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Annals Article Recognized for Impact on Field of Biosurveillance

The PopHR team received first prize from the International Society for Disease Surveillance.

Published March 08, 2018

Annals Article Recognized for Impact on Field of Biosurveillance

While doctors treat their patient’s symptoms individually, stakeholders in the field of public health must take into account the needs of an entire community or demographic. Whether grappling with a flu outbreak or monitoring a community’s obesity rate, the detailed electronic records that exist for an individual are often inadequate or nonexistent for large populations.

The lack of adequate integrated systems for monitoring the health status of large populations is a concern of Academy Member Arash Shaban-Nejad, now an assistant professor of the University of Tennessee Health Science Center – Oak Ridge National Laboratory, Center for Biomedical Informatics. He entered his field to help people live longer and happier lives, describing biomedical informatics with its employment of cutting-edge technologies to design and implement new algorithms, methods, and tools in the detection, prevention, and treatment of diseases – as one of the best ways to impact the most people.

Dr. Shaban-Nejad was part of the PopHR team at the Surveillance Lab, led by Dr. David L. Buckeridge, at McGill University, that designed the Population Health Record (PopHR) a big data platform to help public health stakeholders implement community and population health surveillance and evidence-based decision making. The platform first appeared in a  January 2017 special issue of Annals of the New York Academy of Sciences, and subsequently received first prize in the 2018 Awards for Outstanding Research Articles in Biosurveillance – in the Impact on Field Category from the International Society for Disease Surveillance (ISDS).

The ISDS is a nonprofit dedicated to improving population health by advancing the science and practice of disease surveillance. Dr. Shaban-Nejad and the PopHR team were honored to be recognized by other scientists in their field. “We believe winning the award can give the PopHR team the momentum to expand the scope and features of the software platform, making it available to a wider group of people, communities, and organizations, and ultimately help to save more lives.”

PopHR is analogous to an electronic medical record, but one that integrates data for a defined population instead of an individual. “Like an EMR, PopHR is a platform for decision support, enabling intelligent analysis and visualization of data to create coherent portraits of population health and health system performance from large amounts of information,” explained Dr. Shaban-Nejad. “For many years public health organizations, scientists, and policymakers lacked a coherent platform for population health information. PopHR aims to fill this gap by providing a platform that uses existing knowledge about population health to assist public health practitioners and policy makers in monitoring population health and health system performance in a conceptually coherent manner.”

The difficulty with developing any population health record is how to effectively collect, integrate, use, and share population health data. Dr. Shaban-Nejad described four challenges: heterogeneous data sources that present challenges in collection, integration, and processing; data with poor temporal and geographical resolution; the unknown validity of some commonly used health indicators; and data that isn’t representative of the greater population. These challenges are compounded by barriers related to the design and operation of existing web portals for population health information.

“The main advantages of the PopHR over other existing systems include: maintaining up-to-date indicators, representing different indicators with respect to a common conceptual model, ensuring reproducibility of results, and explicitly linking information about a defined population to evidence,” he explained. “The use of advanced knowledge representation and artificial intelligence tools and techniques, enables the system to make population health indicators available in a format and timeliness that supports decision making by automating the retrieval and integration of massive, heterogeneous, and dynamic data from multiple sources (e.g., administrative records, clinical data, and survey results) in near real time with high geographical resolution.”

The creation of PopHR has depended on advances in the field of artificial intelligence (AI) explained Dr. Shaban Nejad. “The convergence between Big Data, AI, and its sub-disciplines is transforming the way health care decisions are made, processed, assessed and delivered. This phenomenon has given rise to emerging fields such as precision health that aims at analyzing factors influencing a population’s health (genetics, environments, and lifestyles) to provide individualized solutions that prevent disease and improve human health and well-being.”

The PopHR’s award winning paper is titled, “PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data” and can be found in Ann NY Acad Sci 1387: 1–153, Special Issue: “Data Science, Learning, and Applications to Biomedical and Health Sciences.”