Continuous Quality Management of Breast Hypertrophy by the German Association of Plastic Surgeons: A Preliminary Report

59 Background: Sarah Cannon Blood Cancer Network (SCBCN) is a network of seven markets dedicated to provide high quality and safe care to patients with complex blood cancers. Continuous quality management (QM) and improving patient safety are critical components to the mission of SCBCN. Methods: Four SCBCN disease-specific working groups have developed evidence-based pathways for complex blood cancers. However, there are currently no SCBCN clinical quality of care metrics to monitor value-based care. To address this unmet need, the SCBCN leadership endorsed a team-based approach to measure QM for complex blood cancers, using basic clinical performance metrics proposed by the American Society of Hematology, the American Medical Association-convened Physician Consortium for Performance Improvement, the U.S. Department of Health and Human Services Agency for Healthcare Research and Quality National Quality Measures Clearinghouse, and Centers for Medicare & Medicaid Services. Results: Between 2012 and September 2015, 1221 new adult cases of Acute Myeloid Leukemia (AML) and 253 new adult cases of Myelodysplastic Syndrome (MDS), respectively, were reported within the SCBCN. Based on the volume of cases and to measure QM in AML and MDS, quality indicators were selected based on meaningfulness to program goals and feasibility of data capture, leading to development of quality metrics dashboard for AML and MDS in SCBCN. Also, keeping in mind the changing paradigm of personalized care using new and emerging therapies in AML and MDS, exploratory quality metrics are also proposed to evaluate access to new trials as QM of AML and MDS in SCBCN. Conclusions: SCBCN is a wide network of community hospitals with expertise in managing complex blood cancers. As proof of concept study, the AML and MDS dashboard was developed and chosen as a model for continuous QM for complex blood cancers. This dashboard will initially be tested to evaluate QM at two SCBCN sites to facilitate the overarching programmatic goal of continuous QM for all AML/MDS and other blood cancers presenting within the SCBCN.

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Evaluation of a Diabetes Management System Based on Practice Guidelines, Integrated Care, and Continuous Quality Management in a Federal State of Germany: A population-based approach to health care research

Diabetes Care ◽

10.2337/dc07-0858 ◽

2008 ◽

Vol 31 (5) ◽

pp. 863-868 ◽

Cited By ~ 67

Author(s):

U. Rothe ◽

G. Muller ◽

P. E.H. Schwarz ◽

M. Seifert ◽

H. Kunath ◽

...

Keyword(s):

Health Care ◽

Quality Management ◽

Integrated Care ◽

Practice Guidelines ◽

Diabetes Management ◽

Health Care Research ◽

Population Based ◽

Federal State ◽

Continuous Quality Management ◽

Continuous Quality

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Quality management systems in Aboriginal Community Controlled Health Services: a review of the literature

BMJ Open Quality ◽

10.1136/bmjoq-2020-001091 ◽

2021 ◽

Vol 10 (3) ◽

pp. e001091

Author(s):

Jenifer Olive Darr ◽

Richard C Franklin ◽

Kristin Emma McBain-Rigg ◽

Sarah Larkins ◽

Yvette Roe ◽

...

Keyword(s):

Quality Improvement ◽

Quality Management ◽

Health Service ◽

First Nations ◽

Quality Management System ◽

Grey Literature ◽

Models Of Care ◽

Clinical Governance ◽

Aboriginal Community ◽

Continuous Quality

BackgroundA national accreditation policy for the Australian primary healthcare (PHC) system was initiated in 2008. While certification standards are mandatory, little is known about their effects on the efficiency and sustainability of organisations, particularly in the Aboriginal Community Controlled Health Service (ACCHS) sector.AimThe literature review aims to answer the following: to what extent does the implementation of the International Organisation for Standardization 9001:2008 quality management system (QMS) facilitate efficiency and sustainability in the ACCHS sector?MethodsThematic analysis of peer-reviewed and grey literature was undertaken from Australia and New Zealand PHC sector with a focus on First Nations people. The databases searched included Medline, Scopus and three Informit sites (AHB-ATSIS, AEI-ATSIS and AGIS-ATSIS). The initial search strategy included quality improvement, continuous quality improvement, efficiency and sustainability.ResultsSixteen included studies were assessed for quality using the McMaster criteria. The studies were ranked against the criteria of credibility, transferability, dependability and confirmability. Three central themes emerged: accreditation (n=4), quality improvement (n=9) and systems strengthening (n=3). The accreditation theme included effects on health service expenditure and clinical outcomes, consistency and validity of accreditation standards and linkages to clinical governance frameworks. The quality improvement theme included audit effectiveness and value for specific population health. The theme of systems strengthening included prerequisite systems and embedded clinical governance measures for innovative models of care.ConclusionThe ACCHS sector warrants reliable evidence to understand the value of QMSs and enhancement tools, particularly given ACCHS (client-centric) services and their specialist status. Limited evidence exists for the value of standards on health system sustainability and efficiency in Australia. Despite a mandatory second certification standard, no studies reported on sustainability and efficiency of a QMS in PHC.

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Big data quality framework: a holistic approach to continuous quality management

Journal Of Big Data ◽

10.1186/s40537-021-00468-0 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Ikbal Taleb ◽

Mohamed Adel Serhani ◽

Chafik Bouhaddioui ◽

Rachida Dssouli

Keyword(s):

Big Data ◽

Quality Management ◽

Data Quality ◽

Value Added ◽

Holistic Approach ◽

Research Area ◽

Heterogeneous Data ◽

Data Generation ◽

Continuous Quality ◽

Quality Profile

AbstractBig Data is an essential research area for governments, institutions, and private agencies to support their analytics decisions. Big Data refers to all about data, how it is collected, processed, and analyzed to generate value-added data-driven insights and decisions. Degradation in Data Quality may result in unpredictable consequences. In this case, confidence and worthiness in the data and its source are lost. In the Big Data context, data characteristics, such as volume, multi-heterogeneous data sources, and fast data generation, increase the risk of quality degradation and require efficient mechanisms to check data worthiness. However, ensuring Big Data Quality (BDQ) is a very costly and time-consuming process, since excessive computing resources are required. Maintaining Quality through the Big Data lifecycle requires quality profiling and verification before its processing decision. A BDQ Management Framework for enhancing the pre-processing activities while strengthening data control is proposed. The proposed framework uses a new concept called Big Data Quality Profile. This concept captures quality outline, requirements, attributes, dimensions, scores, and rules. Using Big Data profiling and sampling components of the framework, a faster and efficient data quality estimation is initiated before and after an intermediate pre-processing phase. The exploratory profiling component of the framework plays an initial role in quality profiling; it uses a set of predefined quality metrics to evaluate important data quality dimensions. It generates quality rules by applying various pre-processing activities and their related functions. These rules mainly aim at the Data Quality Profile and result in quality scores for the selected quality attributes. The framework implementation and dataflow management across various quality management processes have been discussed, further some ongoing work on framework evaluation and deployment to support quality evaluation decisions conclude the paper.

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Continuous Quality Improvement Applied to Medical Care: Experiences at LDS Hospital

Medical Decision Making ◽

10.1177/0272989x9101104s11 ◽

1991 ◽

Vol 11 (4_suppl) ◽

pp. S60-S65 ◽

Cited By ~ 10

Author(s):

Gil Kuperman ◽

Brent James ◽

Julie Jacobsen ◽

Reed M. Gardner

Keyword(s):

Quality Improvement ◽

Quality Management ◽

Medical Care ◽

Continuous Quality Improvement ◽

Analytic Approach ◽

Statistical Tools ◽

Continuous Quality ◽

Key Steps ◽

Expected Outcomes

At LDS Hospital the authors are implementing continuous quality improvement (CQI), a systems-analytic approach to quality management in industry, as an approach to quality management in medical domains. Their approach consists of 1) choosing a process to be improved, 2) assembling a team of expert clinicians that understands the process and the outcomes, 3) determining key steps in the process and expected outcomes, 4) collecting data that measure the key process steps and outcomes, and 5) feeding back the data to the practitioners. CQI theory states that the practitioners will use the information and their own best intentions to improve the manner in which they provide care. The authors have developed statistical tools that display the data and distinguish between random and assignable variation.

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Improving healthcare quality in the United States healthcare system: A scientific management approach

Journal of Hospital Administration ◽

10.5430/jha.v9n5p19 ◽

2020 ◽

Vol 9 (5) ◽

pp. 19

Author(s):

Soumya Upadhyay ◽

William Opoku-Agyeman

Keyword(s):

Quality Improvement ◽

Quality Management ◽

Healthcare System ◽

Continuous Quality Improvement ◽

Six Sigma ◽

Healthcare Quality ◽

The United States ◽

Management Theory ◽

Scientific Management ◽

Continuous Quality

The US healthcare system has been facing pressures from stakeholders to reduce costs and improve quality. The purpose of this paper is to develop a conceptual model to illustrate the approaches used in healthcare quality management (Continuous Quality Improvement/Total Quality Management, Lean, and Six Sigma) weaved into the underlying framework of scientific management theory. This paper employs scientific management theory to explain the healthcare quality tenets that influence the quality of care in our healthcare organizations. The father of scientific management, Frederick Taylor, and other key contributors collectively created scientific management principles, which are widely used for quality improvement purposes both in the engineering and the healthcare field. Healthcare quality is also discussed with examples of the application of scientific management principles. Shared themes between scientific management principles and healthcare quality tenets, as given in CQI/TQM, Six Sigma-Lean, and Donabedian Model, were developed. To understand the three pillars of quality (structure, process, outcome) in relation to the underpinnings of scientific management principles, we incorporated insights of scientific management theory into Donabedian’s healthcare quality model. It is recommended that selection of personnel play a more significant role among human resources practices in organizations; strategy formulation must include a careful assessment of organizations’ strengths and weaknesses with regard to continuous quality improvement, with organizations striving to achieve standardization to attain efficiency and reduce costs.

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