Decreasing Preoperative Delays-A Rapid Process Improvement Project

AORN Journal ◽  
2003 ◽  
Vol 77 (4) ◽  
pp. 737-741 ◽  
Author(s):  
Judith Celik
Author(s):  
Pramila Kalaga ◽  
Barbara Wolford ◽  
Matthew Mormino ◽  
Timothy Kingston ◽  
Julie Fedderson ◽  
...  

The risk of a needle stick or sharps injury in the operating room (OR) is high due to conditions such as minimal physical protective measures, frequent transfer of sharps, and reliance on human attention and skill for injury avoidance. An ergonomic process improvement project was initiated at a large metro teaching hospital to identify ergonomic risk factors for these OR injuries. To maximize the engagement of the front- end users, an ergonomic process improvement (EPI) team was developed, consisting of representatives from participating OR teams, an employee health nurse and two ergonomists. Surveys, observations, and interviews were conducted to quantify injury risk for the OR teams, evaluate barriers to best practice adherence, and identify opportunities for targeted interventions. Risk mapping was completed for the surgeons, surgical techs and OR nurses identifying double gloving and safe passing zone as areas in need of improvement. Through observation and interviews, researchers identified physical factors relating to musculoskeletal pain and cognitive factors leading to distractions as safety risk concerns. The overall success of the EPI was the engagement of the OR teams and surgeons in the process of identifying risk factors and potential opportunities for ergonomic solutions related to cognitive workload, physical workload, teamwork, and work design for injury prevention. The risk factors identified will provide the basis for developing targeted, effective interventions for eliminating injuries from needles and sharps within the OR.


2016 ◽  
Vol 22 (6) ◽  
pp. 1099-1117 ◽  
Author(s):  
Boyd A. Nicholds ◽  
John P.T. Mo

Purpose The research indicates there is a positive link between the improvement capability of an organisation and the intensity of effort applied to a business process improvement (BPI) project or initiative. While a degree of stochastic variation in applied effort to any particular improvement project may be expected there is a clear need to quantify the causal relationship, to assist management decision, and to enhance the chance of achieving and sustaining the expected improvement targets. The paper aims to discuss these issues. Design/methodology/approach The paper presents a method to obtain the function that estimates the range of applicable effort an organisation can expect to be able to apply based on their current improvement capability. The method used analysed published data as well as regression analysis of new data points obtained from completed process improvement projects. Findings The level of effort available to be applied to a process improvement project can be expressed as a regression function expressing the possible range of achievable BPI performance within 90 per cent confidence limits. Research limitations/implications The data set applied by this research is limited due to constraints during the research project. A more accurate function can be obtained with more industry data. Practical implications When the described function is combined with a separate non-linear function of performance gain vs effort a model of performance gain for a process improvement project as a function of organisational improvement capability is obtained. The probability of success in achieving performance targets may be estimated for a process improvement project. Originality/value The method developed in this research is novel and unique and has the potential to be applied to assessing an organisation’s capability to manage change.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiju Antony ◽  
Bart A. Lameijer ◽  
Hans P. Borgman ◽  
Kevin Linderman

Purpose Although scholars have considered the success factors of process improvement (PI) projects, limited research has considered the factors that influence failure. The purpose of this paper is to extend the understanding of PI project failure by systematically reviewing the research on generic project failure, and developing research propositions and future research directions specifically for PI projects. Design/methodology/approach A systematic literature review protocol resulted in a total of 97 research papers that are reviewed for contributions on project failure. Findings An inductive category formation process resulted in three categories of findings. The first category are the causes for project failure, the second category is about relatedness between failure factors and the third category is on failure mitigation strategies. For each category, propositions for future research on PI projects specifically are developed. Additional future research directions proposed lay in better understanding PI project failure as it unfolds (i.e. process studies vs cross-sectional), understanding PI project failure from a theoretical perspective and better understanding of PI project failure antecedents. Originality/value This paper takes a multi-disciplinary and project type approach, synthesizes the existing knowledge and reflects upon the developments in the field of research. Propositions and a framework for future research on PI project failure are presented.


Author(s):  
Dessislava Pachamanova ◽  
Vera Tilson ◽  
Keely Dwyer-Matzky

This case discusses a process improvement project aimed at maximizing the use of hospital capacity as the flu season looms. Dr. Erin Kelly heads the observation unit and turns to predictive models to improve the assignment of patients to her unit. The case covers three major themes: (1) data analytics life cycle and interface of predictive and prescriptive analytics in the context of process improvement, (2) design and ethical application of machine learning models, and (3) effecting organizational change to operationalize the findings of the analysis. Realistic data, R code, and Excel models are provided. The rich context of the case allows for discussing change management in a healthcare organization, analytics problem framing and model mapping, service process capacity analysis and Little’s law, data summaries and visualizations, interpretable machine learning algorithms, evaluations of predictive model performance, algorithmic bias, and dealing with dirty data. The case is appropriate for use in courses in machine learning, business analytics, operations management, and operations research, both at the advanced undergraduate level and at the master’s/MBA level.


2005 ◽  
Author(s):  
Robert G. Keane ◽  
Howard Fireman ◽  
Daniel W. Billingsley

In October 1989, the Naval Sea Systems Command (NAVSEA) conducted the Ship Design for Producibility Workshop with broad participation from the Navy, Shipbuilders, Ship Design Agents and Academia. The Workshop was one of NAVSEA’s first Total Quality Leadership (TQL) initiatives and was subsequently expanded by NAVSEA’s Chief Engineer (CHENG) and the Deputy Assistant Secretary of the Navy (DASN) for Ships into the Ship Design, Acquisition, and Construction (DAC) Process Improvement Project. In addition, the National Shipbuilding Research Program (NSRP) initiated a number of thrusts in Concurrent Engineering and Increased Throughput. The authors describe one of these major process improvement initiatives, NAVSEA’s 3D “Product Model” Strategy to extend throughout the enterprise-wide process of warship development a primary focus on the bridge between ship design and shipbuilding. The Workshop and subsequent process improvement initiatives have had a profound impact on the Naval Ship Design Process. Yet, as reported to Congress in 2002 by the Secretary of the Navy, the unbudgeted cost growth and increased cycle times for Detail Design of new warships have “reached an untenable level”. This necessitated the October 2004 ASN (RDA) policy memorandum on Integrated Digital Data Environment (IDDE). To realize transformational innovations in our ship designs, as well as transformational innovations in the entire warship development process, the National Naval Responsibility in Naval Engineering (NNR-NE) was recently established by the Navy. To support NNR-NE the Office of Naval Research (ONR) and the Naval Sea Systems Command (NAVSEA) created the Center for Innovation in Ship Design (CISD). A summary of some recent CISD Innovation Cells and how CISD can contribute to breaking down the existing organizational cultures and institutionalizing a collaborative product development environment are also discussed. As we begin a new century, it is appropriate that our naval ship design and shipbuilding community review its progress, look at the cross-cut principles of leading change, determine what it takes to bring about dramatic cultural transformation, and discuss the critical need for Navy, Shipbuilder, Design Agent and Academia leadership to continue developing a new collaborative product development environment which fosters a sea change in the whole naval ship development process.


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