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Statistical Process Control (SPC) for Quality Improvement In-Person

SPC is an industry-standard methodology for measuring and controlling quality during the manufacturing process. It has increasingly been shown to be useful in health care quality improvement projects. It’s a set of methods based on the theory of variation that can be used to make sense of any process or outcome measured over time, usually with the intention of detecting improvement or maintaining a high level of performance.

 

Presented by:  Simon Jones, PhD, MSc

Simon Jones, PhD, MScDr. Jones is a Research Professor in the Department of Population Health, Division of Healthcare Delivery Science. He brings extensive experience in leveraging data analysis and health informatics in the study of health services research to his role at NYU.

Dr. Jones attended London’s Southbank University, where he received an MSc degree in Software Engineering and Mathematics. He then earned a PhD in Mathematics from Kingston upon Thames’ Kingston University in 2005. From 2002 to 2005, Dr. Jones was the Head of Health Informatics and Operational Research at Bromley Hospitals National Health Service (NHS) Trust. He became a Research Fellow at London’s Kings College in 2007 and a Research Professor at the University of Surrey in 2011. In 2012 Dr. Jones was awarded Chair in Healthcare Management and Policy, University of Surrey. His most recent post was as a full Professor of Epidemiology and Head of the Integrated Care Division at the School of Health Science at the University of Surrey in the United Kingdom and as a Visiting Senior Fellow in Health Services Research at the London School of Economics.

At NYU Langone Medical Center (NYULMC), Dr. Jones works with our researchers to support the development and implementation of the Division of Healthcare Delivery Science grants and the Center for Healthcare Innovations and Delivery Science NYULMC-based projects.

Date:
Wednesday, February 13, 2019
Time:
10:00am - 12:00pm
Time Zone:
Eastern Time - US & Canada (change)
Location:
Lapidus Library Classroom G101
Categories:
  Data Day to Day  
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