Danielle Masursky

643 total citations
17 papers, 494 citations indexed

About

Danielle Masursky is a scholar working on Emergency Medical Services, Surgery and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Danielle Masursky has authored 17 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Emergency Medical Services, 9 papers in Surgery and 9 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Danielle Masursky's work include Healthcare Operations and Scheduling Optimization (12 papers), Cardiac, Anesthesia and Surgical Outcomes (9 papers) and Hemodynamic Monitoring and Therapy (7 papers). Danielle Masursky is often cited by papers focused on Healthcare Operations and Scheduling Optimization (12 papers), Cardiac, Anesthesia and Surgical Outcomes (9 papers) and Hemodynamic Monitoring and Therapy (7 papers). Danielle Masursky collaborates with scholars based in United States. Danielle Masursky's co-authors include Franklin Dexter, Nancy A. Nussmeier, Elisabeth U. Dexter, Bradley J. Hindman, Richard H. Epstein, Colleen E. O’Leary, Debra J. Szeluga, Muhammad Sarwar, Ruth E. Wachtel and Emine O. Bayman and has published in prestigious journals such as Anesthesia & Analgesia, Canadian Journal of Anesthesia/Journal canadien d anesthésie and Journal of Statistics Education.

In The Last Decade

Danielle Masursky

17 papers receiving 481 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danielle Masursky United States 14 332 260 248 180 72 17 494
Pieter S. Stepaniak Netherlands 12 257 0.8× 301 1.2× 358 1.4× 101 0.6× 28 0.4× 24 617
Hugh Flanagan United States 13 139 0.4× 180 0.7× 340 1.4× 66 0.4× 113 1.6× 26 535
Arthur M. Boudreaux United States 10 61 0.2× 245 0.9× 241 1.0× 28 0.2× 58 0.8× 19 383
C. L. G. Rutten Netherlands 10 65 0.2× 287 1.1× 220 0.9× 39 0.2× 60 0.8× 13 364
Alexander Jünger Germany 14 61 0.2× 267 1.0× 340 1.4× 39 0.2× 79 1.1× 48 512
James E. Pointer United States 13 133 0.4× 46 0.2× 67 0.3× 363 2.0× 108 1.5× 24 524
P. Mackay Australia 8 256 0.8× 255 1.0× 171 0.7× 64 0.4× 164 2.3× 16 522
B. Schwilk Germany 12 76 0.2× 225 0.9× 213 0.9× 64 0.4× 100 1.4× 30 479
Sally E. Rampersad United States 12 103 0.3× 140 0.5× 90 0.4× 24 0.1× 157 2.2× 22 322
M. Riccardo Colella United States 11 75 0.2× 38 0.1× 68 0.3× 304 1.7× 45 0.6× 26 348

Countries citing papers authored by Danielle Masursky

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Masursky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danielle Masursky

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

All Works

17 of 17 papers shown
1.
Dexter, Franklin, Danielle Masursky, Debra J. Szeluga, & Bradley J. Hindman. (2016). Work Habits Are Valid Components of Evaluations of Anesthesia Residents Based on Faculty Anesthesiologists’ Daily Written Comments About Residents. Anesthesia & Analgesia. 122(5). 1625–1633. 15 indexed citations
2.
Dexter, Franklin, Debra J. Szeluga, Danielle Masursky, & Bradley J. Hindman. (2016). Written Comments Made by Anesthesia Residents When Providing Below Average Scores for the Supervision Provided by the Faculty Anesthesiologist. Anesthesia & Analgesia. 122(6). 2000–2006. 21 indexed citations
3.
Dexter, Franklin, Danielle Masursky, & Bradley J. Hindman. (2014). Reliability and Validity of the Anesthesiologist Supervision Instrument When Certified Registered Nurse Anesthetists Provide Scores. Anesthesia & Analgesia. 120(1). 214–219. 23 indexed citations
4.
Dexter, Franklin, et al.. (2013). Role of Communication Systems in Coordinating Supervising Anesthesiologists’ Activities Outside of Operating Rooms. Anesthesia & Analgesia. 116(4). 898–903. 20 indexed citations
5.
Masursky, Danielle, et al.. (2012). Measure to Quantify the Influence of Time from End of Surgery to Tracheal Extubation on Operating Room Workflow. Anesthesia & Analgesia. 115(2). 402–406. 38 indexed citations
6.
Dexter, Franklin, et al.. (2012). Monitoring changes in individual surgeon’s workloads using anesthesia data. Canadian Journal of Anesthesia/Journal canadien d anesthésie. 59(6). 571–577. 26 indexed citations
7.
Masursky, Danielle, et al.. (2011). Surgeons' and Anesthesiologists' Perceptions of Turnover Times. Anesthesia & Analgesia. 112(2). 440–444. 33 indexed citations
8.
Dexter, Franklin, et al.. (2010). Meta-Analysis of Average and Variability of Time to Extubation Comparing Isoflurane with Desflurane or Isoflurane with Sevoflurane. Anesthesia & Analgesia. 110(5). 1433–1439. 64 indexed citations
9.
Dexter, Elisabeth U., et al.. (2010). Prospective Trial of Thoracic and Spine Surgeons' Updating of Their Estimated Case Durations at the Start of Cases. Anesthesia & Analgesia. 110(4). 1164–1168. 24 indexed citations
10.
Dexter, Franklin, Danielle Masursky, Ruth E. Wachtel, & Nancy A. Nussmeier. (2010). Application of an Online Reference for Reviewing Basic Statistical Principles of Operating Room Management. Journal of Statistics Education. 18(3). 10 indexed citations
11.
Dexter, Elisabeth U., et al.. (2009). Both Bias and Lack of Knowledge Influence Organizational Focus on First Case of the Day Starts. Anesthesia & Analgesia. 108(4). 1257–1261. 64 indexed citations
12.
Masursky, Danielle, et al.. (2009). Incentive Payments to Academic Anesthesiologists for Late Afternoon Work Did Not Influence Turnover Times. Anesthesia & Analgesia. 108(5). 1622–1626. 19 indexed citations
13.
Masursky, Danielle, Franklin Dexter, & Nancy A. Nussmeier. (2008). Operating Room Nursing Directors’ Influence on Anesthesia Group Operating Room Productivity. Anesthesia & Analgesia. 107(6). 1989–1996. 36 indexed citations
14.
Masursky, Danielle, et al.. (2008). Long-Term Forecasting of Anesthesia Workload in Operating Rooms from Changes in a Hospital’s Local Population Can Be Inaccurate. Anesthesia & Analgesia. 106(4). 1223–1231. 43 indexed citations
15.
Masursky, Danielle, et al.. (2008). Predicting Orthopedic Surgeons’ Preferences for Peripheral Nerve Blocks for Their Patients. Anesthesia & Analgesia. 106(2). 561–567. 7 indexed citations
16.
Dexter, Franklin, Elisabeth U. Dexter, Danielle Masursky, & Nancy A. Nussmeier. (2008). Systematic Review of General Thoracic Surgery Articles to Identify Predictors of Operating Room Case Durations. Anesthesia & Analgesia. 106(4). 1232–1241. 50 indexed citations
17.
Masursky, Danielle. (1997). Attrition of Low-Income, First Generation African-American Students at a Predominantly White, Urban University.. 1 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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