  
Multi Phase

The well design with long lateral section and multistage frac completion has been proven effective for development of the unconventional reservoirs. Top-tier well production in unconventional reservoir can be achieved by optimizing hydraulic completion and stimulation design, which necessitates an understanding of flow behavior and hydrocarbon contribution allocation.  Historically, conventional production logging (PL) surveys were scarcely used in unconventional reservoirs due to limited and often expensive conveyance options, as well as complicated and non-unique inflow interpretations caused by intricate and changing multi-phase flow behavior (Prakash et al., 2008). The assessment of the cluster performance gradually shifted towards distributed acoustic (DAS) and temperature (DTS) sensing methods using fiber optics cable, which continuously gained popularity in the industry. Fiber optics measurements were anticipated to generate production profiles along the lateral with sub-cluster resolution to assist with optimal completions design selection. Encapsulation of the fiber in the carbon rod provided alternative conveyance method for retrievable DFO measurements, which gained popularity due to cost-efficiency and operational convenience (Gardner et al., 2015). Recent utilization of micro-sensor technology in PL tools, (Abbassi et al, 2018, Donovan et al, 2019) allowed dramatic reduction of the size and the weight of the PL toolstring without compromising wellbore coverage by sensor array. Such ultra-compact PL toolstring could utilize the carbon rod as a taxi and provide mutually beneficial and innovative surveillance combination to evaluate production profile in the unconventional reservoirs. Array holdup and velocity measurements across wellbore from PL would reveal more details regarding multi-phase flow behavior, which could be used for cross-validation and constraining of production inflow interpretation based on DFO measurements. This paper summarizes the lessons learned, key observations and best practices from the unique 4 well program, where such innovative combination was tested in gas rich Duvernay shale reservoir.

Evaluating the Use of Cyberinfrastructure in the Classroom to Enhance Product Dissection

2007 ◽  
Author(s):  
Matt Devendorf ◽  
Kemper Lewis ◽  
Timothy W. Simpson ◽  
Robert B. Stone ◽  
William C. Regli
Keyword(s):  
Phase I ◽  
High Impact ◽  
Lessons Learned ◽  
Digital Design ◽  
Design Engineering ◽  
National Scale ◽  
Research Experiences ◽  
Ongoing Research ◽  
Information Tools ◽  
Digital Environments

Recent cyberinfrastructure initiatives seek to create ubiquitous, comprehensive, interactive, and functionally complete digital environments that consist of people, data, information, tools, and instruments for research communities. With product dissection as our unifying theme, we are forging a cyberinfrastructure to support undergraduate design engineering education through CIBER-U: Cyber-Infrastructure-Based Engineering Repositories for Undergraduates. CIBER-U pairs two of the nation’s leading design repository developers with several active users and their students to realize a high-impact application of cyberinfrastructure in engineering undergraduate curricula involving freshmen through seniors. Specifically, CIBER-U combines product dissection activities at three universities with two digital design repositories, CAD modeling and animation, video, MediaWiki technology, multimedia, and undergraduate summer research experiences to enable cyberinfrastructure-based product dissection activities. Nearly 700 students have participated in the Phase I efforts of CIBER-U, which have focused primarily on generating, capturing, and storing data in two digital design repositories. Lessons learned from these efforts are presented from the students’ perspectives as well as that of the faculty in both engineering and computer science. The implications for implementing CIBER-U on a national scale are discussed along with ongoing research.

scholarly journals An Empirical Examination of Nursing Units in China Based on Nurse Experience

2018 ◽  
Vol 12 (1) ◽  
pp. 108-123 ◽  
Author(s):  
Xiaodong Xuan ◽  
Zongfei Li ◽  
Xixi Chen
Keyword(s):  
Clinical Work ◽  
Patient Room ◽  
Empirical Examination ◽  
Nursing Unit ◽  
Spatial Design ◽  
Work Spaces ◽  
Physical Environments ◽  
Unit Design ◽  
Nurse Experience ◽  
Doctor's Office

Objectives: To create opportunities to increase nursing staff’s satisfaction and operational efficiency and eventually improve nurses’ experiences through better design in unit layout. Background: The majority of research performed on nursing units in China only focused on the spatial design itself, and few studies examined the nursing unit empirically based on nurses’ experience. Nursing units need to be designed with understanding nurses’ behavior and experience in China. Method: A mixed-method approach was conducted in four double-corridor nursing units in China. Observation and interview data were collected to explore how physical environments for managing administrative duties, medications, and caring patient were used in nursing units. Results: The most frequent activities were communication, medication, and patient-care activities. The places in which nurses spent the most of theirs working times were the nurse station (NS), patient room, workstation on wheels (WoW), and medication room. The important clinical work spaces were the patient room, NS, WoW, medication room, doctor’s office, disposal room, examining room, and back corridor. The important traffic linkages were between NS and medication room, patient room and WoW, and medication room and patient room. Conclusions: This article revealed the frequency of nurse activities; how they spent their time; how they use the clinical spaces; identified important clinical spaces, linkages, and driver of inefficiency in nursing work and nursing unit design; and finally generated recommendations for double-corridor nursing unit design in China which can be used by medical planner, hospital administrator.

Artificial Intelligence in Metrology Data Collection

2021 ◽  
Author(s):  
Michael Schwartz ◽  
Keyword(s):  
Artificial Intelligence ◽  
Data Collection ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Lessons Learned ◽  
Continuous Learning ◽  
Automate Data ◽  
Optical Character ◽  
Automate Data Collection ◽  
Continual Learning

Many companies have tried to automate data collection for handheld Digital Multimeters (DMM) using Optical Character Recognition (OCR). Only recently have companies tried to perform this task using Artificial Intelligence (AI) technology, Cal Lab Solutions being one of them in 2020. But when we developed our first prototype application, we discovered the difficulties of getting a good value with every measurement and test point.A year later, lessons learned and equipped with better software, this paper is a continuation of that AI project. In Beta-,1 we learned the difficulties of AI reading segmented displays. There are no pre-trained models for this type of display, so we needed to train a model. This required the testing of thousands of images, so we changed the scope of the project to a continual learning AI project. This paper will cover how we built our continuous learning AI model to show how any lab with a webcam can start automating those handheld DMMS with software that gets smarter over time.

Lessons Learned in Phase I of the Southern Rural Access Program

2003 ◽  
Vol 19 ◽  
pp. 416-421 ◽  
Author(s):  
Michael Beachler ◽  
Curtis Holloman ◽  
Donald E. Pathman
Keyword(s):  
Phase I ◽  
Lessons Learned ◽  
Rural Access ◽  
Access Program

Long Prairie River Watershed TMDL Project - Lessons Learned from Phase I

2013 ◽  
Author(s):  
Hafiz M. Munir ◽  
Bashar Sinokrot ◽  
Dennis E. Ford
Keyword(s):  
Phase I ◽  
Lessons Learned ◽  
River Watershed

EVALUATION OF AN AUTOMATED MULTI-PHASE APPROACH FOR PATTERNS DISCOVERY

2013 ◽  
Vol 23 (10) ◽  
pp. 1367-1398 ◽  
Author(s):  
NADIA BOUASSIDA ◽  
HANENE BEN-ABDALLAH ◽  
IMENE ISSAOUI
Keyword(s):  
Design Pattern ◽  
Design Patterns ◽  
Pattern Detection ◽  
Phase Detection ◽  
Structural Variations ◽  
Design Quality ◽  
Phase Approach ◽  
Detection Approach ◽  
Identification Technique ◽  
Multi Phase

Design patterns capitalize the knowledge of expert designers and offer reuse that provides for higher design quality and overall faster development. To attain these advantages, a designer must, however, overcome the difficulties in understanding design patterns and determining those appropriate for his/her particular application. On the other hand, one way to benefit from design patterns is to assist inexperienced designers in pattern detection during the design elaboration. Such detection should tolerate variations between the design and the pattern since the exact instantiation of a pattern is infrequent in a design. However, not all variations of a pattern are tolerated. In particular, some structural variations may result in non-optimal instantiations where the requirements are respected but the structure is different; such variations are called spoiled patterns and should also be detected and transformed into acceptable pattern instantiations. This paper first presents an improvement of our design/spoiled pattern detection approach, named MAPeD (Multi-phase Approach for Pattern Discovery). The latter uses an XML information retrieval technique to identify design/spoiled pattern occurrences in a design using, first, static and semantic information and, secondly, dynamic information. This multi-phase detection approach tolerates structural differences between the examined design and the identified design pattern. Furthermore, thanks to the matching information it collects, our identification technique can offer assistance for the improvement of a design. In its second contribution, this paper evaluates MAPeD by comparing its recall and precision rates for five open source systems: JHotDraw, JUnit, JRefactory, MapperXML, QuickUML. The latter were used by other approaches in experimental evaluations. Our evaluation shows that our design pattern identification approach has an average improvement of 9.98% in terms of precision over the best known approach.

scholarly journals Lessons Learned from Journey Mapping in Health Care

2019 ◽  
Vol 8 (1) ◽  
pp. 105-109
Author(s):  
Kyle Maddox ◽  
Donna Baggetta ◽  
Jennifer Herout ◽  
Kurt Ruark
Keyword(s):  
Health Care ◽  
Human Factors ◽  
Data Gathering ◽  
Lessons Learned ◽  
Human Factors Engineering ◽  
Department Of Veterans Affairs ◽  
Design Quality ◽  
User Research ◽  
Stakeholder Groups ◽  
Engineering Team

The Department of Veterans Affairs’ Human Factors Engineering team recognizes the value of journey maps as a means for communication among stakeholder groups and develops maps to showcase the experience of users with health services and technology systems. The uniqueness of health care environments caused difficulties in following available trade guidance for creating journey maps. Anticipating that other Human Factors Engineers working in health care settings will encounter similar challenges, this paper showcases our lessons learned while creating two distinct journey maps and offers a process for constructing journey maps in health care environments. We learned to selectively limit the content of journey maps, ensure design quality by utilizing a template and rubric, and apply alternate approaches for data gathering. Our improved process includes steps to partner with stakeholders, produce a journey map framework and confirm it with user research, and visualize findings in the completed journey map.

scholarly journals P023: Development of a Canadian Global Health Emergency Medicine (GHEM) Certificate Program based on established best practices

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S72-S73
Author(s):  
R. Stefan ◽  
J. Maskalyk ◽  
L. Puchalski Ritchie ◽  
M. Salmon ◽  
M. Landes
Keyword(s):  
Emergency Medicine ◽  
Best Practices ◽  
Global Health ◽  
Addis Ababa ◽  
Phase 1 ◽  
Lessons Learned ◽  
Certificate Program ◽  
University Of Toronto ◽  
Fellowship Programs ◽  
Multi Phase

Innovation Concept: Global health fieldwork is valuable for Canadian residents, but is often trainee-organized, short-term, unsupervised, and lacking in preparation and debriefing. In contrast, we have developed a Certificate Program which will be offered to University of Toronto (UofT) emergency medicine (EM) trainees in their final year of residency. This 6-month Program will complement the Transition to Practice stage for residents interested in becoming leaders in GHEM. Methods: We completed a multi-phase needs assessment to inform the structure and content of a GHEM Certificate Program. Phase 1 consisted of 9 interviews with Program Directors (PDs), Assistant PDs, and past fellows from existing GH fellowships in Canada and USA to understand program structure, curriculum, fieldwork and funding. In Phase 2 we interviewed 4 PDs and fellows from UofT fellowship programs to understand local administrative structures. In Phase 3 we collected feedback from 5 UofT residents and 7 faculty with experience in global health to assess interest in a local GHEM Program. All interview data was reviewed and best practices and lessons learned from key stakeholders were summarized into a proposed outline for a 6-month GHEM Certificate Program. Curriculum, Tool, or Material: The Program will comprise of 1) 3 months of preparatory work in Toronto followed by 2) 3 months of fieldwork in Addis Ababa, Ethiopia. Fieldwork will coincide with activities under the Toronto-Addis Ababa Academic Collaboration in Emergency Medicine (TAAAC-EM). The GHEM trainee's work will support TAAAC-EM activities. Preparatory months will include training in specific competencies (POCUS, teaching, tropical medicine, QI) and meetings between the trainee and a UofT mentor to design an academic project. During fieldwork, the trainee will do EM teaching (75% of time) and complete their academic project (25% of time). A UofT supervisor will accompany, orient and supervise the trainee for their first 2 weeks in Addis. Throughout fieldwork, the trainee will be required to debrief with their UofT mentor weekly for academic and clinical mentoring. One AAU faculty member will be identified as a local supervisor and will participate in all evaluations of the trainee during fieldwork. Conclusion: This Program will launch with a call for applications in July 2021, expecting the first trainee to complete the Program in 2022-23. We anticipate that this Program will increase the number of Canadian EM trainees committed to global health projects and partnerships throughout their career.

Large Scale Collaborative Science: Lessons Learned from the Phase I COFFIES DRIVE Science Center

2021 ◽  
Author(s):  
Shea Hess Webber ◽  
Lisa Upton ◽  
Andres Munoz-Jaramillo ◽  
Todd Hoeksema ◽  
Rock Bush ◽  
...  
Keyword(s):  
Phase I ◽  
Large Scale ◽  
Lessons Learned ◽  
Science Center
Sign in / Sign up

Export Citation Format

Share Document