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  • Book
    John M. Morton, Stacy Brethauer, Eric J. DeMaria, Scott Kahan, Matthew M. Hutter, editors.
    Summary: This book reviews quality definition, measurement, improvement, value, and accountability for obesity management. The interplay between quality, cost, access and satisfaction is fully depicted with a goal toward not only fulfilling current standards but also anticipating future needs. A thorough inventory of current best practices in all aspects of obesity care is cataloged with a gap analysis also employed for potential areas of improvement to be road mapped. All chapters are written by experts in their fields and include the most up-to-date scientific and clinical information, take home messages, and questions towards following the requirements of quality certification in obesity management. Quality in Obesity Treatment provides a comprehensive, contemporary review of this field and serves as a valuable resource for Bariatric Surgeons, Primary Care Physicians, Policy Makers, Insurance Administrators, Bariatricians, and any medical specialty interested in obesity quality management with likely candidates coming from GI, endocrinology, cardiology, sleep medicine and orthopedics.

    Intro; Preface; Contents; Contributors; Part I: National Definitions, Goals, Initiatives;
    1: Defining and Measuring Quality; Why Measure Quality?; What Is Quality?; How Do You Measure Quality?; Measuring Quality in Metabolic and Bariatric Surgery; Surgeons Should Lead in Measuring Quality; References;
    2: Building a Metabolic and Bariatric Surgery Data Registry: Quality Improvement Through Measurement; Introduction; History and Timeline of Quality Improvement; The History of Surgical Innovation in Metabolic and Bariatric Surgery; The Journey Toward Bariatric Surgery Accreditation Limitations of the Original Metabolic and Bariatric Surgery Accreditation ProgramsThe New Era in Metabolic and Bariatric Surgery Quality Improvement: The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP); Conclusion; References;
    3: Lessons Learned from ACS NSQIP; Origins and Early Development; Logistics and Feedback Mechanisms; Demonstration of Local Quality Improvement; Powerful Quality Research Platform; Future Directions: Increasing Breadth and Depth of Data; Lessons for Growing Quality Improvement Programs; References
    4: The Institute of Medicine and the Pursuit of QualityIntroduction; To Err Is Human; Crossing the Quality Chasm; The Ongoing Pursuit of Quality; References;
    5: Private Payer Initiatives for Quality Improvement; Introduction; Health-Care Quality in the United States; Top-Down Approaches to Quality Improvement; Collaborative Quality Improvement; Elements of Collaborative Quality Improvement; Benefits of Collaborative Quality Improvement; Collaborative Quality Improvement in Surgery; Northern New England Cardiovascular Disease Study Group; Surgical Care and Outcomes Assessment Program Payer-Funded Collaborative Quality ImprovementPay for Participation; Michigan Bariatric Surgery Collaborative; Opportunities and Challenges; Conclusion; References;
    6: The Value Proposition and ProvenCare®; Geisinger Health System and Value Reengineering; The Development of ProvenCare® Bariatrics; Analysis of the Impact of ProvenCare® Bariatrics; Reliability; Length of Stay (LOS); Postoperative Complications; Additional Outcomes; Efficacy of the ProvenCare® Bariatric Program; Financial Analysis; ProvenCare® Bariatric and the Value Proposition; Reliability; Quality; Costs "Unjustified" VariabilityConclusions; References;
    7: Patient Satisfaction, Patient-Reported Outcomes, and Quality; Introduction; PROs and PROMs: An Overview; Patient Experience; HCAHPS; CG-CAHPS; S-CAHPS; Recovery; Quality of Life; Functional Status; PROMs in the MBSAQIP: The LOBSTER PROMs Project; Conclusion; References;
    8: Understanding Risk and Reliability Adjustment in Metabolic and Bariatric Surgical Quality Profiling; Introduction; Measuring Surgical Quality; Risk Adjustment; Risk Adjustment with Logistic Regression Models; Estimating the Effect of a Predictor Determining the Significance of a Predictor
    Digital Access Springer 2019