Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Telehealth transformation: COVID-19 and the rise of virtual care
20201.1k citationsEric G. Poon et al.Journal of the American Medical Informatics Associationprofile →
Effect of Bar-Code Technology on the Safety of Medication Administration
2010380 citationsEric G. Poon, Carol Keohane et al.profile →
Ethics in Patient Preferences for Artificial Intelligence–Drafted Responses to Electronic Messages
202512 citationsBenjamin A. Goldstein, Vardit Ravitsky et al.JAMA Network Openprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Eric G. Poon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eric G. Poon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric G. Poon more than expected).
This network shows the impact of papers produced by Eric G. Poon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eric G. Poon. The network helps show where Eric G. Poon may publish in the future.
Co-authorship network of co-authors of Eric G. Poon
This figure shows the co-authorship network connecting the top 25 collaborators of Eric G. Poon.
A scholar is included among the top collaborators of Eric G. Poon based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Eric G. Poon. Eric G. Poon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Goldstein, Benjamin A., Vardit Ravitsky, Jean‐Christophe Bélisle‐Pipon, et al.. (2025). Ethics in Patient Preferences for Artificial Intelligence–Drafted Responses to Electronic Messages. JAMA Network Open. 8(3). e250449–e250449.12 indexed citations breakdown →
Wright, Adam, Eric G. Poon, Jonathan S. Wald, et al.. (2008). Effectiveness of health maintenance reminders provided directly to patients.. PubMed. 1183–1183.9 indexed citations
9.
El‐Kareh, Robert, Tejal K. Gandhi, Eric G. Poon, et al.. (2008). Trends in clinician perceptions of a new electronic health record.. PubMed. 940–940.2 indexed citations
10.
Wright, Adam, et al.. (2008). Ability to perform registry functions among practices with and without electronic health records.. PubMed. 1052–1052.2 indexed citations
11.
Volk, Lynn A., et al.. (2008). Do electronic health records create more errors than they prevent?. PubMed. 1143–1143.2 indexed citations
Simon, Steven R., Rainu Kaushal, Paul D. Cleary, et al.. (2006). Correlates of electronic health record adoption in office practices: a statewide survey.. PubMed. 1098–1098.22 indexed citations
14.
Simon, Steven R., Rainu Kaushal, Chelsea Jenter, et al.. (2006). Electronic health records: which practices have them and how are clinicians using them?. PubMed. 1097–1097.4 indexed citations
Poon, Eric G., Samuel J. Wang, Tejal K. Gandhi, et al.. (2002). A Comprehensive Outpatient Results Manager with Decision Support: Design Considerations and Architecture.. Europe PMC (PubMed Central). 1132–1132.2 indexed citations
20.
Poon, Eric G., Gilad J. Kuperman, Julie Fiskio, & David W. Bates. (2001). Real-Time Notification of Laboratory Data Requested by Users through Alphanumeric Pagers. Europe PMC (PubMed Central). 999–999.2 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.