Maccabi Institute Demos MDClone, Showcasing Results from COVID-19 Collaboration

event synopsis

Last week, Professor Gabriel Chodick, a longtime member of the HCSRN, demonstrated how self-service data exploration and synthetic data generation accelerated COVID-19 research in Israel. Professor Chodick leads the epidemiological and clinical research arm of Maccabi Healthcare, an HMO with nearly one-third of the Israeli population under its care. Maccabi partnered with MDClone in 2017 to broaden access to data and eliminate long cycle times associated with analyst mediated research.

When the COVID-19 pandemic struck, Maccabi researchers had already experienced how much faster they could complete data projects using the MDClone platform. What once had taken months, now took only days to weeks.

This increased ‘speed-to-insight’ proved invaluable as the pandemic evolved and spread. MDClone enabled Maccabi to participate in joint research projects with Sheba Medical Center, Israel’s premier academic hospital.

During the forum, Professor Chodick recounted Maccabi’s response to the pandemic and highlighted some of the joint research conducted by Maccabi and Sheba investigators. The MDClone query tool was utilized to share actual synthetic patient data from both Maccabi and Sheba Medical Center.

THE DEMONSTRATION

In a demo during the forum, MDClone’s CMO Dr. Robi Wartenfeld demonstrated the MDClone platform to the viewers. In a hypothetical use case, Dr. Wartenfeld hoped to explore the positivity rates of patients after receiving the first COVID-19 vaccine dose versus the second vaccine dose. In minutes, Dr. Wartenfeld pulled a population of 1.4 million patients to analyze, creating events for the first vaccine and the second vaccine, and comparing the positivity rates associated with those queries.

Data showed only 1% of patients tested positive for COVID-19 after the first dose versus less than 1% of patients after the second dose of the vaccine. These outcomes were similar to those being shared publicly by Israeli Ministry of Health, thus validating the accuracy of the quick data analysis.

In a second use case example, Dr. Wartenfeld wanted to explore the rate of infectious diseases before and after the pandemic, assuming that mask-wearing had stifled these diseases over the past year. Again, in a few clicks, he pulled data targeting pneumonia before and after the pandemic, layering age, gender, medication choices, and more in order to narrow down the cohort population to a very specific example.

The original cohort was generated into synthetic data maintaining the same correlations as the original data. The new cohort (synthetic data set) fully reflected the original cohort, but none of the individual patients were included in this new data set, therefore, maintaining patient privacy. With synthetic data, Dr. Wartenfeld demonstrated how easy it was to share findings with colleagues, non-users, and outside organizations.

Lastly, Dr. Wartenfeld visualized the results with a few bar graphs, adjusting chart settings, saving the visuals for later use, and creating a library of discoveries based on the data. Visually, he was able to layer on demographics and adjust the charts based on specific interests.

Although it was just a short glimpse into the platform’s capabilities, the ability to explore data instantly, dynamically, and without mediators was apparent as Dr. Wartenfeld pulled insights within minutes for the audience. The brief MDClone platform demo gave viewers a glimpse into the possibilities of the system, the ease of use, the intuitive environment, and the speed at which data can be explored.

the takeaway

With the onset of the pandemic, Maccabi realized how important the MDClone platform was in order to accelerate research and investigate COVID-19 cases. In order to create the full picture of a COVID-19 patient from their first visit to a Maccabi clinic to the admittance to the Sheba Medical Hospital, the MDClone platform was able to tie the full patient story together, sharing information via synthetic data with the speed needed during this crisis. The collaboration between the two health systems enabled a better understanding of the COVID-19 patient journey.

speaker bio

Professor Chodick is the Head of Maccabitech Epidemiology and Database Research. Professor Chodick is a full-time professor at the School of Public Health at Tel Aviv University and an adjunct researcher at the Division of Cancer Epidemiology and Genetics at the National Institutes of Health. He earned an MSc and PhD degrees in Epidemiology from Tel Aviv University, where he also completed his Masters in Health Administration. He was a Fulbright Visiting Scholar at the School of Public Health at the University of North Carolina at Chapel Hill, and completed his post-doctoral fellowship at the National Cancer Institute in Bethesda, Md. Professor Chodick has authored or co-authored over 300 articles in peer-reviewed journals.

The Health Care Systems Research Network

The HCSRN brings together the research centers from many of the nation's best and most innovative health care systems. Collectively, the HCSRN represents more than 2,000 scientists and research staff with methodological and content expertise from an array of disciplines such as epidemiology, economics, disparities, outcomes and quality assessment, clinical trials, and genomics.

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