Todd R. Johnson

4.6k total citations
115 papers, 2.8k citations indexed

About

Todd R. Johnson is a scholar working on Artificial Intelligence, Health Information Management and Emergency Medical Services. According to data from OpenAlex, Todd R. Johnson has authored 115 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 25 papers in Health Information Management and 20 papers in Emergency Medical Services. Recurrent topics in Todd R. Johnson's work include Electronic Health Records Systems (23 papers), Patient Safety and Medication Errors (19 papers) and Healthcare Technology and Patient Monitoring (16 papers). Todd R. Johnson is often cited by papers focused on Electronic Health Records Systems (23 papers), Patient Safety and Medication Errors (19 papers) and Healthcare Technology and Patient Monitoring (16 papers). Todd R. Johnson collaborates with scholars based in United States, Belgium and South Africa. Todd R. Johnson's co-authors include Jiajie Zhang, Constance Johnson, Jack W. Smith, Vimla L. Patel, Jiajie Zhang, Vimla L. Patel, Danielle L. Paige, Tate Kubose, James P. Turley and Juliana J. Brixey and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Todd R. Johnson

106 papers receiving 2.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Todd R. Johnson United States 24 705 435 423 411 389 115 2.8k
Vimla L. Patel United States 28 1.3k 1.8× 443 1.0× 720 1.7× 291 0.7× 485 1.2× 64 3.2k
Emily S. Patterson United States 33 929 1.3× 1.2k 2.8× 816 1.9× 282 0.7× 493 1.3× 194 4.6k
Farah Magrabi Australia 34 1.2k 1.7× 462 1.1× 984 2.3× 734 1.8× 346 0.9× 127 3.9k
Jiajie Zhang United States 19 585 0.8× 279 0.6× 325 0.8× 147 0.4× 294 0.8× 52 1.7k
Raj M. Ratwani United States 26 979 1.4× 320 0.7× 575 1.4× 207 0.5× 330 0.8× 160 2.5k
Yan Xiao United States 33 513 0.7× 1.1k 2.6× 675 1.6× 181 0.4× 747 1.9× 221 4.9k
Arie Hasman Netherlands 31 1.2k 1.8× 183 0.4× 614 1.5× 444 1.1× 316 0.8× 229 3.5k
Leanne M. Currie Canada 27 584 0.8× 245 0.6× 920 2.2× 216 0.5× 155 0.4× 137 2.9k
Nancy Staggers United States 28 851 1.2× 290 0.7× 938 2.2× 116 0.3× 272 0.7× 98 2.5k
Elizabeth M. Borycki Canada 29 1.4k 2.0× 250 0.6× 1.4k 3.2× 171 0.4× 366 0.9× 278 3.6k

Countries citing papers authored by Todd R. Johnson

Since Specialization
Citations

This map shows the geographic impact of Todd R. Johnson'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 Todd R. Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd R. Johnson more than expected).

Fields of papers citing papers by Todd R. Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd R. Johnson. 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 Todd R. Johnson. The network helps show where Todd R. Johnson may publish in the future.

Co-authorship network of co-authors of Todd R. Johnson

This figure shows the co-authorship network connecting the top 25 collaborators of Todd R. Johnson. A scholar is included among the top collaborators of Todd R. Johnson 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 Todd R. Johnson. Todd R. Johnson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bernstam, Elmer V., et al.. (2025). Review of tools to support Target Trial Emulation. Journal of Biomedical Informatics. 171. 104897–104897.
2.
Kookal, Krishna Kumar, et al.. (2023). Designing audit and feedback dashboards for dentists to monitor their opioid prescribing. International Journal of Medical Informatics. 176. 105092–105092. 1 indexed citations
3.
Johnson, Todd R., Eta S. Berner, Sue S. Feldman, et al.. (2023). Mapping the delineation of practice to the AMIA foundational domains for applied health informatics. Journal of the American Medical Informatics Association. 30(10). 1593–1598.
4.
Johnson, Todd R. & Elmer V. Bernstam. (2023). Why is biomedical informatics hard? A fundamental framework. Journal of Biomedical Informatics. 140. 104327–104327. 2 indexed citations
5.
Diaz‐Garelli, Franck, Elmer V. Bernstam, MinJae Lee, et al.. (2019). DataGauge: A Practical Process for Systematically Designing and Implementing Quality Assessments of Repurposed Clinical Data. SHILAP Revista de lepidopterología. 7(1). 32–32. 14 indexed citations
6.
Bernstam, Elmer V., et al.. (2016). Improving the utility of MeSH® terms using the TopicalMeSH representation. Journal of Biomedical Informatics. 61. 77–86. 19 indexed citations
7.
Zozus, Meredith, Carl F. Pieper, Constance Johnson, et al.. (2015). Factors Affecting Accuracy of Data Abstracted from Medical Records. PLoS ONE. 10(10). e0138649–e0138649. 42 indexed citations
8.
Joffe, Erel, James P. Turley, Kevin O. Hwang, et al.. (2013). Errors in after-hours phone consultations: a simulation study. BMJ Quality & Safety. 23(5). 398–405. 2 indexed citations
9.
Johnson, Todd R., et al.. (2012). Abstract 107: Performing Hands-on Defibrillation in Out-of-Hospital Cardiac Arrest Can Result in the Mild, Subjective Perception of Current to Providers. Circulation. 4 indexed citations
10.
Jones, Stephen L., et al.. (2012). Cross-terminology mapping challenges: A demonstration using medication terminological systems. Journal of Biomedical Informatics. 45(4). 613–625. 49 indexed citations
11.
Bao, Ruijun, et al.. (2005). What vs. Where: Which Direction Is Faster?. eScholarship (California Digital Library). 27(27). 1 indexed citations
12.
Wang, Hongbin, et al.. (2004). Spatial Updating in Intrinsic Frames of Reference. eScholarship (California Digital Library). 26(26). 2 indexed citations
13.
Zhang, Jiajie, Vimla L. Patel, Todd R. Johnson, & Edward H. Shortliffe. (2004). A cognitive taxonomy of medical errors. Journal of Biomedical Informatics. 37(3). 193–204. 161 indexed citations
14.
Johnson, Todd R., Hongbin Wang, & Jiajie Zhang. (2003). An ACT-R Model of Human Object-Location Memory. eScholarship (California Digital Library). 25(25). 4 indexed citations
15.
Yang, Lan, et al.. (2002). Redesign of Pedigree Displays through User-centered Visualization. Europe PMC (PubMed Central). 1206–1206.
16.
Johnson, Constance, Todd R. Johnson, Vimla L. Patel, & James P. Turley. (2002). The Feasibility of Using Propositional Analysis as a Method for Understanding Differences Between Physicians and Nurses Reading EMRs. Digital Commons-TMC (Texas Medical Center). 1053–1053. 1 indexed citations
17.
Johnson, Todd R., Vimla L. Patel, & James P. Turley. (2001). Cognitive Differences in Chart Reading: A Comparison of Nurses and Physicians.. Digital Commons-TMC (Texas Medical Center). 940–940. 1 indexed citations
18.
Wang, Hongbin, Jiajie Zhang, & Todd R. Johnson. (2000). Human Belief Revision and the Order Effect. eScholarship (California Digital Library). 22(22). 11 indexed citations
19.
Zhang, Jiajie, et al.. (2000). The Representational Effect in Complex Systems: A Distributed Representation Approach. eScholarship (California Digital Library). 22(22). 2 indexed citations
20.
Bunn, Christopher, et al.. (1999). Predicting the Risk of Obesity Using a Bayesian Network. Digital Commons-TMC (Texas Medical Center). 1035–1035. 3 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.

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