Policy Studies Centre presents Health data reporting systems for this century-FR
The Policy Studies Centre is presenting the lecture, Health data reporting systems for this century by Drs. Daniel Dutton and Dean Yergens, University of Calgary.
Abstract: Access to timely, relevant and up to date information for clinicians and health system decision makers has long been held out as critical for improving health care system productivity, improving the value for money of services delivered, improving clinical decision making and ultimately patient outcomes. A large volume of data is routinely collected in health care systems and through surveys, but traditional labour intensive approaches for analyzing, understanding, and disseminating the information produced continue to be a limiting barrier.
These labour intensive approaches to analysis result in higher costs for reporting on the increasing volume of data, exacerbate the skills shortages required to meaningfully interpret the data, and impact the time required for information to be delivered to inform decision making. Additionally, through the use of traditional manual methods most of this data is never analyzed and the information therein is treated like it does not exist.
Our presentation demonstrates how an automation approach to health information production through software applications improves the completeness and timeliness of analyzing health datasets. First, we sought to understand how datasets were being analyzed in the health research literature. This involved conducting software-enhanced literature reviews to understand what epidemiological concepts, statistical techniques, and other approaches were being applied Next, applying the resultant knowledge, an automated approach was developed that could perform the same level of analysis found in the peer-reviewed academic literature.
This presentation will focus on one case study, examining the Canadian Community Health Survey, a national cross-sectional survey conducted by Statistics Canada since 2001. We will demonstrate the benefits of the automated literature and data analysis approach. We will show how this approach brings traditionally trained analysts to a decision point faster than the traditional methods and how this approach results in cost-savings for organizations trying to generate knowledge from data.
Daniel Dutton Bio:
Dr. Daniel Dutton is a post-doctoral scholar at the University of Calgary’s School of Public Policy. He has degrees in public health and economics and his main research interests involve using large datasets to solve or inform health and social policy-related problems. He is primarily interested in issues of population-level exposures and their impact on poverty and health; he also has an interest in methodological practice around answering applied questions using data.
Dean Yergens Bio:
Dr. Dean Yergens is a computer scientist and health services researcher specializing in the use of data and information for improving healthcare research and operations. He has worked in a variety of research environments including critical care, medical informatics, and global health having worked in the Philippines, Malawi, Zambia, Kenya, Samoa, and as a consultant with the World Health Organization. His research interests include automated statistical analysis, machine learning, multi-agent simulations, and information management for improving scoping and systematic literature reviews. He is the founder of Synthesis Research Inc. and Healthcare Simulations Inc., and is an Adjunct Assistant Professor, Department of Critical Care Medicine at the University of Calgary.
Building: Tilley Hall
Room Number: 307
1 506 453 4828