David Rushlow

1.1k total citations
25 papers, 498 citations indexed

About

David Rushlow is a scholar working on General Health Professions, Cardiology and Cardiovascular Medicine and Public Health, Environmental and Occupational Health. According to data from OpenAlex, David Rushlow has authored 25 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in General Health Professions, 4 papers in Cardiology and Cardiovascular Medicine and 4 papers in Public Health, Environmental and Occupational Health. Recurrent topics in David Rushlow's work include Primary Care and Health Outcomes (7 papers), Cardiac Arrhythmias and Treatments (3 papers) and Atrial Fibrillation Management and Outcomes (3 papers). David Rushlow is often cited by papers focused on Primary Care and Health Outcomes (7 papers), Cardiac Arrhythmias and Treatments (3 papers) and Atrial Fibrillation Management and Outcomes (3 papers). David Rushlow collaborates with scholars based in United States, Qatar and Japan. David Rushlow's co-authors include Michelle A. Lampman, Rachel Giblon, Nilay D. Shah, Jonathan Inselman, Rozalina G. McCoy, Shaheen Kurani, George Divine, Michelle Witkop, Angela Lambing and Robert J. Stroebel and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and BMJ.

In The Last Decade

David Rushlow

21 papers receiving 488 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Rushlow United States 10 111 109 98 65 61 25 498
Sayaka Shimizu Japan 16 80 0.7× 62 0.6× 151 1.5× 64 1.0× 72 1.2× 71 719
Lih‐Wen Mau United States 14 93 0.8× 121 1.1× 154 1.6× 43 0.7× 71 1.2× 47 731
Talia Foster United States 13 132 1.2× 66 0.6× 81 0.8× 52 0.8× 64 1.0× 15 742
Clark DuMontier United States 16 241 2.2× 80 0.7× 81 0.8× 37 0.6× 60 1.0× 62 890
Chen Dai United States 14 110 1.0× 37 0.3× 39 0.4× 98 1.5× 28 0.5× 47 554
Thomas V. Joshua United States 9 64 0.6× 75 0.7× 98 1.0× 28 0.4× 23 0.4× 20 378
Sébastien Lamy France 13 111 1.0× 21 0.2× 103 1.1× 32 0.5× 46 0.8× 60 507
Caitlyn T. Wilke United States 8 106 1.0× 69 0.6× 85 0.9× 24 0.4× 33 0.5× 9 624
Nikhil K. Mull United States 9 76 0.7× 31 0.3× 81 0.8× 31 0.5× 53 0.9× 22 437
Kathleen Lang United States 16 246 2.2× 79 0.7× 83 0.8× 43 0.7× 115 1.9× 33 764

Countries citing papers authored by David Rushlow

Since Specialization
Citations

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

Fields of papers citing papers by David Rushlow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Rushlow. 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 David Rushlow. The network helps show where David Rushlow may publish in the future.

Co-authorship network of co-authors of David Rushlow

This figure shows the co-authorship network connecting the top 25 collaborators of David Rushlow. A scholar is included among the top collaborators of David Rushlow 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 David Rushlow. David Rushlow 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.
2.
Olofson, Amy, Ryan J. Lennon, Kan Liu, et al.. (2025). Detection of Undiagnosed Liver Cirrhosis via Artificial Intelligence-Enabled Electrocardiogram (DULCE): Rationale and design of a pragmatic cluster randomized clinical trial. Contemporary Clinical Trials Communications. 45. 101494–101494.
3.
Kolla, Bhanu Prakash, et al.. (2025). The impact of GLP-1 agonists on sleep disorders: spotlight on sleep apnea. Expert Opinion on Pharmacotherapy. 26(14-15). 1529–1538.
4.
Gerhart, James, et al.. (2025). A Family Medicine Shared Vision and Road Map for AI in Primary Care. The Annals of Family Medicine. 23(5). 481.2–483. 1 indexed citations
5.
Lópes, Renato D., Steven J. Atlas, Alan S. Go, et al.. (2024). Effect of Screening for Undiagnosed Atrial Fibrillation on Stroke Prevention. Journal of the American College of Cardiology. 84(21). 2073–2084. 17 indexed citations
6.
Jiang, Yiqun, et al.. (2024). Predicting Provider Workload Using Predicted Patient Risk Score and Social Determinants of Health in Primary Care Setting. Applied Clinical Informatics. 15(3). 511–527. 1 indexed citations
7.
Rushlow, David, Tom D. Thacher, & Barbara Barry. (2024). Building Capacity for Pragmatic Trials of Digital Technology in Primary Care. Mayo Clinic Proceedings. 99(3). 491–501.
8.
9.
Singer, Daniel E., Steven J. Atlas, Alan S. Go, et al.. (2024). Atrial Fibrillation Burden on a 14-Day ECG Monitor. JACC. Clinical electrophysiology. 11(1). 110–119. 4 indexed citations
10.
Bernard, Matthew, Michael Halasy, David Rushlow, et al.. (2022). The effect of primary care clinician type and care team characteristics on health care costs. Journal of Evaluation in Clinical Practice. 28(6). 1055–1060. 1 indexed citations
11.
Berg, Bjorn P., et al.. (2022). Balancing Clinician Workload Through Strategic Patient Panel Designs. Quality Management in Health Care. 32(3). 137–144. 1 indexed citations
12.
Rushlow, David, Ivana T. Croghan, Jonathan Inselman, et al.. (2022). Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care.. Mayo Clinic Proceedings. 97(11). 2076–2085. 17 indexed citations
13.
Barry, Barbara, Xuan Zhu, Emma Behnken, et al.. (2022). Provider Perspectives on Artificial Intelligence–Guided Screening for Low Ejection Fraction in Primary Care: Qualitative Study. SHILAP Revista de lepidopterología. 1(1). e41940–e41940. 9 indexed citations
14.
Bernard, Matthew, Summer V. Allen, Michael Halasy, et al.. (2021). Clinician Care Team Composition and Health Care Utilization. SHILAP Revista de lepidopterología. 5(2). 338–346. 5 indexed citations
15.
Ponamgi, Shiva, Konstantinos C. Siontis, David Rushlow, et al.. (2021). Screening and management of atrial fibrillation in primary care. BMJ. 373. n379–n379. 14 indexed citations
16.
Lampman, Michelle A., Aravind Chandrasekaran, Megan E. Branda, et al.. (2021). Optimizing Huddle Engagement Through Leadership and Problem Solving Within Primary Care: Results from a Cluster-Randomized Trial. Journal of General Internal Medicine. 36(8). 2292–2299. 5 indexed citations
17.
Lampman, Michelle A., Randy Foss, Gregory M. Garrison, et al.. (2020). Relationship of Clinician Care Team Composition and Diabetes Quality Outcomes. Population Health Management. 24(4). 502–508. 6 indexed citations
18.
Branda, Megan E., Aravind Chandrasekaran, Nilay D. Shah, et al.. (2018). Optimizing huddle engagement through leadership and problem-solving within primary care: A study protocol for a cluster randomized trial. Trials. 19(1). 536–536. 14 indexed citations
19.
Witkop, Michelle, et al.. (2011). Assessment of acute and persistent pain management in patients with haemophilia. Haemophilia. 17(4). 612–619. 47 indexed citations
20.
Witkop, Michelle, et al.. (2011). A national study of pain in the bleeding disorders community: a description of haemophilia pain. Haemophilia. 18(3). e115–9. 75 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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