Dana Siegal

719 total citations · 1 hit paper
12 papers, 406 citations indexed

About

Dana Siegal is a scholar working on Pharmacy, Family Practice and General Health Professions. According to data from OpenAlex, Dana Siegal has authored 12 papers receiving a total of 406 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Pharmacy, 7 papers in Family Practice and 5 papers in General Health Professions. Recurrent topics in Dana Siegal's work include Medical Malpractice and Liability Issues (9 papers), Clinical Reasoning and Diagnostic Skills (7 papers) and Healthcare cost, quality, practices (5 papers). Dana Siegal is often cited by papers focused on Medical Malpractice and Liability Issues (9 papers), Clinical Reasoning and Diagnostic Skills (7 papers) and Healthcare cost, quality, practices (5 papers). Dana Siegal collaborates with scholars based in United States and Kenya. Dana Siegal's co-authors include David E. Newman‐Toker, Adam C. Schaffer, C. Winnie Yu‐Moe, Ali S. Saber Tehrani, Yuxin Zhu, Najlla Nassery, Zheyu Wang, Mehdi Fanai, Gwendolyn Clemens and Mark L. Graber and has published in prestigious journals such as Journal of Clinical Oncology, JAMA Network Open and BMJ Quality & Safety.

In The Last Decade

Dana Siegal

12 papers receiving 390 citations

Hit Papers

Burden of serious harms from diagnostic error in the USA 2023 2026 2024 2025 2023 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dana Siegal United States 7 189 94 89 84 74 12 406
C. Winnie Yu‐Moe United States 6 163 0.9× 62 0.7× 73 0.8× 73 0.9× 71 1.0× 11 339
Mehdi Fanai United States 6 168 0.9× 54 0.6× 66 0.7× 55 0.7× 43 0.6× 8 307
Lindsey Wilson United States 8 148 0.8× 78 0.8× 86 1.0× 76 0.9× 42 0.6× 16 418
R. Rao United States 6 72 0.4× 172 1.8× 45 0.5× 72 0.9× 28 0.4× 8 404
Esteban Gershanik United States 9 20 0.1× 92 1.0× 41 0.5× 81 1.0× 19 0.3× 20 305
Laila Cochón United States 11 28 0.1× 138 1.5× 26 0.3× 37 0.4× 14 0.2× 38 317
Brian Gale United States 6 60 0.3× 217 2.3× 18 0.2× 22 0.3× 24 0.3× 8 286
K. Piper United Kingdom 14 40 0.2× 514 5.5× 37 0.4× 42 0.5× 18 0.2× 38 569
Paul A. Bergl United States 8 63 0.3× 42 0.4× 35 0.4× 36 0.4× 14 0.2× 27 202
Eugene Lucas United States 7 12 0.1× 89 0.9× 54 0.6× 65 0.8× 5 0.1× 9 339

Countries citing papers authored by Dana Siegal

Since Specialization
Citations

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

Fields of papers citing papers by Dana Siegal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dana Siegal

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

All Works

12 of 12 papers shown
1.
Krevat, Seth, et al.. (2023). Identifying Electronic Health Record Contributions to Diagnostic Error in Ambulatory Settings Through Legal Claims Analysis. JAMA Network Open. 6(4). e238399–e238399. 3 indexed citations
2.
Newman‐Toker, David E., Najlla Nassery, Adam C. Schaffer, et al.. (2023). Burden of serious harms from diagnostic error in the USA. BMJ Quality & Safety. 33(2). 109–120. 76 indexed citations breakdown →
3.
Rosenkrantz, Andrew B., et al.. (2021). Oncologic Errors in Diagnostic Radiology: A 10-Year Analysis Based on Medical Malpractice Claims. Journal of the American College of Radiology. 18(9). 1310–1316. 4 indexed citations
6.
Newman‐Toker, David E., Adam C. Schaffer, C. Winnie Yu‐Moe, et al.. (2019). Serious misdiagnosis-related harms in malpractice claims: The “Big Three” – vascular events, infections, and cancers. Diagnosis. 6(3). 227–240. 104 indexed citations
7.
Siegal, Dana, et al.. (2019). Harnessing the power of medical malpractice data to improve patient care. Journal of Healthcare Risk Management. 39(3). 28–36. 3 indexed citations
8.
Nass, Sharyl J., Christopher R. Cogle, James A. Brink, et al.. (2019). Improving Cancer Diagnosis and Care: Patient Access to Oncologic Imaging Expertise. Journal of Clinical Oncology. 37(20). 1690–1694. 17 indexed citations
9.
Siegal, Dana, et al.. (2017). The role of radiology in diagnostic error: a medical malpractice claims review. Diagnosis. 4(3). 125–131. 23 indexed citations
10.
Siegal, Dana, et al.. (2017). Developing risk management dashboards using risk and quality measures: A visual best practices approach. Journal of Healthcare Risk Management. 37(2). 8–28. 5 indexed citations
11.
Siegal, Dana, et al.. (2015). Data as a catalyst for change: Stories from the frontlines. Journal of Healthcare Risk Management. 34(3). 18–25. 6 indexed citations
12.
Graber, Mark L., et al.. (2015). Electronic Health Record–Related Events in Medical Malpractice Claims. Journal of Patient Safety. 15(2). 77–85. 68 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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