Continuous quality management for complex blood cancers in Sarah Cannon Blood Cancer Network.

2017 ◽  
Vol 35 (8_suppl) ◽  
pp. 59-59
Author(s):  
Suman Kambhampati ◽  
Therese Dodd ◽  
Cheryl Sheridan ◽  
Charles F. LeMaistre
Keyword(s):  
Quality Management ◽  
Performance Metrics ◽  
Unmet Need ◽  
Quality Metrics ◽  
Healthcare Research ◽  
Blood Cancer ◽  
Continuous Quality Management ◽  
Continuous Quality ◽  
National Quality ◽  
Cancer Network

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.

scholarly journals Quality Assessment Across A National Cancer Network

2013 ◽  
Vol 9 (3) ◽  
pp. 165-168 ◽  
Author(s):  
William J. Simeone ◽  
John Bingham ◽  
Thomas W. Burke ◽  
Peter W.T. Pisters
Keyword(s):  
Quality Management ◽  
Quality Assessment ◽  
Quality Care ◽  
Quality Metrics ◽  
High Quality ◽  
National Network ◽  
High Quality Care ◽  
Cancer Network

Quality management with the ability to benchmark quality metrics remains a cornerstone of the authors' overarching strategy to maintain consistent high-quality care throughout our national network.

CONTINUOUS QUALITY MANAGEMENT

1998 ◽  
Vol 26 (Supplement) ◽  
pp. 46A
Author(s):  
Oriando Kirton ◽  
Soo Hee Kim ◽  
Carol Williams ◽  
Jimmy Windsor ◽  
David Shatz ◽  
...  
Keyword(s):  
Quality Management ◽  
Continuous Quality Management ◽  
Continuous Quality

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

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.

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

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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