Day 2 :
Keynote: Intelligent Assistance: Harnessing “Big Data” Technologies to Assist in Providing Timely and Safe Patient Care
Time : 10:00-10:40
Charles is the Chief Innovation Officer for Clearsense, a healthcare analytics organization specializing in bringing “Big Data” technologies to healthcare. Prior to Clearsense Charles was the Enterprise Analytics Architect for Stony Brook Medicine. In his role he is developed the analytics infrastructure to serve the clinical, operational, quality and research needs of the organization. He was a founding member of the team that developed the Health and Human Services award winning application "Now Trending" to assist in the early detection of disease outbreaks utilizing social media feeds. In 2015 Charles served as co-editor for “Mastering Healthcare Informatics” published by Sigma Theta Tau. Charles holds a MS in Technology Management from Stevens Institute of Technology and is the President of the American Nursing Informatics Association.
In 2010 the Clinical Informatics Team at the University of California, Irvine set out introduce technologies deployed by Twitter, Facebook, LinkedIn and Yahoo into healthcare. The ability to utilize and process data by these organizations in a very real time nature was compelling. Even more compelling was the similarities in data types shared by these organizations as well as healthcare such as structured, unstructured, images and video. This presentation will focus on the work done over the past six years regarding the infrastructure required to ingest healthcare and healthcare related data into a “Big Data” ecosystem. Additional areas of focus will be on the clinical applications built on the ecosystem utilizing streaming data for monitoring patients in high acuity areas in real time by virtue of streaming data and streaming analytics. Real time quality assessment and monitoring will be discussed as healthcare is moving from retrospective quality reporting to a real time assessment of patients meeting quality measures. Data not traditionally found within the healthcare data environment will also be explored and the use cases for acquiring high value data such as social determinates of health, social media geographic information systems and public data will be covered.
University of Graz, Austria
Time : 10:40-11:20
Werner Leodolter is CIO of KAGes . Previously he served as CIO in steel industry. 2008-2013 he led the Styrian hospital GmbH ( KAGes ) – a 17000 employees hospital group in Austria - as CEO through a period of organizational realignment . He is also member of the telehealth services commission of the Federal Ministry of Health of Austria. He is university professor of Applied Management in Health Care at the University of Graz (KFU). He is author of the book (in German) "The subconscious mind of organizations: New technologies - Rethinking organizations", published at Springer in 2015.
New technologies are changing the individual´s and the organization´s perception of their environment, they change learning processes, the management of knowledge, etc. - they also change healthcare itself – the digital transformation is on its way. This disruptive innovation requires a new, complementary perspective. The subconscious mind of organizations as a powerful metaphor describes the comprehensive view of an healthcare organization and its internal and external interconnectedness. It helps to find new ways to design and build organisations. The new technologies are becoming increasingly part of the ICT infrastructure which itself is a part of the subconscious mind of organizations. Based upon that the subconscious mind of organizations is composed and formed from different self-similar perspectives - Board, CEO, CFO, Chief Physician, technical expert, etc.To form the subconscious of organizations means to prepare and focus the organizations in their methods, tools and processes and redirect them to exploit opportunities of change while controlling the risks. Following the proposed guidelines organizations should be able to deal with uncertainty, complexity and upheaval as good as possible. The design of the ICT infrastructure in clever platforms enables both collaboration and innovation. It is important to develop "intelligent organizations", in which certain activities perform in the "subconscious mind of the organization”. This should be deliberately designed and regularly evaluated, so that future healthcare organizations will be a kind of “hybrid intelligence” - excellent, successful and sustainable organizations with a significant share of artificial intelligence but the clear primacy of the human and organizational component.
Track 8:Health Informatics Engineering
Location: Crown Plaza New Orleans airport
Adrian Zai, MD PhD MPH, is the clinical director of population informatics at the Massachusetts General Hospital’s Laboratory of Computer Science, a faculty member of Harvard Medical School, and the Chief Medical Informatics Technology at SRG-Technology. Dr. Zai has been in healthcare for over 20 years, with the last 12 years focused on population health management. He is the lead designer and innovator of Top Care, an information technology platform designed uniquely for population health management with core components that support team-based care and patient-centered management.
In this presentation, Dr. Zai will give an overview of the state of population health management in the U.S. as it relates to technology. He will touch on the most important peer-reviewed publications in this domain and share lessons learned. Furthermore, he will talk about areas of challenges and unprecedented opportunities for information technology to improve outcomes and reduce costs of health care in the United States. He will present several use cases where some of the clearest opportunities exist to reduce costs through the use of big data, care coordination, or creative patient engagement solutions. He will explain what are the critical technology components required for effective population health management and share critical mistakes to avoid
Tulane University School of Public Health, USA
Title: Introducing a Text – Message based Early Warning System for Contraceptive Stock Outs in Kinshasa, D.R. Congo
Time : 12:05-12:35
Dr. Julie Hernandez received her PhD from the University of Paris X Nanterre in 2010. She currently is a Research Assistant Professor with the Tulane School of Public Health in New Orleans, LA. Dr. Hernandez is a Geographic Information System / Digital Data Collection specialist with 10+ years of experience in developing user – friendly, participant mapping and surveys initiatives and early warning systems in resource – constrained environments. She serves as Co-Investigator on several DFID, Gates Foundation and Packard Foundation funded projects in DR Congo to improve access to Family Planning services.
In Kinshasa, D.R. Congo, unmet need for modern contraception is extremely high (31.3% in 2013), while access to primary healthcare facilities remains difficult. Community – based contraceptives distribution is a possible solution to increase FP use. However, evaluations conducted with Community – Based Distributors (CBD) revealed that they were stocked out of contraceptives about 70% of the time. Quarterly resupply circuits were insufficient to meet the demand. In addition, routine healthcare services reporting in Kinshasa is mired with completeness, accuracy and timeliness issues. In order to strengthen contraceptive logistics, Tulane developed a text – message based reporting system to track contraceptive distribution at the community level. This system (“sms4bPF”) is linked to a web base capable treating routine data and alerting suppliers of imminent stock outs. We evaluated the technical and systemic feasibility of this platform based on feedback from 150 DBC users and quality analysis of the pilot database. While this text-message based reporting system shows promising results in terms of strengthening ADBCs involvement in community-based activities and FP service reporting, the pilot phase revealed in particular that, while some of the issues encountered with this reporting system stem from its technical design, most barriers to its effectiveness are rooted in the same communication and logistics issues plaguing the contraceptive supply chain in Kinshasa. With electronic data collection and mHealth increasing popularity for strengthening global health systems, this presentation will endeavor to look beyond the “techno fix” approach and highlight systemic hurdles to scaling up and sustaining these initiatives in challenging programmatic environments.
Ajman University of Science and Technology, UAE
Time : 12:35-13:05
Syed Imtiaz Ali Rizvi is a senior lecture at Department of Information Systems, College of Information Technology, Ajman University of Science and Technology, Fujairah Campus, United Arab Emirates. He has bachelors degree in Electrical Engineering and Masters in Computer Science. He has more than 25 years of teaching experience and has supervised around 50 projects in a diversified fied of science and technolgy. He is extensify involved in research with Dr. Amer Al-Nasiri; who is Deputy Dean of the college and is a co-author of this paper. He has different published articles in the field of Image Processing and Data mining.
Healthcare information are traditionally collected through surveys, which are although a direct source but much of the healthcare information is hidden. There should be an indirect way to collect the healthcare information about individuals and communities. Such information provide a real-time insight into the health situation of individuals or communities. Currently Data warehousing is a common source in Businesses to get information to plan and to know the current and future trends in business. The main source of business data are individuals and communities; so why not this huge reservoir of information is used for healthcare. In this article we describe two analytical techniques based on support vector machines (SVMs) for data analysis and support vector regression (SVR) to extract and classify healthcare information from a typical Business data warehouse about individuals and communities. Working out on data collection of a local chain of retail market in UAE and from the purchase habits of consumers get their healthcare information. Different kernels are be used in Support of Vector Machines models. These include linear, polynomial, radial basis function (RBF) and sigmoid as part of mapping system and analysis of healthcare information. The results show that using SVM method as analytical and classification tool for healthcare data is promising and comparable to other techniques like ANN. Finally this technique can be used to correlate the extracted information with the existing standards of International health organizations at a national and global level and suggest the change in purchase habits of individuals and communities in context of healthcare.
University of Alberta, Canada
Title: Barriers and Facilitators to Electronic Medical Record (EMR) Use in Urban Slums - Kibera Field Study
Time : 14:00-14:30
Badeia obtained a bilingual Bachelor of Commerce degree, is a Certified Human Resource Professional (CHRP) and completed a Master of Science degree focused on health informatics from the University of Alberta. Badeia developed a passion for health technology and global development when presenting at the 2009 Education without Borders conference in Dubai. She began an exploration of innovative uses of tele-health and mobile devices in rural Kenya, then progressed to a range of work in not-for-profit health informatics and global health initiatives. Badeia’s research interests include applications of mobile health technology and impacts of health information systems in resource-limited settings. Badeia is currently managing an EMR initiative in Nairobi, Kenya and works with global partners providing support and expertise to other EMR deployments.
Nearly one billion people live in slums throughout the world, where they suffer from the health problems of vulnerable populations. Recognizing the potential of electronic medical records (EMRs) to improve communication, sharing and tracking of health care; this study explored facilitators and barriers to effective EMR use in an urban slum in Kibera, Nairobi. Descriptive qualitative methods were used to characterize perceptions of primary care staff about effects of EMR implementations in two different Kibera clinics. Ten staff participated in in-depth interviews guided by open-ended, semi-structured questions. Content analysis methods were used to explore transcribed data. Three major themes – infrastructure, software, social and organizational issues – emerged, with sustainability crossing all as an overriding concern for participants. Although many infrastructure (e.g., reliable power, networks and interoperability) and software (e.g., health data, confidentiality and deployment) challenges were described, social and organizational factors (e.g., identity management and EMR use incentives) appeared to be the most potent determinants of positive or negative EMR impacts. These findings are consistent with what others have reported, especially the importance of practical (infrastructure and software) barriers to EMR use in both limited resource settings and developed countries. Other findings appear to be uniquely impactful in slum settings, including the importance of identity management, meaningful incentives and sustainability programs.