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"Total Quality Management methods."
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How can we recognize continuous quality improvement?
Objective. Continuous quality improvement (CQI) methods are foundational approaches to improving healthcare delivery. Publications using the term CQI, however, are methodologically heterogeneous, and labels other than CQI are used to signify relevant approaches. Standards for identifying the use of CQI based on its key methodological features could enable more effective learning across quality improvement (QI) efforts. The objective was to identify essential methodological features for recognizing CQI. Design. Previous work with a 12-member international expert panel identified reliably abstracted CQI methodological features. We tested which features met rigorous a priori standards as essential features of CQI using a three-phase online modified-Delphi process. Setting. Primarily United States and Canada. Participants. 119 QI experts randomly assigned into four on-line panels. Intervention(s). Participants rated CQI features and discussed their answers using online, anonymous and asynchronous discussion boards. We analyzed ratings quantitatively and discussion threads qualitatively. Main outcome measure(s). Panel consensus on definitional CQI features. Results. Seventy-nine (66%) panelists completed the process. Thirty-three completers self-identified as QI researchers, 18 as QI practitioners and 28 as both equally. The features 'systematic data guided activities,' 'designing with local conditions in mind' and 'iterative development and testing' met a priori standards as essential CQI features. Qualitative analyses showed cross-cutting themes focused on differences between QI and CQI. Conclusions. We found consensus among a broad group of CQI researchers and practitioners on three features as essential for identifying QI work more specifically as 'CQI.' All three features are needed as a minimum standard for recognizing CQI methods.
Journal Article
A Practice Change Model for Quality Improvement in Primary Care Practice
Faced with a rapidly changing healthcare environment, primary care practices often have to change how they practice medicine. Yet change is difficult, and the process by which practice improvement can be understood and facilitated has not been well elucidated. Therefore, we developed a model of practice change using data from a quality improvement intervention that was successful in creating a sustainable practice improvement. A multidisciplinary team evaluated data from the Study To Enhance Prevention by Understanding Practice (STEP-UP), a randomized clinical trial conducted to improve the delivery of evidence-based preventive services in 79 northeastern Ohio practices. The team conducted comparative case-study analyses of high- and low-improvement practices to identify variables that are critical to the change process and to create a conceptual model for the change. The model depicts the critical elements for understanding and guiding practice change and emphasizes the importance of these elements' evolving interrelationships. These elements are (1) motivation of key stakeholders to achieve the target for change; (2) instrumental, personal, and interactive resources for change; (3) motivators outside the practice, including the larger healthcare environment and community; and (4) opportunities for change--that is, how key stakeholders understand the change options. Change is influenced by the complex interaction of factors inside and outside the practice. Interventions that are based on understanding the four key elements and their interrelationships can yield sustainable quality improvements in primary care practice.
Journal Article
Six sigma+lean toolset : mindset for successful implementation of improvement projects
The current, second edition of this book reflects the 15 years of practical experience with the Six Sigma+Lean toolbox. It is a comprehensive collection of all the tools necessary for project work and running workshops when improving processes. All tools have been illustrated in a clear and comprehensible structure with examples and tips for applying the tools included. The chronology corresponds to the procedure of an improvement project comprising the steps D(efine), M(easure), A(nalyze), I(mprove) and C(ontrol). The most important innovation of this edition is the fact that it guides the user to select the appropriate tool using questions. The paradigm change from a Toolset to a Mindset has proven worthwhile in project work and ensures that corporate problems are addressed with the goal of achieving efficient solutions rather than having a large quantity of perfect tools to choose from. The efficiency factor of work in projects and workshops will therefore improve significantly. Through this paradigm change, connected with its unique structure, this book provides an effective tool not only for project and workshop leaders but also for the executives/sponsors involved who will be guided to solve the given task formulation quickly and in a sustainable way.
Book
Patient-Based Real-Time Quality Control: Review and Recommendations
For many years the concept of patient-based quality control (QC) has been discussed and implemented in hematology laboratories; however, the techniques have not been widely implemented in clinical chemistry. This is mainly because of the complexity of this form of QC, as it needs to be optimized for each population and often for each analyte. However, the clear advantages of this form of QC, together with the ongoing realization of the shortcomings of “conventional” QC, have driven a need to provide guidance to laboratories to assist in deploying patient-based QC. This overview describes the components of a patient-based QC system (calculation algorithm, block size, truncation limits, control limits) and the relationship of these to the analyte being controlled. We also discuss the need for patient-based QC system optimization using patient data from the individual testing laboratory to reliably detect systematic errors while ensuring that there are few false alarms. The term patient-based real-time quality control covers many activities that use data from patient samples to detect analytical errors. These activities include the monitoring of patient population parameters such as the mean or median analyte value or using single within-patient changes such as the delta check. In this report, we will restrict the discussion to population-based parameters. This overview is intended to serve as a guide for the implementation of a patient-based QC system. The report does not cover the clinical evaluation of the population.
Journal Article
How Intermountain Trimmed Health Care Costs Through Robust Quality Improvement Efforts
It has been estimated that full implementation of the Affordable Care Act will extend coverage to thirty-two million previously uninsured Americans. However, rapidly rising health care costs could thwart that effort. Since 1988 Intermountain Healthcare has applied to health care delivery the insights of W. Edwards Deming's process management theory, which says that the best way to reduce costs is to improve quality. Intermountain achieved such quality-based savings through measuring, understanding, and managing variation among clinicians in providing care. Intermountain created data systems and management structures that increased accountability, drove improvement, and produced savings. For example, a new delivery protocol helped reduce rates of elective induced labor, unplanned cesarean sections, and admissions to newborn intensive care units. That one protocol saves an estimated $50 million in Utah each year. If applied nationally, it would save about $3.5 billion. \"Organized care\" along these lines may be central to the long-term success of health reform. [PUBLICATION ABSTRACT]
Journal Article
From resilience to satisfaction: Defining supply chain solutions for agri-food SMEs through quality approach
Since it is an important human need and many organizations are involved in the value chain, the agricultural food supply chain is exposed to various risks that arise naturally or through human actions. This study aims to develop the application of a quality function deployment approach to increase the resilience of the food supply chain by understanding customer needs and logistical risks in the food supply chain. In-depth studies with empirical analysis were conducted to determine the importance of customer needs, food supply chain risks, and actions to improve supply chain resilience of SMEs in the agri-food industry. The result shows that the top three customer needs are \"attractive, bright color\", \"firm texture\" and \"fresh smell\". The top three risks in the agri-food supply chain are \"improper storage,\" \"Harvest Failure\" and \"Human Resource Risks\" and the top three resilience actions are \"continuous training,\" \"preventive maintenance,\" and \"supply chain forecasting.\" The implications of this study are to propose an idea that broadens the perspective of supply chain resilience in the agri-food industry by incorporating the needs of customers in considering how to mitigate the existing risks to the satisfaction of customers, and it also highlights the relatively low skill and coordination of the workforce in agri-food supply chains.
Journal Article