Performance Improvement in Healthcare

2020 ◽  
pp. 210-221
Author(s):  
Candice Freeman ◽  
Jill Erin Stefaniak
Keyword(s):  
Disciplinary Action ◽  
Engineering Model ◽  
Healthcare Leadership ◽  
Just Culture ◽  
Quality Patient Care ◽  
Management Personnel ◽  
Behavior Engineering Model ◽  
Sentinel Event ◽  
Action Process

Healthcare leadership and department management personnel are tasked with the responsibility of ensuring safe, high-quality patient care delivered by competent and proficient staff. This responsibility often comes in the form of identification of discrepant and erroneous practices that result in subsequent employee disciplinary action process improvement discussions and implementation. This case study presents an example of a sentinel event and how Gilbert's Behavior Engineering Model (BEM) was utilized in the context of a Just Culture to ensure both processes and personnel were adequately supported to meet expected task outcomes.

Blending Front-End Analysis

2019 ◽  
pp. 934-965
Author(s):  
Beth McGoldrick
Keyword(s):  
Performance Improvement ◽  
Engineering Model ◽  
Improve Performance ◽  
Front End ◽  
Behavior Engineering Model ◽  
Underlying Causes ◽  
Behavior Engineering ◽  
Performance Problems

Performance problems come in all forms. The method presented in this chapter blends the models of three respected Performance improvement icons – Joe Harless, Thomas Gilbert, and Roger Chevalier. Their theoretical and practical approaches are applied to a case study. The three models – 13 Smart Questions (Front-end analysis), Behavior Engineering Model (BEM), and Updated BEM – when combined show ways practitioners can assess and improve performance. The practitioner will develop effective partnerships with clients, gain valuable perspectives on the issues, and their underlying causes. Finally the practitioner will be able to lead a department or an organization in fully analyzing problems and determining how best to solve them.

Blending Front-End Analysis

2015 ◽  
pp. 344-383
Author(s):  
Beth McGoldrick
Keyword(s):  
Performance Improvement ◽  
Engineering Model ◽  
Improve Performance ◽  
Front End ◽  
Behavior Engineering Model ◽  
Underlying Causes ◽  
Behavior Engineering ◽  
Performance Problems

Performance problems come in all forms. The method presented in this chapter blends the models of three respected Performance improvement icons – Joe Harless, Thomas Gilbert, and Roger Chevalier. Their theoretical and practical approaches are applied to a case study. The three models – 13 Smart Questions (Front-end analysis), Behavior Engineering Model (BEM), and Updated BEM – when combined show ways practitioners can assess and improve performance. The practitioner will develop effective partnerships with clients, gain valuable perspectives on the issues, and their underlying causes. Finally the practitioner will be able to lead a department or an organization in fully analyzing problems and determining how best to solve them.

scholarly journals Errors in documenting the subsoil and their impact on the investment implementation: Case study

2021 ◽  
Vol 11 (1) ◽  
pp. 744-754
Author(s):  
Marzena Lendo-Siwicka ◽  
Grzegorz Wrzesiński ◽  
Katarzyna Pawluk
Keyword(s):  
Construction Projects ◽  
Organic Soils ◽  
Cohesive Soils ◽  
Engineering Model ◽  
Limit States ◽  
Uplift Pressure ◽  
Geological Engineering ◽  
Jet Grouting ◽  
Geotechnical Category

Abstract Improper recognition of the subsoil is the most common cause of problems in the implementation of construction projects and construction facilities failures. Most often, their direct cause is the mismatch of the scope of geotechnical diagnosis to the appropriate geotechnical category, or substantive errors, including incomplete or incorrect interpretation in the creation of a geological-engineering model and often overlooked hydrogeological conditions. In many cases, insufficient recognition and documentation of geotechnical and/or geological and engineering conditions leads to damage and construction failures, delays in consider construction, and the increase of the investment budget. That’s why, in order to avoid the above, particular attention should be paid to proper geotechnical and geological-engineering documentation at the design and construction stages. The selected example of the investment analyzed errors in the geological-engineering documentation, which mainly concerned the lack of recognition of locally occurring organic soils, the incorrectly determined location of the groundwater table and the degree of compaction of non-cohesive soils, and numerous errors of calculated values of soil uplift pressure. The detection of the errors presented in the paper made it possible to select the correct technology for the construction of the sanitary sewage system and to increase the thickness of the horizontal shutter made of jet grouting columns in the area of the excavation. In addition, the article discusses the principles of proper calculation of limit states and subsoil testing, which have a significant impact on the implementation of planned investments.

Barriers to Adopting Technology for Teaching and Learning

2020 ◽  
pp. 66-79
Author(s):  
Equi Emmanuel Nwulu
Keyword(s):  
Technology Adoption ◽  
Instructional Practices ◽  
Change Process ◽  
Teaching And Learning ◽  
New Technologies ◽  
Teacher Behaviors ◽  
Engineering Model ◽  
Cultural Research ◽  
Behavior Engineering Model ◽  
Cross Cultural Research

The purpose of this chapter is to use a cross-cultural research-based evidence to discuss the root causes of barriers to effective technology adoption by evaluating the effect the teaching environment and the ranges of teacher behaviors have on technology adoption. The author described and explained the change processes that teachers go through as they implement new technologies or instructional practices with a view to connecting the change process, the innovation, and the individuals involved in the process. Two overarching frameworks that guided the author's discussion of this chapter and the behavior engineering model (BEM) and the concerns-based model (CBAM) frameworks.

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