Global Health IT Strategies Minitrack

Permanent URI for this collection

https://hdl.handle.net/10125/42476

The global advancements in information and communication technologies has provided opportunities to address issues important to global health, such as coordinating responses to emerging diseases, and addressing health issues that have an international interest throughout diverse regions of the world. These technologies assist in disease surveillance and response, global health education, applying traditional telemedicine applications, as well as other applications for all healthcare actors. These efforts are already impacting the rapid growth and further development of global healthcare solutions and approaches arising from the active collaboration among cross-disciplinary researchers, multi-national agencies and international clinical practitioners.

This minitrack covers broad issues related to Global Health IT strategies, such as applying technology to address health issues that have a global impact. Topics include disease surveillance and response, global health education, community health, coordination of healthcare efforts internationally, new forms and modalities of care delivery aided with Health IT globally such as use of innovative low- cost, mobile and sensor-enabled and other emerging health technological applications. These solutions will provide a multinational perspective on the benefits of mobile health and other emerging information technologies and describes different examples and applications implemented.

Minitrack Co-Chairs:

Joseph Tan (Primary Contact)
McMaster University, Canada
Email: tanjosep@mcmaster.ca

Ofir Turel
California State University Fullerton
Email: oturel@fullerton.edu

Michael S. Dohan
Lakehead University, Canada
Email: msdohan@lakeheadu.ca

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Now showing 1 - 7 of 7

Drone Delivery Models for Healthcare
(2017-01-04) Scott, Judy; Scott, Carlton
Just as the mobile phone allowed developing countries to leapfrog technology in personal communication, the delivery drone has the potential to have the same effect on traditional transportation infrastructure. Inaccessible roads no longer will prevent delivery of blood, medications or other healthcare items. This paper reviews the current status of innovative drone delivery with a particular emphasis on healthcare. The leading companies in this field and their different strategies are studied. Further we review the latest decision models that facilitate management decision making for operating a drone fleet. Our contribution in this paper of two new models associated with the design of a drone healthcare delivery network will facilitate more timely, efficient and economical drone healthcare delivery to potentially save lives.
Developing Effective Crowdsourcing Systems for Medical Diagnosis: Challenges and Recommendations
(2017-01-04) Sen, Kabir; Ghosh, Kaushik
Diverse medical traditions follow different ‘grammar’ making encapsulation of varied body of knowledge challenging. However, the advances in information technology in the 21st century provide an opportunity to aggregate knowledge from varied cultures and medical traditions to tackle difficult health issues for which no cure has been developed. In addition to accumulating knowledge from wide-ranging sources, an ideal crowdsourcing system (CS) can benefit from the use of appropriate algorithms to choose the best solution. This conceptual paper examines existing classification of crowdsourcing and the various challenges involved with the capture and transmission of medical knowledge. It proposes the steps involved in developing an effective CS for dealing with medical problems. The ideal CS should involve the crowd and medical experts from all across the world, who together with the help of algorithms and other technology features in the CS could provide a useful solution for hard to solve health problems.
Data Visualization on Global Trends on Cancer Incidence An Application of IBM Watson Analytics
(2017-01-04) Tsoi, Kelvin Kf; Chan, Felix Ch; Hirai, Hoyee W; Leung, Gary Ks; Kuo, Yong-Hong; Tai, Samson; Meng, Helen Ml
Visual analytics is widely used to explore data patterns and trends. This work leverages cancer data collected by World Health Organization (WHO) across over a hundred of cancer registries worldwide. In this study, we present a visual analytics platform, IBM Watson Analytics, to explore the patterns of global cancer incidence. We included 26 cancers from different geographic regions. An interactive interface was applied to plot a choropleth map to show global cancer distribution, and line charts to demonstrate historical cancer trends over 29 years. Subgroup analyses were conducted for different age groups. With real-time interactive features, we can easily explore the data with a selection of any cancer type, gender, age group, or geographical region. This platform is running on the cloud, so it can handle data in huge volumes, and is assessable by any computer connected to the Internet.
Community Health Workers as Innovators: Methods and Results from a Tele-Education Pilot for Community Health Workers in Detroit, Michigan
(2017-01-04) Prentiss, Tyler; Tamler, Ilyssa; Plum, Alex; Parke, Dana; Zervos, John; Tanniru, Mohan; Sears, Michele Harrison; White, Monica; Wisdom, Kimberlydawn; Kaljee, Linda
Community health workers (CHWs) have played an important role in improving the health of underserved populations in resource-limited settings. CHWs are trusted in communities that they serve, and are often able to see solutions to community problems that outside persons cannot. Solutions need to be low cost and easily accessible, and address the knowledge gaps among CHWs through appropriate training. Utilizing information technology solutions can be key to increasing access to knowledge for these community agents. This paper outlines the methods and results from a pilot study of the Community Health Innovator Program performed in Detroit, Michigan with a group of community health workers in basic grant-writing training, utilizing an information technology platform. The results will be discussed as a larger response to growing issues in global health and how such platforms can be used and adapted in response to ever-evolving global health challenges.
Analysis of ZIKA Virus Tweets: Could Hadoop Platform Help in Global Health Management?
(2017-01-04) Juric, Radmila; Kim, Inhwa; Panneerselvam, Hemalatha; Tesanovic, Igor
This paper investigates possibilities of enhancing everyday decision making in global health management, by looking at the power of twitter data and the use of big data platforms in order to collect and interpret excessive amounts of information generated in a short period of time. We use the scenario of the ZIKA virus because it has triggered a massive response through tweets and retweets. Our goal is to find out a) if we can make sense of twitter data in a global health scare and b) if information available on Twitter could help in the management and containment of the spread of the virus. The results of manual content analysis of selected tweets has been juxtaposed with the results of the manipulation of the same tweets through the Hadoop platform. We wanted to know which approach should be used for addressing public concerns about the ZIKA virus and answer a) and b) at the same time. Both approaches have their advantages and drawbacks. Therefore this paper should be used as an overview of options available for public health organizations, when they need to manipulate social media data in situations where we need to manage health on a global scale
A Hybrid Mining Approach to Facilitate Health Insurance Decision: Case Study of Non-Traditional Data Mining Applications in Taiwan NHI Databases
(2017-01-04) Tan, Joseph; Turel, Ofir; Dohan, Michael
This study examines time-sensitive applications of data mining methods to facilitate claims review processing and provide policy information for insurance decision-making vis-à-vis the Taiwan National Health Insurance databases. In order to obtain the best payment management, a hybrid mining approach, which has been grounded on the extant knowledge of data mining projects and health insurance domain knowledge, is proposed. Through the integration of data warehousing, online analytical processing, data mining techniques and traditional data analysis in the healthcare field, an easy-to-use decision support platform, which will facilitate the health insurance decision-making process, is built. Drawing from lessons learned in case study, results showed that not only is hybrid mining approach a reliable, powerful, and user-friendly platform for diversified payment decision support, but that it also has great relevance for the practice and acceptance of evidence-based medicine. Researchers should develop hybrid mining approach combined with their own application systems in the future.
Introduction to Global Health IT Strategies Minitrack
(2017-01-04) Tan, Joseph; Wang, Fuchung

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